Global Infectious Disease Surveillance and Detection
Content
Global Infectious Disease Surveillance and
Detection: Assessing the Challenges -- Finding
Solutions, Workshop Summary
Forum on Microbial Threats, Stanley M. Lemon,
Margaret A. Hamburg, P. Frederick Sparling, Eileen R.
Choffnes, and Alison Mack, Rapporteurs
ISBN: 0-309-11115-3, 284 pages, 6 x 9, (2007)
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Global Infectious Disease
Surveillance and Detection:
Assessing the Challenges—
Finding Solutions
Workshop Summary
Rapporteurs: Stanley M. Lemon, Margaret A. Hamburg,
P. Frederick Sparling, Eileen R. Choffnes, and Alison Mack
Forum on Microbial Threats
Board on Global Health
THE NATIONAL ACADEMIES PRESS
Washington, D.C.
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Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
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Research, and Defense Threat Reduction Agency; U.S. Department of Veterans Affairs;
U.S. Department of Homeland Security; Lawrence Livermore National Laboratory;
American Society for Microbiology; Sanofi Pasteur; Burroughs Wellcome Fund; Pfizer;
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Institute of Medicine. 2007. Global infectious disease surveillance and detection: Assessing the challenges—finding solutions. Workshop summary. Washington, DC: The National
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Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Willing is not enough; we must do.”
—Goethe
Advising the Nation. Improving Health.
Copyright © National Academy of Sciences. All rights reserved.
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Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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FORUM ON MICROBIAL THREATS
STANLEY M. LEMON (Chair), School of Medicine, University of Texas
Medical Branch, Galveston
MARGARET A. HAMBURG (Vice-chair), Nuclear Threat Initiative/Global
Health & Security Initiative, Washington, DC
P. FREDERICK SPARLING (Vice-chair), University of North Carolina,
Chapel Hill
DAVID W. K. ACHESON, Center for Food Safety and Applied Nutrition,
Food and Drug Administration, Rockville, Maryland
RUTH L. BERKELMAN, Emory University, Center for Public Health Pre
paredness and Research, Rollins School of Public Health, Atlanta, Georgia
ENRIQUETA C. BOND, Burroughs Wellcome Fund, Research Triangle Park,
North Carolina
ROGER G. BREEZE, Centaur Science Group, Washington, DC
STEVEN J. BRICKNER, Pfizer Global Research and Development, Pfizer
Inc., Groton, Connecticut
NANCY CARTER-FOSTER, Program for Emerging Infections and
HIV/AIDS, U.S. Department of State, Washington, DC
GAIL H. CASSELL, Eli Lilly & Company, Indianapolis, Indiana
BILL COLSTON, Lawrence Livermore National Laboratory, Livermore,
California
RALPH L. ERICKSON, Global Emerging Infections Surveillance and
Response System, Department of Defense, Silver Spring, Maryland
MARK B. FEINBERG, Merck Vaccine Division, Merck & Co., West Point,
Pennsylvania
J. PATRICK FITCH, National Biodefense Analysis and Countermeasures
Center, Frederick, Maryland
DARRELL R. GALLOWAY, Medical S&T Division, Defense Threat
Reduction Agency, Fort Belvoir, Virginia
S. ELIZABETH GEORGE, Biological and Chemical Countermeasures
Program, Department of Homeland Security, Washington, DC
JESSE L. GOODMAN, Center for Biologics Evaluation and Research, Food
and Drug Administration, Rockville, Maryland
EDUARDO GOTUZZO, Instituto de Medicina Tropical–Alexander von
Humbolt, Universidad Peruana Cayetano Heredia, Lima, Peru
JO HANDELSMAN, College of Agricultural and Life Sciences, University of
Wisconsin, Madison
CAROLE A. HEILMAN, Division of Microbiology and Infectious Diseases,
National Institute of Allergy and Infectious Diseases, National Institutes of
Health, Bethesda, Maryland
DAVID L. HEYMANN, Polio Eradication, World Health Organization,
Geneva, Switzerland
PHIL HOSBACH, New Products and Immunization Policy, Sanofi Pasteur,
Swiftwater, Pennsylvania
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
JAMES M. HUGHES, Global Infectious Diseases Program, Emory
University, Atlanta, Georgia
STEPHEN A. JOHNSTON, Arizona BioDesign Institute, Arizona State
University, Tempe
GERALD T. KEUSCH, Boston University School of Medicine and Boston
University School of Public Health, Massachusetts
RIMA F. KHABBAZ, National Center for Preparedness, Detection and
Control of Infectious Diseases, Centers for Disease Control and
Prevention, Atlanta, Georgia
LONNIE J. KING, Center for Zoonotic, Vectorborne, and Enteric Diseases,
Centers for Disease Control and Prevention, Atlanta, Georgia
GEORGE W. KORCH, U.S. Army Medical Research Institute for Infectious
Diseases, Fort Detrick, Maryland
JOSHUA LEDERBERG, The Rockefeller University, New York
LYNN G. MARKS, Medicine Development Center, GlaxoSmithKline,
Collegeville, Pennsylvania
EDWARD McSWEEGAN, National Institute of Allergy and Infectious
Diseases, National Institutes of Health, Bethesda, Maryland
STEPHEN S. MORSE, Center for Public Health Preparedness, Columbia
University, New York
MICHAEL T. OSTERHOLM, Center for Infectious Disease Research and
Policy, School of Public Health, University of Minnesota, Minneapolis
GEORGE POSTE, Arizona BioDesign Institute, Arizona State University,
Tempe
DAVID A. RELMAN, Stanford University, Palo Alto, California
GARY A. ROSELLE, Central Office, Veterans Health Administration,
Department of Veterans Affairs, Washington, DC
JANET SHOEMAKER, Office of Public Affairs, American Society for
Microbiology, Washington, DC
BRIAN J. STASKAWICZ, Department of Plant and Microbial Biology,
University of California, Berkeley
TERENCE TAYLOR, International Council for the Life Sciences,
Washington, DC
Staff
EILEEN CHOFFNES, Forum Director
ALLISON BRANTLEY, Senior Program Assistant*
SARAH BRONKO, Senior Program Assistant†
ALISON MACK, Science Writer
KATE SKOCZDOPOLE, Research Associate
*Ending June 2007.
†Beginning June 2007.
vi
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
BOARD ON GLOBAL HEALTH
Margaret Hamburg (chair), Consultant, Nuclear Threat Initiative,
Washington, DC
George Alleyne, Director Emeritus, Pan American Health Organization,
Washington, DC
Donald Berwick, Clinical Professor of Pediatrics and Health Care Policy,
Harvard Medical School, and President and Chief Executive Officer,
Institute of Healthcare Improvement, Boston, Massachusetts
Jo Ivey Boufford (IOM Foreign Secretary), President, New York Academy of
Medicine, New York
David R. Challoner, Vice President for Health Affairs, Emeritus, University of
Florida, Gainesville
Ciro de Quadros, Albert B. Sabin Vaccine Institute, Washington, DC
Sue Goldie, Associate Professor of Health Decision Science, Department
of Health Policy and Management, Center for Risk Analysis, Harvard
University School of Public Health, Boston, Massachusetts
Richard Guerrant, Thomas H. Hunter Professor of International Medicine
and Director, Center for Global Health, University of Virginia School of
Medicine, Charlottesville
Gerald T. Keusch, Assistant Provost for Global Health, Boston University
School of Medicine, and Associate Dean for Global Health, Boston
University School of Public Health, Massachusetts
Jeffrey Koplan, Vice President for Academic Health Affairs, Emory
University, Atlanta, Georgia
Sheila Leatherman, Research Professor, University of North Carolina School of
Public Health, Chapel Hill
Michael Merson, Director, Duke Global Health Institute, Duke University,
Durham, NC
Mark L. Rosenberg, Executive Director, Task Force for Child Survival and
Development, Emory University, Decatur, Georgia
Philip Russell, Professor Emeritus, Bloomberg School of Public Health, The
Johns Hopkins University, Baltimore, Maryland
Staff
Patrick Kelley, Director
Allison Brantley, Senior Program Assistant
IOM boards do not review or approve individual reports and are not asked to endorse conclusions
and recommendations. The responsibility for the content of the reports rests with the authors and the
institution.
vii
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Reviewers
This report has been reviewed in draft form by individuals chosen for their
diverse perspectives and technical expertise, in accordance with procedures
approved by the National Research Council’s Report Review Committee. The
purpose of this independent review is to provide candid and critical comments
that will assist the institution in making its published report as sound as possible
and to ensure that the report meets institutional standards for objectivity, evidence, and responsiveness to the study charge. The review comments and draft
manuscript remain confidential to protect the integrity of the deliberative process.
We wish to thank the following individuals for their review of this report:
John Besser, Public Health Laboratory, Minnesota Department of Health
R. James Cook, Department of Plant Pathology, Washington State
University
Charlotte A Gaydos, Division of Infectious Diseases, The Johns Hopkins
University and International STD Reference Laboratory
Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the final draft of the report
before its release. The review of this report was overseen by Melvin Worth,
Scholar-in-Residence, Institute of Medicine. Appointed by the Institute of Medicine, he was responsible for making certain that an independent examination of
this report was carried out in accordance with institutional procedures and that all
review comments were carefully considered. Responsibility for the final content
of this report rests entirely with the authoring committee and the institution.
ix
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Preface
The Forum on Emerging Infections was created by the Institute of Medicine
(IOM) in 1996 in response to a request from the Centers for Disease Control and
Prevention (CDC) and the National Institutes of Health (NIH). The purpose of
the Forum is to provide structured opportunities for leaders from government,
academia, and industry to meet and examine issues of shared concern regarding
research, prevention, detection, and management of emerging or reemerging
infectious diseases. In pursuing this task, the Forum provides a venue to foster
the exchange of information and ideas, identify areas in need of greater attention,
clarify policy issues by enhancing knowledge and identifying points of agreement, and inform decision makers about science and policy issues. The Forum
seeks to illuminate issues rather than resolve them; for this reason, it does not
provide advice or recommendations on any specific policy initiative pending
before any agency or organization. Its value derives instead from the diversity
of its membership and from the contributions that individual members make
throughout the activities of the Forum. In September 2003, the Forum changed
its name to the Forum on Microbial Threats.
About the Workshop
Early detection is essential to the control of emerging, reemerging, and novel
infectious diseases, including agents of bioterrorism. Containing the spread of
such a disease in a profoundly interconnected world requires active vigilance
for signs of an outbreak, rapid recognition of its presence, and diagnosis of
its microbial cause, as well as strategies and resources for an appropriate and
efficient response. While often viewed in terms of public health, the challenges
xi
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
xii
PREFACE
of detecting natural and intentionally introduced disease outbreaks are equally
shared by the plant and animal health communities.
Currently, disease surveillance and detection relies heavily on the astute
individual: the clinician, veterinarian, grower, livestock manager, or agricultural
extension agent who notices atypical or suspicious symptoms and brings them
to the attention of public health, veterinary medicine, or agricultural officials—
including academicians and zoological parks. While most developed countries
have a surveillance system in place and the ability to detect and diagnose human,
animal, and plant diseases, many developing countries—where most of the global
population resides—may not have the resources or infrastructure to support such
activities. Under such circumstances, disease detection occurs on the local level
and depends entirely on the early recognition of both known and novel infectious
diseases.
Technological advances in disease surveillance and detection such as regional
syndromic surveillance, bioinformatics, and new rapid diagnostic methods have
the potential to improve infectious disease control and prevention efforts. Further
improvements are likely to result from ongoing innovations in infectious disease
diagnostics, reporting, and surveillance. However, a number of challenges remain
to be met before deployment of rapid, low-cost, sensitive, and specific point-ofcare disease diagnostics become a reality.
The Forum on Microbial Threats of the Institute of Medicine hosted a public
workshop in Washington, DC, on December 12 and 13, 2006, to consider the
scientific and policy issues—some of them long standing, others more recently
arisen—relevant to the practice of disease surveillance and detection. Through
invited presentations and discussions, participants examined current and emerging methods and strategies for the surveillance and detection of human, animal,
and plant diseases, and assessed the resource needs and opportunities for improving and coordinating infectious disease surveillance, detection, and reporting.
Acknowledgments
The Forum on Microbial Threats and the IOM wish to express their warmest
appreciation to the individuals and organizations who gave their valuable time to
provide information and advice to the Forum through their participation in this
workshop. A full list of presenters can be found in Appendix A.
The Forum is indebted to the IOM staff who contributed during the course
of the workshop and the production of this workshop summary. On behalf of the
Forum, we gratefully acknowledge the efforts led by Eileen Choffnes, director
of the Forum, and Kate Skoczdopole, research associate, for dedicating much
effort and time to developing this workshop’s agenda and for their thoughtful and
insightful approach and skill in translating the workshop’s proceedings and discussion into this workshop summary. We would also like to thank the following
IOM staff and consultants for their valuable contributions to this activity: Patrick
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
xiii
PREFACE
Kelley, Alison Mack, Sarah Bronko, Bronwyn Schrecker, Allison Brantley, Lara
Andersen, and Laura Penny.
Finally, the Forum wishes to recognize the sponsors that supported this
activity. Financial support for this project was provided by the U.S. Department
of Health and Human Services: National Institutes of Health, National Institute
of Allergy and Infectious Diseases, Centers for Disease Control and Prevention,
and Food and Drug Administration; U.S. Department of Defense: Global Emerging Infections Surveillance and Response System, Walter Reed Army Institute of
Research, and Defense Threat Reduction Agency; U.S. Department of Veterans
Affairs; U.S. Department of Homeland Security; Lawrence Livermore National
Laboratory; American Society for Microbiology; Sanofi Pasteur; Burroughs
Wellcome Fund; Pfizer; GlaxoSmithKline; Infectious Diseases Society of America; and the Merck Company Foundation. The views presented in this workshop
summary report are those of the workshop participants and rapporteurs and are
not necessarily those of the Forum on Microbial Threats or its sponsors.
Stanley M. Lemon, Chair
Margaret A. Hamburg, Vice-chair
P. Frederick Sparling, Vice-chair
Forum on Microbial Threats
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Contents
Summary and Assessment
1
1 Surveillance Strategies
Overview, 45
Syndromic Surveillance: Moving from Theory to Practice, 49
Patrick W. Kelley, M.D., Dr.P.H.
Syndromic Surveillance in Public Health Practice, 63
Michael A. Stoto, Ph.D.
Implications of “Real Time” Versus “Batch Reporting” for
Surveillance, 72
Joseph Lombardo, M.S.
One World—One Health: Wildlife and Emerging Disease
Surveillance, 77
William B. Karesh, D.V.M.
Agricultural Biosecurity: Threats and Impacts for Plant Pathogens, 86
Jacqueline Fletcher, Ph.D., and James P. Stack, Ph.D.
Plant Biosecurity Infrastructure for Disease Surveillance and
Diagnostics, 95
James P. Stack, Ph.D., and Jacqueline Fletcher, Ph.D.
References, 102
2
Surveillance Networks
Overview, 107
Global Infectious Disease Surveillance and Early Warning Systems:
ProMED and ProMED-Mail, 109
Stephen S. Morse, Ph.D.
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Copyright © National Academy of Sciences. All rights reserved.
45
107
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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xvi
CONTENTS
Global Public Health Surveillance: The Role of Nontraditional
Surveillance Tools, 116
Abla Mawudeku, M.P.H., M. Ruben, M.D., Ph.D.,
and R. Lemay, B.Sc., M.B.A.
HealthMap: Internet-Based Emerging Infectious Disease
Intelligence, 122
John S. Brownstein, Ph.D., Clark C. Freifeld, B.S., Ben Y. Reis, Ph.D.,
and Kenneth D. Mandl, M.D., M.P.H.
Using Cell Phone Technology for Infectious Disease Surveillance in
Low-Resource Environments: A Case Study from Peru, 136
Pamela R. Johnson, Ph.D., and David L. Blazes, M.D., M.P.H.
�����������������������������������������������������������
References, 153
3
Detection and Diagnostics
158
Overview, 158
Partnering for Better Microbial Diagnostics, 160
Mark D. Perkins, M.D., and Peter M. Small, M.D.
Rapid Infectious Disease Diagnostic Assays, 165
Mark J. Wolcott, Ph.D., Randal J. Schoepp, Ph.D.,
David A. Norwood, Ph.D., and David R. Shoemaker, Ph.D.
Emerging Tools for Microbial Diagnosis, Surveillance, and
Discovery, 177
W. Ian Lipkin, M.D., and Thomas Briese, Ph.D.
The Potential Importance of Presymptomatic, Host-Based Diagnosis in
Biodefense and Standard Health Care, 193
Stephen Albert Johnston, Ph.D.
References, 207
4
Resource Needs and Opportunities
Overview, 213
Coordination of Disease Surveillance, Detection, Diagnostics, and
Reporting, 216
William D. Hueston, D.V.M., Ph.D.
Improving Infectious Disease Surveillance and Detection: A Public
Health Laboratory Perspective, 224
Frances Pouch Downes, Dr.P.H.
References, 230
Appendixes
A Agenda
B Acronyms
C Forum Member Biographies
Copyright © National Academy of Sciences. All rights reserved.
213
233
238
243
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Tables, Figures, and Boxes
Tables
SA-1
SA-2
1-1
1-2
1-3
Animal Diseases Associated with Direct and Indirect Human
Impacts, 12
Current Public Health Paradigm and Alternative World View, 34
Sources for Syndromic Surveillance, 2003 and 2006 Annual Meeting
Abstracts, 62
Potential Sources of Data for Syndromic Surveillance, 62
U.S. Select Agent List for Plants, 91
2-1
Top Infectious Disease Alerts from the HealthMap System, October 1,
2006–February 16, 2007, 128
3-1
3-2
Department of Defense (DoD) Acquisition Program for Diagnostic
Devices, 168
Criteria for Proof of Causation, 179
4-1
Current Public Health Paradigm and Alternative World View, 221
Figures
SA-1
SA-2
SA-3
The economic impact of selected infectious diseases, 13
Traditional public health reporting, 18
The power of the ProMED surveillance network, 19
xvii
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
xviii
TABLES, FIGURES, AND BOXES
SA-4
Source of initial reporting of potential events of public health concern
by WHO between January 1, 2001, and December 31, 2002, 21
SA-5 HealthMap alert volume by source, 23
SA-6 Telephone subscribers per 100 inhabitants, Africa 1995–2004, 24
SA-7 Star Trek medical tricorder, 30
1-1
1-2
1-3
1-4
1-5
1-6
1-7
1-8
1-9
1-10
2-1
2-2
Syndromic surveillance of U.S. marines for treated diarrheal syndromes during the lead-up to the Persian Gulf War, 1990–1991, 52
Conceptual steps in development and implementation of a syndromic
surveillance system in a community, 53
The donut-hole effect, 55
Estimated sensitivity for West Nile virus by different surveillance
methods, 57
E. coli O157:H7 spinach-associated outbreak, 2006, 58
Time associated with confirming spinach-related illness, 58
Locations of surveillance systems in abstracts for the 2006 International Society for Disease Surveillance (ISDS) meeting, 61
System requirements for public health surveillance, 63
Sensitivity of syndromic surveillance (probability of detection by day)
for influenza-like illness at a typical urban hospital emergency room
using four detection algorithms, 67
Electronic health monitoring components, 74
2-8
2-9
2-10
2-11
Epidemic intelligence framework, 117
Global Public Health Intelligence Network (GPHIN) flow of information, 119
Screenshot of the HealthMap system, 125
Framework for Internet-based surveillance, 126
HealthMap geographic coverage, October 1, 2006–
February 16, 2007, 130
Distribution of the earth’s population, 138
Being able to enter and access data from any available communications channels can optimize the use of existing infrastructure, 141
Health-care personnel collect data, 146
Alerta network, 147
Data flow from the field, 148
Outbreak of diarrhea as reported by the system, 150
3-1
3-2
3-3
3-4
3-5
Product development path for microbial diagnostics, 164
Infection and response time course, 166
Orthogonal diagnostic testing, 167
Acquisition program—evolutionary strategy, 168
Diagnostic system architecture, 172
2-3
2-4
2-5
2-6
2-7
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
xix
TABLES, FIGURES, AND BOXES
3-6
3-7
3-8
3-9
3-10
3-11
3-12
3-13
3-14
3-15
3-16
3-17
3-18
3-19
3-20
3-21
3-22
3-23
3-24
Comprehensive integrated diagnostic system, 176
A staged strategy for pathogen detection and discovery, 183
Schematic representation of MassTag PCR procedure, 183
Greene pathogen database, 186
The Bio-Maginot line, 195
Changing spectrum of biothreat risk, 196
Growth of GenBank, 1982–2005, 197
The combination of rapid knowledge and technological growth will
create the potential to make new pathogens, 198
The threat space is becoming increasingly complex, 198
Biosignature pattern recognition in human diseases, 199
Personalized medicine based on biosignatures, 200
Biosignatures versus biomarkers, 201
Upper respiratory disease incubation periods, 202
Program to create DocInBox diagnosis, 203
Health-care spending projections, 204
In 2005, 18 percent of GDP was spent on health care, 205
Comparison of U.S. spending on energy and health care,
1970–2004, 206
Average annual health-care expenditures by age, 2005, 206
Human species needs to square life’s curve, 207
Box
3-1
Example of Diagnostic Systems Validation Parameters, 173
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Summary and Assessment
GLOBAL INFECTIOUS DISEASE SURVEILLANCE AND DETECTION:
ASSESSING THE CHALLENGES—fINDING SOLUTIONS
Early detection is essential to the control of emerging, reemerging, and novel
infectious diseases, whether naturally occurring or intentionally introduced. Containing the spread of such diseases in a profoundly interconnected world requires
active vigilance for signs of an outbreak, rapid recognition of its presence, and
diagnosis of its microbial cause, in addition to strategies and resources for an
appropriate and efficient response. Although these actions are often viewed in
terms of human public health, they also challenge the plant and animal health
communities.
Surveillance, defined as “the continual scrutiny of all aspects of occurrence
and spread of a disease that are pertinent to effective control” (IOM, 2003; Last,
1995; WHO, 2000), involves the “systematic collection, analysis, interpretation,
and dissemination of health data” (WHO, 2000). Disease detection and diagnosis is the act of discovering a novel, emerging, or reemerging disease or disease
event and identifying its cause. Diagnosis is “the cornerstone of effective disease
control and prevention efforts, including surveillance” (IOM, 2003).
Disease surveillance and detection relies heavily on the astute individual: the
clinician, veterinarian, plant pathologist, farmer, livestock manager, or agricultural
extension agent who notices something unusual, atypical, or suspicious and brings
this discovery in a timely way to the attention of an appropriate representative of
human public health, veterinary medicine, or agriculture. Most developed countries have the ability to detect and diagnose human, animal, and plant diseases
The Forum’s role was limited to planning the workshop, and the workshop summary has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop.
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global infectious disease surveillance and detection
and have some type of active or passive surveillance for many well-characterized
agents. However, many developing countries—where most of the global population
resides—lack the resources or infrastructure to support such activities.
One way to close this gap in infectious disease surveillance and detection
may lie with the dispersion of technological advances such as regional syndromic surveillance, bioinformatics, and rapid diagnostic methods. Such tools
and approaches have already made important contributions to infectious disease
control and prevention efforts, albeit mainly in the developed world. Further
improvements are expected to result from ongoing progress in infectious disease
awareness and reporting, and from the continued development and deployment
of efficient, low-cost diagnostic platforms. A major challenge to global disease
surveillance and detection, and to this workshop, is not only the detection and
reporting of well-characterized “known” infectious diseases, but also the ability
to detect novel, emerging, or reemerging infectious diseases in relatively lowtech environments. There is a corresponding need to also develop redundant/
complimentary systems for infectious disease detection that go beyond the yield
of the more traditional surveillance systems and approaches.
The Institute of Medicine’s (IOM’s) Forum on Microbial Threats convened
a workshop addressing Global Infectious Disease Surveillance and Detection:
Assessing the Challenges—Finding Solutions on December 12 and 13, 2006, to
consider these and other scientific and policy issues relevant to the practice of
disease surveillance and detection. To adequately cover a broad range of topics
related to global infectious disease surveillance and detection, the Forum had
to be selective in prioritizing the challenges and exploring solutions to disease
detection and surveillance.
While the workshop did explore a variety of conventional and novel
approaches for disease surveillance and detection, the workshop organizers did
not attempt to critique standard domestic disease detection approaches nor did the
workshop make recommendations about what an “optimal” or “desirable” disease
surveillance and detection system would look like. Workshop participants examined current and emerging methods and strategies for the surveillance, detection,
and diagnosis of human, animal, and plant diseases in order to assess resource
needs and opportunities for improving and coordinating global infectious disease
surveillance, detection, and reporting.
Organization of Workshop Summary
This workshop summary was prepared for the Forum membership in the
name of the rapporteurs and includes a collection of individually authored papers
and commentary. Sections of the workshop summary not specifically attributed
The individually authored papers and commentaries of the speakers and participants at this workshop reflect their appreciation of disease detection and surveillance. As such, we have limited control
over how the experts defined disease surveillance and detection. For our purposes, surveillance is
defined on page 1.
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SUMMARY AND ASSESSMENT
to an individual reflect the views of the rapporteurs and not those of the Forum
on Microbial Threats, its sponsors, or the IOM. The contents of the unattributed
sections are based on the presentations and discussions at the workshop.
The workshop summary is organized into chapters as a topic-by-topic description of the presentations and discussions that took place at the workshop.
Its purpose is to present lessons from relevant experience, to delineate a range of
pivotal issues and their respective problems, and to offer potential responses as
described by workshop participants.
Although this workshop summary provides an account of the individual
presentations, it also reflects an important aspect of the Forum philosophy. The
workshop functions as a dialogue among representatives from different sectors
and presents their beliefs about which areas may merit further attention. The
reader should be aware, however, that the material presented here expresses
the views and opinions of the individuals participating in the workshop and not
the deliberations and conclusions of a formally constituted IOM study committee. These proceedings summarize only what participants stated in the workshop
and are not intended to be an exhaustive exploration of the subject matter or a
representation of consensus evaluation.
Surveillance Strategies
The practice of infectious disease surveillance is no longer restricted to
its original role in recognizing outbreaks of feared human diseases. Workshop
presentations reflected diverse goals, approaches, and methodologies for disease
surveillance in humans, animals, and plants. To place these presentations and
ensuing discussions in context, we begin by briefly describing the multiple purposes served by public health surveillance, as well as current disease surveillance
practices in animals and plants.
Surveillance Purposes and Practices
Public Health Surveillance
In the United States, public health surveillance for infectious disease is conducted through a variety of state and federal programs (GAO, 2004). Health-care
providers and others report cases of “notifiable” infectious disease (as defined by
local and state health codes) to health departments; health department officials
verify disease reports, monitor disease incidence, identify possible outbreaks, and
forward their findings to the Centers for Disease Control and Prevention (CDC).
CDC and other federal agencies, including the Food and Drug Administration
(FDA), the U.S. Department of Agriculture (USDA), and the Department of
Defense (DoD), independently gather and analyze information for disease surveillance. In addition, these agencies fund domestic and international networks of
disease surveillance laboratories that develop diagnostic tests and conduct disease
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diagnostic research. Although the CDC has provided guidelines for surveillance
systems funded by the federal government, evaluation is generally lacking. Furthermore, as noted by Forum member Edward McSweegan, little evidence has
been provided on the cost-effectiveness of massive federal public health surveillance investments (see also Eban, 2007).
Early Warning
Some surveillance systems are designed to provide early warning of a disease
threat by detecting the mere presence of potentially infectious microorganisms.
The federal BioWatch program, for example, uses a network of aerosol sampling
stations to monitor major U.S. population centers for a range of potential biological agents, such as anthrax, plague, and tularemia (the entire list of pathogens is
not publicly available) (Shea and Lister, 2003; OIG, 2005). The goal of this program is to detect biological agents within 36 hours of release, allowing federal,
state, and local officials to organize a timely response (OIG, 2005).
Surveillance also extends to symptoms indicative of infectious disease. Syndromic surveillance—the real time monitoring of nonspecific, prediagnostic
indicators for disease outbreaks—has been widely adopted by cities, states, and
the federal government as a means to provide early warning of infectious disease
outbreaks (Sosin, 2003; Stoto, 2005). Several syndromic surveillance systems are
currently operational. The Real Time Outbreak and Disease Surveillance System
(RODS) is used by several states to gather data on the symptoms of emergency
room patients (GAO, 2004). The RODS laboratory at the University of Pittsburgh
also created the National Retail Data Monitor (NRDM) to examine sales of overthe-counter health-care products. The Electronic Surveillance System for the
Early Notification of Community-Based Epidemics (ESSENCE), operated by
DoD, allows epidemiologists to track, in real-time, syndromes reported in daily
data feeds from regional hospitals and clinics in the National Capital area (GAO,
2004). The federal BioSense program—in which the United States has invested
an estimated $230 million since its 2004 inception—aggregates data relevant to
bioterrorism and other public health threats from numerous electronic sources
The
term “syndromic surveillance” applies to surveillance using health-related data that precede
diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health
response. Though historically syndromic surveillance has been used to target investigation of potential
cases, its utility for detecting outbreaks associated with bioterrorism is increasingly being explored
by public health officials (CDC, 2006a).
The National Retail Data Monitor (NRDM) is a public health surveillance tool that collects and
analyzes daily sales data for over-the-counter health-care products. NRDM collects sales data for
selected over-the-counter health-care products in near-real time from more than 15,000 retail stores
and makes them available to public health officials. NRDM is one of the first examples of a national
data utility for public health surveillance that collects, redistributes, and analyzes daily sales-volume
data of selected health-care products, thereby reducing the effort for both data providers and health
departments. For further information on the NRDM, see Wagner et al., 2004.
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SUMMARY AND ASSESSMENT
(GAO, 2004; Eban, 2007). Despite the considerable investments that have been
made in domestic syndromic surveillance systems, many workshop participants
noted, their promise remains largely unproven (Descenclos, 2006; Bravata et al.,
2004; Reingold, 2003; RAND Corporation, 2004; Stoto, 2005; Sosin, 2003).
Situational Awareness
Surveillance approaches are also used to monitor the progress and outcome
of an intervention to mitigate or stop the progression of a communicable disease,
as during the recent severe acute respiratory syndrome (SARS) pandemic (IOM,
2004; Heymann and Rodier, 2004) and in the campaigns to eradicate smallpox
(Henderson, 1999) and polio (WHO, 2006). The broad and multifaceted use
of surveillance to describe and inform response over the entire course of an
outbreak, known as “situational awareness,” was a central topic of workshop
discussion, as noted below.
Animals
The practice of surveillance is not limited to human diseases. Some surveillance systems protect economically and ecologically important animal or plant
species; others are designed to detect transmission of a zoonotic disease among
animal and human populations over space and time, and to predict future transmission patterns.
Within the complex network of federal agencies that govern animal health,
separate—and in some cases, parallel—surveillance programs are conducted by
USDA, Department of Homeland Security (DHS), DoD, Department of Health
and Human Services (HHS), the Department of the Interior (DoI), and Department of Commerce (NRC, 2005). As noted in the recent National Research Council report, Animal Health at the Crossroads, “whether due to historic structures
or functions of . . . related federal, state, and local governments, or because of
changes and challenges in funding and resources, there is an apparent disconnect
between [animal health] agencies that should function in partnership” (NRC,
2005). A further element of disintegration is introduced through the practice of
disease-specific surveillance at both federal and state levels.
Technological advances in disease detection that have benefited public health
surveillance—such as rapid, automated, sensitive, and portable sampling and
assay systems and DNA-based diagnostic tools—remain to be adapted to track
animal diseases (NRC, 2005). Such tools could have significantly reduced the
severe burden of recent outbreaks such as exotic Newcastle disease (END) among
chickens in the United States and foot-and-mouth disease (FMD) among cattle
in the United Kingdom; a recent analysis supports the use of polymerase chain
reaction (PCR) to screen bulk milk for the FMD virus (Thurmond and Perez,
2006). Other early warning technologies with potential application to animal
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disease surveillance include embedded monitoring chips to measure temperature
and other physiological states, gene-based pathogen assays, and biosensors.
Plants
Plant disease surveillance occurs at several levels: through growers, who
monitor crops for signs of disease; at the local and regional levels, by private
crop consultants and USDA cooperative extension agents who diagnose disease
and provide advice to growers on outbreak management; at the national level,
through programs such as the National Plant Diagnostic Network (NPDN; see
subsequent discussion) and BioWatch; and at the international level through collaborative research organizations such as the Consultative Group on International
Agriculture Research (CGIAR) (Fletcher, 2005; Stack et al., 2006).
In recent years, a broad range of molecular techniques, including PCR-based
and immunological assays and DNA arrays, have been adapted to detect and track
the spread of plant pathogens (Alvarez, 2004; Schaad et al., 2003). Although
routine diagnosis of many crop diseases can now be made within a day by realtime PCR, there is further need to develop same-day, onsite protocols for identifying plant pathogens, as well as standardized procedures to validate diagnostic
protocols (Schaad et al., 2003). In theory, earlier detection of plant pathogens
could be achieved through the capture of molecular signals from pathogens in
situ; however, this and related technologies are likely to be first applied to detect
animal and human pathogens (Cook, 2005; Schaad et al., 2003).
Public Health Surveillance: A Local Perspective
The traditional model of infectious disease surveillance remains essential
to public health practice, particularly at the local level. Speaker Marci Layton,
of the New York City Department of Health and Mental Hygiene (DOHMH),
emphasized the importance of reports—of both routine and unusual findings—by
health-care providers to local health departments. The interpretation and investigation of such reports by DOHMH officials supports the identification and control
of infectious disease in one of the world’s largest and most cosmopolitan cities
(see Chapter 1 overview). These efforts have been boosted in recent years by the
introduction of electronic reporting for laboratory results and web-based reporting by health-care providers. An alert system has also been established to inform
area health-care providers of public health emergencies.
Because of the high risk for disease importation into New York City, DOHMH
officials stay abreast of international infectious disease trends, ramping up surveillance and alerting health-care providers in response to threatened outbreaks.
The city has also invested federal funding to improve the ability of hospital
triage systems to identify and appropriately treat patients who show symptoms
associated with an emerging infectious disease. This is crucial, Layton observed,
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SUMMARY AND ASSESSMENT
because New York City “could be the next Toronto, with an unrecognized SARS
outbreak from overseas.”
Syndromic Surveillance
Layton noted that many infectious disease threats (e.g., influenza, SARS,
and viral encephalitis, as well as potential bioterrorism agents such as anthrax
and smallpox) manifest as syndromes with nonspecific symptoms (“influenzalike symptoms”). In the case of a rapidly spreading, emerging infectious disease,
laboratory diagnosis may be impossible. Under these circumstances, she said,
syndromic surveillance systems can alert public health authorities to an outbreak
before it is revealed in reports from health-care providers.
Keynote speaker Patrick Kelley, director of the Institute of Medicine’s Board
on Global Health, and presenter Michael Stoto, of the Georgetown University’s
School of Nursing and Health Studies, reviewed the theoretical underpinnings
and historical development of syndromic surveillance (see Kelley, Stoto in
Chapter 1). When people first develop symptoms, following an exposure or
first contact with a novel or rapidly emerging infectious disease, they may be
much more likely to attempt to treat themselves and stay home from work or
school rather than seeking care from a health-care provider to obtain a clinical
or laboratory diagnosis (Stoto, 2005). Syndromic surveillance systems monitor
existing descriptive data of these behaviors (e.g., school and work absenteeism,
sales of over-the-counter medications, illness-related 911 calls, emergency room
admissions for symptoms indicative of infectious disease) for patterns or clusters of behaviors suggestive of an illness outbreak. The concept of syndromic
surveillance is doubly attractive because in addition to its potential to increase
the speed and effectiveness of the public health response to natural or deliberate
disease outbreaks, it costs far less to implement than traditional, labor-intensive
approaches to disease surveillance (Stoto, 2005). However, the ability of syndromic surveillance to reduce disease-related morbidity and mortality remains to
be demonstrated, as does its cost-effectiveness (Bravata et al., 2004; Reingold,
2003; RAND Corporation, 2004; Stoto, 2005; Sosin, 2003). Although rigorous
evaluations of syndromic surveillance in general may be impossible, individual
systems can be assessed under a variety of circumstances (Reingold, 2003).
Moreover, because syndromic surveillance systems are warning devices, it will
be critical to determine their utility within the context of health systems that
respond to both “true” and “false” alarms (Pavlin, 2003; RAND Corporation,
2004).
Global Syndromic Surveillance
In parts of the world where clinicians are in short supply, syndromic surveillance offers a promising model for disease detection, Kelley observed (see
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global infectious disease surveillance and detection
Chapter 1). Infectious disease is a major cause of morbidity and mortality in
low-resource populations, and such environments frequently provide amplifying
conditions for emerging pathogens. Recognition of this threat has spurred the
World Health Organization (WHO) to revise the International Health Regulations
(IHRs)—the legal framework for international cooperation on infectious disease
surveillance. Once limited to a trio of internationally notifiable diseases (plague,
cholera, and yellow fever), as of June 15, 2007, the revised IHRs became the
“world’s first legally binding agreement in the fight against public health emergencies of international concern” (WHO, 2007). Reporting of new and reemerging diseases with epidemic or pandemic potential, as well as diseases associated
with acute chemical or radionuclear events, will be mandatory regardless of their
origin or source (WHO, 2007).
“The mandate for general global public health surveillance is moving beyond
named diseases to encompass a global responsibility to detect and report in a
timely manner internationally important disease events, whether they are individual cases or clusters, whether they are well-defined diseases or ill-defined
diseases,” Kelley explained. Syndrome detection is central to this new paradigm,
and should be viewed as one of a collection of approaches to global surveillance
for infectious diseases, he said. However, he also noted considerable challenges
in moving syndromic surveillance from theory to practice.
Syndromic Surveillance by Design
Kelley emphasized that a key step in developing effective syndromic surveillance systems—and one that has frequently been overlooked—is the precise
definition of system capabilities. While considerable effort has been applied to
the development of syndromic definitions (e.g., for flu-like illnesses that may
indicate bioterrorism), far less attention has been paid to identifying robust
detectors of those conditions, he said. Moreover, rather than formulate clear and
specific questions and design systems to answer them, he observed that developers of syndromic surveillance systems have too often created systems based on
opportunistic datasets.
In addition to appropriate data to answer essential questions, a system for
public health surveillance requires powerful analytical tools, as well as technically proficient analysts to use them and accurately interpret the findings, Kelley
said. He added that these considerations are equally applicable to domestic
surveillance programs that, due to their complexity, might be fruitfully developed through academic partnerships with individual communities. Kelley also
advocated strengthening the epidemiological capacity at the local level in order
to inform the interpretation of syndromic findings in light of “local epidemi-
ological peculiarities,” as well as to ensure a rapid response to syndromic
alerts.
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SUMMARY AND ASSESSMENT
From Syndromic Surveillance to “Situational Awareness”
Syndromic surveillance systems are handicapped by their very nature. Not
only must they obtain relevant and accurate data quickly and from a variety of
sources, but they must also be tuned to recognize unusual trends against a highly
variable background; otherwise, syndromic surveillance systems may either miss
an important event or generate unacceptable levels of false positives (see contributions by Kelley, Stoto in Chapter 1). Indeed, Stoto explained, according to
the syndromic detection algorithm, it is impossible to increase the sensitivity,
specificity, or timeliness of syndromic detection without reducing the other two
attributes. This point is illustrated by a recent model of outbreak detection for
inhalational anthrax by Buckeridge and colleagues (2006), who concluded that
“when syndromic surveillance was sufficiently sensitive to detect a substantial
proportion of outbreaks before clinical case finding, it generated frequent false
alarms” (Buckeridge et al., 2006).
Stoto explored several additional examples of this dilemma, all of which
support his contention that traditional, statistics-based syndromic surveillance
systems are unsuited to the detection of rare, small-scale events such as a localized biological attack or the initial cases of a newly imported or emerging disease.
He suggested, rather, that syndromic surveillance was most likely to be valuable
in detecting potentially large-scale, natural disease outbreaks (e.g., seasonal and
pandemic influenza, foodborne disease) for which the useful “detection window”
is relatively broad.
Case-Finding by Syndrome
Instead of bypassing health-care providers, Stoto said that syndromic surveillance technology could be used to “arm astute physicians and health departments with modern approaches to finding small numbers of cases” and allow
health professionals to identify them before they are formally diagnosed. Such
“case-finding” surveillance systems currently in operation include the Syndromic
Reporting Information System (SYRIS) (ARES, 2007; Mandl et al., 2004; CDC,
2006b), Rapid Syndrome Validation Project (RSVP) (Zelicoff et al., 2001), and
Lightweight Epidemiological Advanced Detection Emergency Response System (LEADERS) (Green and Kaufman, 2002). Because case-finding syndromic
surveillance requires early reporting of symptoms, it can only succeed in “an
atmosphere that doesn’t penalize people for getting it wrong,” Stoto said (and,
as other participants noted, for getting it right, that is, for being the bearer of bad
news). Under enabling conditions, he said, case-finding syndromic surveillance
could build the kind of strong relationships between public health and health-care
providers that are critical to effective outbreak response.
“Like any alarm system, [syndromic surveillance is] only as good as what
happens when the bell rings,” Stoto concluded. “It must be followed with active
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global infectious disease surveillance and detection
surveillance and epidemiological investigation, and with policy decisions regarding intervention.” Speaker Joseph Lombardo, of the Johns Hopkins University
Applied Physics Laboratory, further advised that syndromic surveillance systems
be designed to meet the specific needs of epidemiologists and public health analysts. “The tools need to be built to support those individuals, and I believe public
health informatics has a tremendous role in doing that,” he said.
Situational Awareness
Several workshop participants described the use of syndromic surveillance
data beyond the mere detection of behavioral “signals” of an outbreak. Kelley
noted that syndromic data could support efforts to characterize infectious diseases, help target outbreak response, and inform risk communication. Lombardo
distinguished between syndromic surveillance, which he defined as an automated
detection and alarm system, and “situational awareness,” a term long used by
DoD that encompasses disease classification, tracking, response, and outcome
monitoring, in addition to detection. Viewed through the lens of situational
awareness, syndromic surveillance provides a rapid means to obtain descriptive
data throughout the course of an infectious disease outbreak. Epidemiologists
and others who monitor surveillance findings represent “the most important component of an advanced disease surveillance system,” Lombardo insisted. “They
cannot be replaced by statistics.”
Real-Time and Batched Reporting
In addition to collecting strategic data, well-designed public health surveillance systems incorporate appropriate mechanisms to process information and
deliver it to users. The computational performance of these tasks may occur
in “real time” or it may be “batched,” according to Lombardo, who explained
the implications of these descriptions for infectious disease surveillance (see
Chapter 1).
Real-time computing methods (presently used in video games and automotive safety systems) permit an immediate response to surveillance data, Lombardo
said. Batching may occur at any of several junctures along the path from data
collection to reporting, he explained; the term “batched reporting” may therefore
reflect the simultaneous collection of multiple data points, or the contemporaneous processing of data collected at different times, or the reporting, at regular
intervals, of the outcome of sequentially processed data. Batched health data may
be reported to users as soon as it is processed, at regular intervals, or accessed
on demand.
Breaking the electronic surveillance process into a series of steps, Lombardo
compared the potential and consequences for real-time and batched reporting.
Only certain syndromic surveillance data are available in real time, he noted.
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SUMMARY AND ASSESSMENT
11
For example, while cash registers transmit medication purchases immediately,
schools report absenteeism on a daily basis. Moreover, he observed, “the benefits
of real-time data collection are only realized if the other components of a surveillance system are real-time as well.”
Data may be continuously communicated for processing via a virtual private
network (used in some hospitals), or it may be sent by file transfer protocol as
batched files in intervals of seconds to hours. At the data processing step, the
distinction between real time and batched may not be meaningful if computation
is complex and therefore time consuming, Lombardo observed. For example, a
spatial analysis of disease phenomena across a series of ZIP codes could take a
long time to process; however, surveillance systems can allow analysts selectively to invoke certain processes in real time in order to monitor a potentially
urgent situation.
Surveillance reports can be delivered in real time, in the form of automatic
alerts, but Lombardo described considerable problems with this feature. As previously noted, many reports that are based on syndromic data represent false
positives and will therefore require an epidemiologist’s attention and expertise to
discern a true signal among considerable background noise. This can take time.
Unless surveillance reports are subject to continuous analysis, it makes no
sense to invest resources in providing them on a real-time basis, Lombardo concluded. “Getting information several times an hour should be more than adequate
for public health needs,” he said. To provide for public health emergencies, he
envisioned two modes of operation for advanced disease surveillance systems:
batched reporting for routine analysis, and real-time reporting, which would be
based on case definition and used for more focused surveillance during a crisis.
Animal Disease Surveillance
Two important factors contribute to the proliferation of zoonotic diseases:
the explosive growth of human and domestic animal populations, and the increasingly close physical proximity within which humans and domestic and wild
animals live (Karesh and Cook, 2005; NRC, 2005). Infectious diseases primarily
affecting animals can have both direct and indirect impacts on humans (Table
SA-1), including significant economic consequences (Figure SA-1). Therefore it
is widely acknowledged that the timely identification of future emerging microbial threats (on the order of SARS, West Nile virus, or H5N1 avian influenza)
will require an integrated international approach to disease surveillance. Progress
toward this goal has been hampered by a variety of economic and political factors, most notably the threat of trade embargoes against countries that voluntarily
report livestock or wildlife disease outbreaks.
Although they share comparable objectives, the U.S. animal health community lags far behind its public health counterpart in terms of surveillance
infrastructure and technology (NRC, 2005). These deficits were raised in several
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global infectious disease surveillance and detection
TABLE SA-1 Animal Diseases Associated with Direct and Indirect Human
Impacts
Infectious Disease
Affects
Wildlife
Brucellosis
Canine Parvovirus
Chagas
Distemper
Foot-and-mouth disease
Leishmania
Leptospirosis
Rabies
Scabies
Toxoplasmosis
X
X
X
X
X
X
X
X
X
X
Affects
Domestic
Animals
Affects
Humans
Directly
Affects
Humans
Indirectly
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SOURCE: WCS (2007).
workshop discussions, and particularly in comments from veterinary pathologist Tracey McNamara of the Wildlife Conservation Society (WCS). In 1999,
McNamara linked the presence of dead birds on the grounds of two New York
City zoos with the first human cases of West Nile encephalitis in the United
States. Thereafter, she led the effort to create a national surveillance network for
the disease involving more than 35 zoos (Watanabe, 2002). A far more comprehensive and integrated strategy is needed for the surveillance of zoonoses, McNamara said. She noted that there is no provision for veterinarians who routinely
diagnose infectious disease in zoo animals and wildlife to report unusual findings
or send samples to public health authorities for testing, as physicians are required
to do. “Zoos are the most overlooked long-term epidemiological monitoring stations in the United States and in the world today,” she concluded.
As part of their overall mission, WCS conducts routine surveillance for a
wide variety of infectious diseases in animals around the world, including the
20,000 residents of zoological parks in the New York City area. In his presentation, William Karesh, director of the Society’s Field Veterinary Program,
described ongoing programs to monitor two important zoonoses: Ebola virus and
avian influenza (see Karesh in Chapter 1).
Ebola Virus Surveillance in Central Africa
In a reversal of standard public health thinking, WCS views humans as a
worrisome source of diseases that infect great apes. To protect endangered gorillas in central Africa from the Ebola virus, WCS has supported human disease
surveillance among the underserved populations that live in close contact with
the gorillas by training local people in simple data collection, syndromic surveil-
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1997
1999
SA-1 Broadside
2001
2002
2003
2004
BSE, U.S.
$3.5B
Avian flu, Asia
U.S., Canada
$10B
BSE, Canada
$1.5B
BSE,
Japan Avian flu, EU
$500M
$1.5B
2000
Nipah,,Malaysia
$350-400M
Swine flu,
Netherlands
$2.3B
1998
Foot and Mouth
Taiwan, $5-8B
Lyme disease
U.S., $2.5B
BSE, UK
$10-13B
Foot and Mouth
UK
$30B
SARS
China, Hong Kong,
Singapore, Canada,…
$50B+
FIGURE SA-1 The economic impact of selected infectious diseases.
SOURCE: Karesh (2006). Reprinted with permission from Bio-era. Copyright 2007.
Estimated cost
$50B
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global infectious disease surveillance and detection
lance, and basic laboratory diagnosis. These efforts, which helped to identify the
link between human outbreaks of Ebola virus and the consumption of gorilla and
chimpanzee meat (Leroy et al., 2004), now enable community members to avoid
infection with the virus by providing early warning of outbreaks in animals. Current surveillance is also directed toward evaluating the effectiveness of human
Ebola vaccine candidates in wildlife.
In addition to their efforts on behalf of gorillas, WCS has sought to teach
people in central Africa how to avoid getting Ebola through basic hygiene measures such as hand washing and cooking meat thoroughly. These lessons have
afforded opportunities to improve overall food safety in communities, Karesh
observed.
Global Surveillance for Avian Influenza
Over the course of several years, WCS has worked with individual governments to conduct surveillance for avian influenza in wild birds. This typically
involves basic epidemiology and viral sample collection and characterization
(by CDC); in some instances, birds are tracked with radio transmitters. In Mongolia, such a program has provided a candidate virus for development of a
human influenza vaccine, Karesh said. More recently, these individual efforts
have been combined into the Global Avian Influenza Network for Surveillance
(GAINS). The program seeks to expand international surveillance for influenza
in wild birds and promote the dissemination of surveillance information to governments, international organizations, the private sector, and the public. With
support from USDA, the U.S. Agency for International Development (USAID),
and the Food and Agriculture Organization of the United Nations (FAO), GAINS
trains individuals and organizations to collect samples for analysis by a network
of diagnostic labs, the results of which are disseminated through a common,
open-access database. Participants in the program, which currently reaches 24
countries, include hunters, birdwatchers, and other members of the public, as
well as animal health professionals. Karesh acknowledged that GAINS raises
privacy concerns in the United States. (“Who wants to say they have a sick bird
on their property?”), but he also observed, “the rest of the world doesn’t seem to
have that problem.”
Indeed, as Karesh notes in Chapter 1, the early success of GAINS has led
to an expansion of the program to address a broader range of infectious diseases
and species. The Wildlife Global Animal Information Network for Surveillance
(Wildlife GAINS) aims to establish “a comprehensive worldwide wildlife health
surveillance system to enhance preparedness for and awareness of emerging
infectious diseases,” he reports.
See
http://www.gains.org.
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SUMMARY AND ASSESSMENT
15
Plant Disease Surveillance and Detection
While plant health programs address many of the same challenges (e.g.,
globalization, biosecurity) and use similar tools and approaches as their animal
and public health counterparts, the near impossibility of preventing the global
spread of plant pathogens orients surveillance and detection toward preparedness
for disease. Agricultural production in the United States is especially vulnerable
because it encompasses vast areas, observed speaker Jacqueline Fletcher of the
University of Oklahoma (see Fletcher and Stack in Chapter 1).
Considerable time often elapses between the introduction of an agricultural
pathogen and its detection; therefore, federal programs such as the aforementioned NPDN focus on the early detection of plant diseases to minimize economic
losses. Because it would be too expensive to eradicate the more than 50,000 plant
diseases currently in the United States, the typical strategy is to minimize the
economic impact of each disease, Fletcher explained. However, given sufficient
warning prior to the introduction of a new plant disease threat, researchers can
reduce the impact of disease by identifying chemical control measures or by
breeding resistant crop varieties.
National Plant Diagnostic Network
Early detection, aimed at reducing the economic impact of plant diseases, is
the central mission of NPDN, according to speaker James Stack of Kansas State
University (see Stack and Fletcher in Chapter 1). Created in 2002 by the U.S.
Secretary of Agriculture, NPDN links plant disease and pest diagnostic facilities
at land grant universities in order to provide rapid detection and accurate diagnosis of important plant pathogens and pests (Stack et al., 2006). These efforts
received further federal support in 2004, under a Homeland Security Presidential
Directive (HSPD-9), which “establishes a national policy to defend the agriculture and food system against terrorist attacks, major disasters, and other emergencies.” HSPD-9 mandates the development of a national agricultural biosecurity
initiative that would expand capacity for disease detection and diagnosis (White
House, 2004).
According to Stack, NPDN is currently pursuing a range of passive and
active disease surveillance strategies. These include sentinel surveillance for specific pathogens (e.g., soybean rust, introduced to the United States by hurricanes
in 2004); random surveys for plant disease conducted by specialists throughout
the country; strategic and bidirectional surveillance, which attempt to locate the
source of disease outbreaks; syndromic surveillance (also for soybean rust); and
biosensors (for toxin-producing pathogens in stored grains and seeds). While
mandatory reporting of high-consequence pathogens and pests has been instituted
in some circumstances, Stack noted that the considerable disincentives to do so
probably lead to high rates of noncompliance.
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global infectious disease surveillance and detection
NPDN has also undertaken several projects intended to maximize the productivity of shrinking numbers of plant scientists trained in diagnosing disease,
Stack said. These include the creation of a curriculum to teach agricultural
workers to recognize signs of important plant diseases, and the development of
diagnostic databases and a “telemedicine” system that links state agricultural labs
to diagnostic experts.
National Center for Plant Biosecurity
Fletcher discussed a proposal for a comprehensive National Center for Plant
Biosecurity that has been endorsed by a broad coalition of scientific societies with
a common interest in crop protection. It is envisioned that the center, modeled on
CDC, would coordinate plant disease information at the national level and collect and disseminate knowledge on plant-disease management and agricultural
biosecurity. The center’s mission would be fundamentally different from that of
USDA, which is driven by the needs of agribusiness and focused on near-term
profitability, Stack explained. “We need another group that can step back from
that and look at our plant-based systems from a strategic standpoint,” he said.
Although the threat of agricultural bioterrorism provided the impetus for
proposing the center’s creation, Fletcher said, its benefits would be substantial in
the absence of such crises. This is particularly true because former USDA functions, such as the Animal and Plant Health Inspection Service (APHIS) and the
Plum Island Animal Disease Center, were subsumed by DHS, Stack observed.
That move has diminished attention to the specific missions of these agencies,
which represent “a first pair of eyes for what is coming into the country,” he said.
“If they don’t know what they are looking for, then that’s wasted time.”
Surveillance Networks
In traditional public health surveillance (based on reports from medical
practitioners, as described in the previous section), information travels up or
down the public health hierarchy, from the local to the international level and
vice versa. According to Forum member Stephen Morse, this seemingly orderly
scenario tends to produce surveillance that is patchy and erratic due to differing
priorities at various levels of the public health system, and information that is
too often focused on “diseases of the moment.” By contrast, electronic network
surveillance systems have the potential to recognize any outbreak, including that
of an emerging or otherwise unexpected disease, on a global scale.
The presentations and discussions summarized below demonstrate the power
of electronic networks to collect and integrate information on infectious disease
from a variety of sources and the ability of networks to disseminate such intelligence widely and rapidly to the user community. Participants also noted several
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SUMMARY AND ASSESSMENT
limitations of disease surveillance networks and—much as they had done for
syndromic surveillance systems—urged the creation of network surveillance
technologies that address specific public health needs and strengthen connections
between “astute clinicians” and public health practitioners.
ProMED-Mail
The first disease surveillance network, ProMED-mail (PMM), began in 1994
as a project of the Federation of American Scientists’ Program for Monitoring
Emerging Diseases (ProMED) (Madoff and Woodall, 2005). Morse, a founding
member of both ProMED and PMM, recounted that the network was initially
intended to enhance communication between working group members; however,
the listserv’s potential as an outbreak reporting system was quickly recognized
and expanded (see Morse in Chapter 2). Now sponsored by the International
Society for Infectious Diseases, PMM is a free, nonprofit, noncommercial, moderated e-mail list that serves in excess of 37,000 subscribers in more than 150
countries, as well as anyone with access to the website.
As illustrated in Figure SA-2, traditional public health reporting follows a
linear “bottom-up” process, beginning with an ill person presenting to a local
doctor, where they may receive medical tests. If the doctor or laboratorian finds
evidence of a “reportable” disease, or merely something unusual, he or she
reports the discovery to local health officials. If the apparent threat is severe, local
health officials report it to the national ministry or department of health, which
forwards the report to international health organizations (“world bodies”) if the
case is of global concern.
Figure SA-3 depicts the nonhierarchical ProMED network, which fosters the
exchange of information on reported diseases among a variety of sources.
In addition to volunteer “rapporteurs,” who provide information on possible
infectious disease outbreaks specific to their geographic area, PMM receives
information from subscribers (who may report firsthand or from other sources)
and from staff-conducted searches of the Internet, media, and various official and
unofficial websites (Madoff, 2004). Moderators assess these reports for plausibility (via established rumor verification protocols and private query to experts), edit
them as necessary, and often add comments or context before posting. Furthermore, because PMM aggregates reports from various locations, it can reveal the
geographical extent of an outbreak. Morse noted that this system has resulted in
several emerging disease reporting “firsts,” including outbreaks of Ebola virus in
Zaire (1995), West Nile virus in the United States (1999), SARS in China (2002),
and H5N1 avian influenza in Indonesia (2003).
See
http://www.promedmail.org.
Copyright © National Academy of Sciences. All rights reserved.
Public
Public
Copyright © National Academy of Sciences. All rights reserved.
Public
Practitioners
Local officials
FIGURE SA-2 Traditional public health reporting.
SOURCE: Figure courtesy of Dr. Larry Madoff.
Labs
Practitioners
Practitioners
Local officials
Ministry of Health
Type Title Here
SA-2 Broadside
Labs
Public
Practitioners
Public
Practitioners
Public
Practitioners
Local officials
Ministry of Health
Type Title Here
Local officials
World bodies: UN, WHO, FAO, OIE
Type Title Here
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SUMMARY AND ASSESSMENT
Ministries of Health
WHO
Media
Health-care workers
Laboratories
Lay public
Local health officials
FIGURE SA-3 The power of the ProMED surveillance network.
SOURCE: Figure courtesy of Dr. Larry Madoff.
Global Outbreak Alert and Response Network
SA-3
To connect the growing number of surveillance networks that followed
PMM in terms of capacity for infectious disease diagnosis and response, WHO
established the Global Outbreak Alert and Response Network (GOARN) in
2000. Conceived as a “network of networks,” GOARN pools human and technical resources from more than 100 institutions around the world (WHO, 2005)
in order to rapidly identify, confirm, and respond to outbreaks of international
importance. In 2002, after receiving worrisome reports from the Global Public
Health Intelligence Network (GPHIN; see below) and the U.S. Global Emerging
Infection Surveillance and Response System (GEIS), GOARN initiated the global
response to an outbreak of a disease that would be named SARS (IOM, 2004;
Heymann and Rodier, 2004).
The Global Public Health Intelligence Network (GPHIN)
Harnessing the power of automated Internet searching for disease surveillance, GPHIN scans thousands of websites in eight languages—including those
identified by two “news aggregators,” who monitor thousands of news sources in
dozens of languages—for early signs of infectious disease outbreaks in humans,
animals, and plants, as well as for chemical incidents and disease threats associated with natural disasters (Mykhalovskiy and Weir, 2006). Abla Mawudeku,
manager of GPHIN within the Public Health Agency of Canada, described the
network’s creation by that agency in partnership with WHO in 1998, its operation
and ongoing development, and its possible future as part of a planned open-access
See
http://www.who.int/csr/outbreaknetwork/en/.
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global infectious disease surveillance and detection
surveillance program under the auspices of a yet-to-be-named nongovernmental
organization (see Mawudeku et al. in Chapter 2).
After a scoring system sorts some 2,000 articles retrieved by GPHIN daily,
a team of multilingual, multidisciplinary, and multicultural analysts review those
articles deemed most relevant, Mawudeku explained. Several analysts work in
staggered shifts to provide round-the-clock coverage. Upon receiving a report of
concern, they follow a decision tree, based on IHR criteria (which may lead analysts to corroborate reports with other surveillance networks, such as ProMEDmail), to determine whether to post an alert. GPHIN does not systematically
validate the information it posts, but relies on WHO to verify outbreak alerts
through its country contacts (Mykhalovskiy and Weir, 2006). Figure SA-4 shows
the source of initial reporting of events of potential public health concern by
WHO in 2001–2002.
Subscribers to GPHIN receive alerts by e-mail or when they log on to the
system’s website. In addition to WHO and Canadian governmental agencies
(e.g., food inspection, defense, police), GPHIN’s audience includes ministries
of health and departments of agriculture from several nations, as well as FAO,
the World Organization for Animal Health (OIE), and the North Atlantic Treaty
Organization (NATO). Depending on the services provided, GPHIN subscriptions
(which in part reflect the expense of subscribing to news aggregators) cost 30,000
to 200,000 Canadian dollars per year, according to Mawudeku (Public Health
Agency of Canada, 2007).
To continue to improve its service, GPHIN has begun to evaluate its own effectiveness. Criteria are based on the number of users; the timeliness, sensitivity, and specificity of alerts; the stability of the system in terms of limited downtime; and the flexibility
of the system in terms of accommodating new technologies and in modifying search
criteria to gather information on a situation of interest, Mawudeku said. The cost of
operating and upgrading the system is a continual challenge, she observed, as well as
a barrier to use by low-resource countries and agencies. However, recent events may
portend a change in this situation. Having received the Technology, Entertainment and
Design (TED) prize in 2006, epidemiologist Larry Brilliant (who played a key role in
WHO’s campaign to eliminate smallpox, and who currently serves as Google’s chief
of philanthropy) is currently marshalling an effort by the influential TED community
to expand and enhance the GPHIN model (Zetter, 2006; Google, 2006; Hempel, 2006).
With GPHIN as a starting point, Brilliant hopes to create a freely available, internationally independent system for the early detection of infectious disease outbreaks.
Due to potential conflicts of interest with the Canadian government, GPHIN’s
staff cannot participate in the negotiations to make this service independent,
Mawudeku explained. “I can’t tell you what will happen to the GPHIN system,
whether we will continue to be within the [Public Health Agency of Canada] or
not,” she said, adding that Google’s attention to GPHIN had at least prompted
Office
International des Epizooties.
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SUMMARY AND ASSESSMENT
Organization
Verified
Not verified
GPHIN
MOH
News Media
NGO
Other Org.
Personal Com.
UN Org.
WHO
WHO Country Off.
WHO Regional Off.
0
50
100
150
Number of events
200
FIGURE SA-4 Source of initial reporting of potential events of public health concern by
WHO between January 1, 2001, and December 31, 2002. Legend: Global Public Health
Intelligence Network (GPHIN); Ministry of Health (MOH); Nongovernmental Organization (NGO); United Nations (UN); World Health Organization (WHO).
SOURCE: Mawudeku et al. (2002).
SA-4
recognition that the network would benefit from greater financial support than the
Canadian government currently provides. It would also satisfy the concerns of
Forum member Gerald Keusch, who observed that government-operated sources
of surveillance information raise “serious issues of credibility.”
HealthMap
HealthMap,
a freely available, web-based surveillance network operating since September 2006, provides a global view of infectious disease outbreaks as reported by the WHO, PMM, Google News,10 and Eurosurveillance.11
John Brownstein, of the Children’s Hospital Informatics Program, Harvard–
See
http://www.HealthMap.org.
http://www.who.int/csr/don/en/.
10 See http://news.google.com/news?hl=en&ned=us&ie=UTF-8&scoring=d&q=intitle:outbreak +
-satire+-%22press+release%22+-%22Communiqués+de+presse%22.
11 Eurosurveillance, a free and open-access multiformat journal, publishes peer-reviewed information
on communicable diseases from a European perspective. In March 2007, Eurosurveillance became
the independent scientific in-house journal of the European Centre for Disease Control and Prevention
(ECDC) in Stockholm, Sweden. For more information, see http://www.eurosurveillance.org.
See
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global infectious disease surveillance and detection
Massachusetts Institute of Technology (MIT) Division of Health Sciences and
Technology, and the Harvard Medical School Center for Medical Bioinformatics,
described the design of the system and efforts to evaluate its data sources (see
Brownstein et al. in Chapter 2).
There is an abundance of open-source electronic surveillance networks for
infectious disease, Brownstein said, but none provide a truly global perspective
due to gaps in geographic or population coverage and expertise. HealthMap
attempts to bridge these gaps by aggregating and integrating information from
several surveillance networks to produce a graphic, continually updated model
of global disease outbreaks over space and time. Alerts are displayed on a
global map that can be viewed at a wide range of resolutions and they are
linked to source sites that provide news of the outbreak and information on
the disease.
Recognizing the tradeoffs between alert sensitivity and specificity,
HealthMap’s creators are conducting an ongoing evaluation of their data sources
with respect to these criteria (see Brownstein et al. in Chapter 2). Brownstein
reported that, based on their first two months’ of data, PMM provided slightly
greater timeliness and better coverage of rare infections as compared with Google
News. On the other hand, he noted, news feeds provide a larger volume of data,
making them more useful for describing the temporal and spatial distribution of
large-scale seasonal infections (Figure SA-5). Brownstein believes “there is a real
value in integrating these data sources . . . to get a much better picture of a global
state of infectious diseases.”
HealthMap’s creators plan to expand their data sources to include CDC,
the private sector, laboratories, the military, and blog searches. They also plan
to incorporate information on animal infections and biotic and abiotic factors
that influence disease emergence and transmission, Brownstein said. In addition
to addressing reporting biases in current datasets, he noted that these additional
sources should support the assessment of population risk, disease severity, and
pathogen transmission within the HealthMap model. Data verification remains a
challenge, he added; with only two employees, HealthMap must rely on data that
have been validated by others—such as ProMED-mail reports.
Several participants recognized potential synergies between HealthMap
and GPHIN, with each network offering important elements (HealthMap’s
openness; GPHIN’s reach and verification capacity) of a long desired and
sought-after “system of systems” approach to infectious disease surveillance.
GPHIN’s current status within Health Canada and its reliance on commercial
news aggregation services would likely prohibit the network from supplying
data to HealthMap, Mawudeku explained; however, such collaboration could
be possible if GPHIN evolves into an open, nongovernmental network as envisioned by Brilliant.
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Report volume
SUMMARY AND ASSESSMENT
FIGURE SA-5 HealthMap alert volume by source. Google News: 899 (14.2 per day; 95
percent CI 11.8-17.2); ProMED: 257 (4.2 per day; 95 percent CI 3.5–4.7); World Health
Organization: 15.
SOURCE: Brownstein (2006).
The Voxiva Model for Resource-Constrained Environments
As several workshop participants observed, a global infectious disease surveillance system capable of early detectionSA-5
and response must identify outbreaks
where they most often arise: in the world’s most impoverished communities.
Many developing countries, however, lack adequate disease surveillance systems
capable of finding, diagnosing, and responding to diseases of global concern.
These countries must also detect and control outbreaks of common diseases,
such as measles, within their own borders. This is the void Voxiva12 attempts to
fill, according to speaker Pamela Johnson, the company’s cofounder (see Johnson
and Blazes in Chapter 2). Although projects have been launched to enable disease
reporting in low-resource settings via the Internet, personal digital assistants
(PDAs), and satellite dishes, she noted that none of these technologies directly
reached the inhabitants of remote communities at risk for infectious disease
outbreaks. By contrast, she reported that cellular phones have begun to connect
even the most isolated villages as their usage rate grows far faster than that of the
12 Founded in 2001, Voxiva aims to find practical ways of using information technology for health
and development in low-resource environments by creating innovative software that allows health
professionals to enter and access data using the Internet, a cell phone, and other devices. This new
capability makes early identification, treatment, and response possible for public health concerns.
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global infectious disease surveillance and detection
Internet. Figure SA-6 illustrates the rapid growth of cell phone usage in Africa
between 1994 and 2004.
Like other electronic surveillance networks, Voxiva is ultimately web-based,
Johnson said. The network receives input from a variety of sources, including cellular and fixed-line telephones, personal computers, PDAs, and paperbased communications to “optimize the use of existing infrastructure to create
multiple-channel, redundant systems” for data collection, she explained. Information is captured in a database that can then be shared with those who contribute
reports, along with tools for data analysis and visualization. Gaining access to
surveillance information and tools—in addition to acknowledgment for their
participation—gives inhabitants of outbreak communities a powerful incentive
for reporting, Johnson said.
Voxiva conducts both syndromic and traditional surveillance for human
disease in a variety of settings in Asia, Africa, South America, and the United
States, as well as systems to monitor animal health and adverse events. In Peru,
Voxiva created a system to replace the paper-based monitoring of illness among
members of its navy, a project described by David Blazes of the U.S. Naval
Medical Research Center in Lima (see Johnson and Blazes in Chapter 2). When
naval personnel or their family members present with disease symptoms at remote
clinics in the Amazon jungle, for example, nurses or physicians enter data via
cellular or toll-free public phones, or if necessary, relay it via radio to another site
with telephone access. The data are captured, displayed in real time on a private
web-based platform, and used to generate messages and alerts that feed back to
FIGURE SA-6 Telephone subscribers per 100 inhabitants, Africa 1995–2004.
SOURCE: Reproduced with the kind permission of the International Telecommunication
Union (2006).
SA-6 © National Academy of Sciences. All rights reserved.
Copyright
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SUMMARY AND ASSESSMENT
25
the reporting clinics. “The Peruvian Navy had no idea how many cases of any
disease were occurring over a period of time,” Blazes observed. “Just setting
baseline trends was very important.”
Like GPHIN, Blazes said that Voxiva has begun to evaluate its surveillance
systems, based on criteria such as simplicity, flexibility, stability, and sustainability, as defined by CDC (CDC, 2001). But Voxiva’s involvement in public health
extends well beyond surveillance, he noted: Their systems are linked to diagnosis
and response teams that can provide guidance or assistance in the event of an outbreak. In addition, Voxiva provides basic training in epidemiology and outbreak
management to its clients, using freely available, web-based curricula.13 All these
functions contribute to Voxiva’s overarching purpose, as defined by Johnson, to
use informatics to build and support networks of astute clinicians.
Considerations for Surveillance Networks
In response to these presentations, workshop participants raised a series of
general issues regarding the structure, function, and future of public health surveillance networks. Although the open-access PMM and HealthMap networks
are well established and poised to expand, some Forum members noted that
none of these networks features the sort of open editing made popular by the
free online encyclopedia Wikipedia.14 Brownstein said that HealthMap may add
a user editing function, but input would be limited to a group of experts. Keusch
pointed out that a similar “portal” model has been used to collect other types of
information; for example, to construct the Encyclopedia of Earth, a free, searchable collection of articles on earth science and ecology written by a diverse team
of experts who collaborate and review each other’s work.15 By contrast, Forum
member Gary Roselle expressed concern that HealthMap’s “beautiful maps of
data” derive from potentially erroneous newspapers and websites, and worse,
could be influenced to manipulate markets. In subsequent remarks, speaker Will
Hueston (see next section and Chapter 4) asserted that the maps would “set back
international development because it supports the idea that a country either has
the disease or doesn’t have the disease and the country either is at zero risk or
is at risk.” Furthermore, he predicted that the vast economic consequences (e.g.,
trade embargoes; decreased tourism and investment) of such labels would inhibit
disease reporting.
Regarding limitations in network access, one Forum member wondered how
public response to the SARS pandemic might have changed had GPHIN been
13 To
date Voxiva has trained more than 1,300 epidemiologists on the basics of outbreak management. Their objectives and curricula are in Spanish and English and are freely available on the
Web. For more information about the training provided by Voxiva, see http://www.nmrcd.med.navy.
mil/outbreak/.
14 See http://www.wikipedia.org.
15 See http://www.digitaluniverse.net/portal/earth/.
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global infectious disease surveillance and detection
freely accessible. Mawudeku speculated that the release of unverified information might have created unnecessary panic, and she advised that such information be accompanied by qualifying commentary if it were provided in an open
version of GPHIN. Another barrier to network openness exists at the level of
data acquisition. Countries do not share surveillance data without government
approval, participants observed, and the IHRs do not presently impose sufficient
consequences to overcome economic barriers to reporting disease. This necessarily limits information available to surveillance networks, except perhaps Voxiva,
whose clients own their data and use the network’s information as they see fit. On
the other hand, Johnson pointed out, clients sufficiently interested in collecting
such data tend to have the greatest capacity to respond to an apparent outbreak.
Looking to the future, Forum member George Korch asked how surveillance
data accumulated by networks might be analyzed further to tease out underlying
factors and relationships, such as previously unknown societal or environmental
influences on disease transmission. To the extent that they occur at all, such analyses are currently conducted on an ad hoc basis; however, both Brownstein and
Mawudeku said their networks are discussing possibilities for deeper and more
detailed surveillance studies, which are likely to proceed as collaborations with
academia and research institutions. Brownstein also predicted that basic research
in Internet-based surveillance would benefit from the recent “explosion of work”
on syndromic surveillance systems; for example, by using previously developed
methods to characterize datasets and reveal their hidden biases.
Finally, participants observed that surveillance networks, like other advanced
technologies that have been integrated into the practice of public health, tend to
be driven by innovation rather than designed to solve important problems. They
urged greater involvement by the public health community in creating tools in
response to pressing public health challenges, and noted that the development of
a common lexicon by technologists and public health practitioners is crucial to
advancing their collaboration.
Detection and Diagnostics
Current microbial detection and identification methods include microbiological culture, nucleic acid-based techniques such as gene amplification via
PCR, and immunological (antibody-based) assays (Peruski and Peruski, 2003;
Fredricks and Relman, 1999; Tang et al., 1997). Each of these platforms offers
complementary advantages and disadvantages for infectious disease diagnosis:
• Microbiological culture, with staining and microscopy, is the most
widely used method for identifying pathogens, particularly in developing countries. Despite being slow and limited in sensitivity for some clinically relevant
microbes, culture often provides the best means to assess complex microbial
phenotypes, such as drug resistance.
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• PCR is a sensitive, specific, and rapid approach for identifying microbes,
including those that are nonviable or inactivated (Peruski and Peruski, 2003;
Gilbert, 2002). Hundreds of different microbe-specific nucleic acid amplification tests have been described, but only a few such tests are routinely used in a
clinical setting to detect pathogens that include N. gonorrheae, C. trachomatis,
herpes simplex virus, and HIV (Fredricks and Relman, 1999; Tang et al., 1997).
PCR methods may also be used to detect drug resistance in pathogens (Fluit et
al., 2001), but the diversity of genotypes and mechanisms associated with this
phenotype, and the difficulty of predicting expression from simple gene detection, have hampered the universal adoption of this approach. Real-time quantitative PCR, which permits sample processing in minutes, powers environmental
detection systems for infectious diseases and biological warfare agents, as well
as innovative point-of-care diagnostic tests (Ivnitski et al., 2003; Peruski and
Peruski, 2003; Raja et al., 2005).
• Immunoassays are usually less sensitive and specific than culture and
PCR (Peruski and Peruski, 2003). Solid-phase, “hand-held” immunoassays for
specific pathogens are rapid, rugged, and easy to use. However, their application
is generally limited to screening or confirming diagnoses.
Newer diagnostic platforms, still largely in development, include nucleic acid
microarrays (“labs on chips” containing hundreds to thousands of oligonucleotide
probes for signature sequences) and mass spectrometry techniques for sequence
analysis (Briese et al., 2005; Palacios et al., 2006; Palacios et al., 2007; Anthony
et al., 2001). These technologies permit detection of a wide range of known
disease-causing organisms (not limited to microbes) and can often distinguish
new pathogen species, strains, and genotypes. Additional innovations include
methods for the simultaneous identification of complex mixtures of organisms
(Ecker et al., 2005; Hofstadler et al., 2005). Potential applications of such multiplexed detection technologies include the characterization of polymicrobial
infections common in epidemics of respiratory disease, and the creation of “universal biosensors” to permit the simultaneous identification of a broad range of
infectious agents in an environmental or clinical sample.
The Diagnostic Landscape
Workshop presentations on infectious disease detection and diagnostics followed a metaphorical road as they surveyed the immediate landscape of capacity, needs, and challenges; anticipated developments around the next turn; and
imagined a far horizon of disease diagnosis prior to the appearance of symptoms.
In the course of this journey, participants examined a variety of approaches to
infectious disease detection and diagnosis and raised significant considerations
for continued development of this field.
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Developing Countries
While threats posed by emerging diseases, pandemic influenza, and bioterrorism underscored workshop discussion, Mark Perkins of the Foundation for
Innovative New Diagnostics (FIND) reminded participants of the severe burden presently imposed on the developing world by infectious diseases such as
tuberculosis (TB) and malaria (see Perkins and Small in Chapter 3). Culture and
microscopy are often the only diagnostic technologies available in developing
countries, typically through a small number of facilities that cannot begin to meet
national needs. This not only hinders treatment for infectious disease in developing countries, he noted, but surveillance as well. Perkins reported that half of
the 22 countries with the highest burden of disease from TB have three or fewer
laboratories that can perform drug-susceptibility testing, a key component of TB
treatment and control; similar barriers also deter the detection and treatment of
trypanosomaisis and malaria.
Developing countries’ needs for rapid, accurate, inexpensive, and robust
diagnostics could be met by recent advances in genomics, proteomics, and materials science, but for the lack of a profitable market for such developments,
Perkins observed. FIND therefore guides the development and adoption of novel
diagnostic products for diseases of the developing world in much the same way as
public–private partnerships have been established to produce drugs and vaccines
for low-resource settings (Perkins and Small, 2006). With FIND’s support, companies that produce low-cost diagnostics for use in developing countries realize
sufficient cost savings (in manufacturing, approval procedures, and marketing)
to sustain profits. “So far it has been a very successful model,” Perkins reported.
“We have about 18 different technologies in the pipeline.”
Diagnostics for TB figure prominently among the Foundation’s current projects. Perkins described a liquid culture system for TB that reduces detection time
by several weeks; a phage replication assay and an automated detection system,
both capable of detecting rifampicin-resistant TB in sputum (signaling a patient
that will fail standard therapy); and an easy-to-use PCR diagnostic system that
can be performed in clinics without laboratory support. He cautioned that many
substandard rapid tests for TB (as well as other diseases, including malaria) have
already appeared on the market. “Small companies, the kinds of companies that are
making these tests, are not going to invest in going back to the genome and figuring
out what the right targets are,” he observed. Nevertheless, Perkins concluded, “Our
belief at FIND is that if you make the right technology, people will use it.”
On the Battlefield
Much like public health workers in developing countries, soldiers at risk
of contracting infectious diseases, either from the natural environment or from
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bioweapons, need diagnostics that are rugged, rapid, and easy to use. According
to speaker Mark Wolcott of the Diagnostic Systems Division at the U.S. Army
Medical Research Institute of Infectious Diseases (USAMRIID), diagnostic
assays must satisfy additional criteria for use in battle. Accuracy is paramount,
and tests must recognize a broad range of potential pathogens, he explained.
“Negatives are problems,” he said, “and false negatives [which may result from a
bioengineered pathogen] are of greater concern than false positives.” The military
currently relies on a combination of PCR tests, immunoassays, and traditional
microbiology to diagnose infectious diseases in the field, while pursuing a strategy to develop comprehensive diagnostic tools.
Animal Diseases
Recognizing the advantages of DNA-based diagnostic tools, Alex Ardans and
colleagues have developed PCR-based assays to screen for pathogens associated
with exotic Newcastle disease (END) in poultry and foot-and-mouth disease
(FMD) in cattle (Crossley et al., 2005; Heller, 2006; Thurmond and Perez, 2006).
Ardans, who directs the California Animal Health and Food Safety Laboratory
System, also described how the discovery of TB among cattle in several of the
state’s large dairies led to the development of a highly efficient testing program.
Although the state laboratory system spearheads surveillance for several
important animal diseases (including zoonoses such as avian influenza, bovine
spongiform encephalopathy, and West Nile encephalitis), Ardans suggested that
its most crucial role is in recognizing unusual disease events. He noted, for
example, that while END was “no stranger” to rural California, a recent outbreak
in an urban setting—among fighting cocks, whose handlers worked in and spread
the disease to commercial operations—took the state by surprise. The laboratory
responded by optimizing an existing real-time PCR assay for END that was used
to perform more than 85,000 tests (Crossley et al., 2005). “These emergency
efforts are a real opportunity to develop some new knowledge,” Ardans said.
“They are unique in what they will give us, and it’s a rare opportunity to improve
the diagnostics. [How else] would you get a chance to validate an assay using
85,000 samples?”
Such situations, Ardans observed, also highlight the importance of meeting
diagnostic needs with appropriate technologies. In pursuing the source of E. coli
O157:H7 in a recent outbreak in spinach, laboratory researchers discovered that
the use of a gauze swab to sample irrigation waters for contaminants performed
better than newer concentration technologies. (As previously noted, surveillance
for infectious plant diseases depends largely on available methods of disease
detection and diagnosis; see also Chapter 1.)
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global infectious disease surveillance and detection
The Road Ahead: Diagnostics in Development
Inspired in part by the image of the original Star Trek’s character “Bones” ®
diagnosing a patient with a wave of his medical tricorder (Figure SA-7), Wolcott
and fellow DoD researchers are attempting to construct an “integrated diagnostic
system” for field use that can detect viruses, bacteria, toxins, “and anything else
that could possibly be thrown at us in the biological detection arena,” he said.
The current prototype relies on automated real-time PCR, but DoD researchers
are testing a wide range of diagnostic technologies (e.g., microarrays, handheld
immunoassays, electrochemiluminescence) and targets (e.g., microbial toxins, as
well as nucleic acids), according to Wolcott. “We have to have multiple platforms
to give us the assurance that what we are reporting up the chain of command is
actually there,” he said. The ultimate goal is to combine multiple platforms into a
single, universal system for field diagnosis. While the time constraints and primitive conditions of battle present significant barriers to the use of microarrays,
Wolcott speculated that chip technology eventually would be adapted to provide
point-of-care diagnosis for soldiers in action.
FIGURE SA-7 Star Trek medical tricorder.16
SOURCE: Printed with permission from CBS Paramount.
16 The
medical tricorder was a palm-sized, handheld, device used by doctors in the Star Trek universe of the 23rd and 24th centuries to help diagnose diseases and collect bodily information about a
patient. The device scanned a living patient, interpreted and displayed the data obtained from the scan
to the user, and recorded the data to isolinear chips (Wikipedia contributors, 2007).
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Following a similar technological progression from PCR to microarrays, the
Pandora’s Box Project, based at Columbia University’s Greene Infectious Disease Laboratory, employs a staged strategy for molecular pathogen surveillance
and discovery (see Lipkin and Briese in Chapter 3) (Palacios et al., 2007). As
described by speaker and Greene Laboratory director W. Ian Lipkin, the first stage
consists of MassTag PCR, a technique that attaches reporter “tags” of distinct
masses to the amplified sequences, permitting the simultaneous, highly sensitive detection of more than 20 different pathogens. This platform, which is both
inexpensive (at approximately $10 per 20-plex assay) and rapid, has been used
to distinguish among various viral hemorrhagic fevers, Lipkin said; it is currently
being adapted for the diagnosis of gastroenteritis. MassTag PCR has also enabled
the recent discovery of a virus responsible for a significant proportion of flu-like
respiratory disease (Lamson et al., 2006).
A second stage of diagnosis becomes necessary when the first stage fails,
or when a larger number of sequences must be screened, Lipkin continued. For
this purpose, the researchers first designed a pair of extensive microarrays, called
GreeneChips, for viruses and other respiratory pathogens, and then a panmicrobial array that incorporates more than 29,000 60-mer probes from filamentous
fungi and yeasts, and parasites, as well as from viruses and bacteria that infect
vertebrates (Palacios et al., 2007). Together, these arrays comprise a system for
assaying nucleic acids extracted from clinical samples (e.g., nasopharyngeal
aspirates, blood, urine) or cell culture. If the less expensive ($100 per assay)
respiratory or viral arrays fail to detect a pathogen, he explained, “then we go to
progressively more comprehensive chips that top out at approximately $350.”
“These are surveillance tools,” Lipkin said of both MassTag PCR and
GreeneChips. “All they do is give you a plus/minus, presence-or-absence, sort of
an answer, if they give you an answer at all. You ultimately have to come back
to surveillance assays [such as] quantitation, with real-time PCR, [and] you have
to do serology.” More importantly, he observed, because diagnosis requires the
integration of various test results with other information, such as epidemiological data, the GreeneChip “is never really going to replace a seasoned, thoughtful
clinician.”
Lipkin also noted that, despite the obvious advantages of multiplexed detection (and in anticipation of less expensive versions of microarrays), the widespread adoption of microarrays for disease detection would require a revision
in regulatory standards based on the more sensitive single-agent model. “The
gold standard, invariably, is single-agent [detection] with an identical match
between template and probe as opposed to multiplex systems, which tolerate
sequence divergence,” he explained. The need to obtain intellectual property
licenses for each of potentially thousands of sequences restricts the development
of array-based diagnostics, Lipkin added. However, both regulatory and intellectual property barriers could be minimized by constructing multiplex assays of
20 or so carefully chosen sequences, according to Forum member Patrick Fitch,
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of Battelle Memorial Institute. “Defining the problem space goes a long way to
getting optimization of the assay you want,” he concluded.
GreeneChips are tools for discovery, as well as for diagnosis. Because as
many as 100 different regions of a genome may be represented on the chip, assays
reveal enough sequence information to enable the rapid sequencing of novel
pathogens, several of which have been characterized. Analyses of GreenChip data
have led to the identification of a novel target for antiviral drugs, which Lipkin
described as an “on/off switch in the human immune system.” He predicted that
broad, unbiased pathogen-detection methods will continue to provoke unanticipated discoveries and enable researchers to explore the apparent link between
infectious and chronic diseases.
The Far Horizon: Presymptomatic Diagnosis
Imagining a future in which bioterrorism agents are continually reengineered
to evade standard detection and diagnostic methods, as well as therapeutics,
speaker and Forum member Stephen Johnston proposed a model of diagnosis
for exposure to a pathogen prior to the appearance of symptoms (see Johnston
in Chapter 3). In this situation, he argued, specific defenses against threat agents
(e.g., vaccines) will be useless. Instead, he envisions the creation of platforms
for defense against the full range of potential bioweapons, such as the means to
recognize and respond to the earliest possible signs of infectious disease in individual patients. Host-based, presymptomatic diagnosis could be accomplished by
monitoring a person’s blood serum chemistry for changes suggestive of compromised health status, Johnston explained; he is currently involved in developing
a device to perform such analyses. He noted that the noninvasive sampling of
breath and saliva is attractive in theory, but that neither of these sources offered
the diversity or concentration of metabolic components found in blood.
Monitoring the biological signatures of infectious disease will require making thousands to millions of simultaneous measurements and comparing them
to well-established baselines, Johnston said. Ideally, this would occur through
a continuous process. Therefore the monitoring device would need to be easily accessible (e.g., in the home), robust, inexpensive, and capable of quickly
measuring thousands of variables—specifications that also apply to point-of-care
devices for low-resource settings. Because the symptoms of respiratory viruses
appear in as little as one day, Johnston hypothesized that presymptomatic detection would need to register changes in the nanomolar-to-picomolar range and
would require clear baselines and the integration of multiple measurements to
avoid an unacceptable level of false positives. In response, Forum member David
Relman of Stanford University referred to an article by Kohane and colleagues
(2006), who describe substantive risks inherent in the practice of personalized,
genomic medicine, among them the imprudence of using “testing panels comprising a sizeable fraction of the genome for clinical care or screening” (Kohane et
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al., 2006). Johnston acknowledged that scant evidence—most of it derived from
early postinfection transcription patterns—suggests such measurements could
actually anticipate the development of respiratory symptoms. He attributed this
dearth of supporting data to the lack of funding for research in this area and to
the yet-unsolved problem of what, exactly, to measure, and how. Johnston and
coworkers are currently attempting to develop synthetic antibody techniques for
monitoring infection-related changes in protein levels.
In addition to offering the best chance of treatment for known, emerging,
or bioengineered pathogens, detecting infectious disease at the earliest possible
moment would permit diagnosis-based triage and increase the effectiveness of
quarantine or other social distancing measures, Johnston predicted. He anticipated that presymptomatic diagnosis will have an even greater impact on everyday medical care. “We have a healthcare system that can’t be sustained in terms
of physical economy,” he said, adding that care for ill patients accounts for nearly
90 percent of health-care spending. “Why does it cost so much? Because we are
diagnosing sick people, taking care of sick people; we even develop our drugs
for sick people.” Therefore, he insisted, our society has no choice but to move
from postsymptomatic to presymptomatic diagnosis.
Considerations for Detection and Diagnosis
Given the considerable interdependence of surveillance, detection, and diagnostic activities as they relate to infectious disease, it is not surprising that key
challenges identified by workshop participants in their discussions of surveillance
strategies would resurface as they explored current and future prospects for disease detection and diagnosis. Once again, participants stressed the importance of
selecting and acquiring clinically relevant samples or specimens, the establishment of said relevance against a background of natural variation, and the need
for standards to guide system design and evaluation.
Workshop participants also considered the status of infectious disease
diagnostics, which they characterized as a largely unsupported area within the
crowded field of medical diagnostics. Fitch observed that pharmaceutical companies tend to develop relatively low-margin diagnostic tests only when they can
be linked to highly profitable therapeutics (e.g., for cardiac disease and cancer).
Nevertheless, participants urged that the vast experience of commercial producers
of medical diagnostics be brought to bear on public efforts to develop applications for infectious diseases. For example, Relman suggested that industry could
participate in efforts to identify and evaluate common principles and platforms
for sample processing, signal generation and detection, and data analysis. However, he added, these considerations are contingent on a more fundamental set
of yet-to-be-determined specifications for any surveillance or detection program:
the exact set of questions to be answered and the appropriate setting in which to
ask them.
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The Challenge of Coordination
Workshop participants, having considered a broad range of tools and strategies for infectious disease surveillance, detection, and diagnosis, turned to the
difficult issue of effectively combining them. Hueston, director of the University
of Minnesota’s Center for Animal Health and Food Safety, launched this discussion with his presentation on the coordination of disease surveillance, detection,
diagnostics, and reporting. This topic is a frequent focus of Hueston’s work,
which emphasizes risk communication and the facilitation of public–private
partnerships (see Chapter 4).
Shifting the Public Health Paradigm
Certain powerful concepts and conditions that influence the practice of public health inhibit the coordination of infectious disease surveillance, detection,
and diagnosis, according to Hueston. Table SA-2 summarizes these elements of
the current public health paradigm, as defined by Hueston, and pairs them with
his proposed alternatives.
Hueston identified several factors driving the current paradigm that specifically undermine public health coordination. Chief among them is high health
TABLE SA-2 Current Public Health Paradigm and Alternative World View
Current Paradigm
Alternative World View
Health focus is individual; benefits
accrue primarily to the developed world
Health focus is global society; benefits accrue to all
Health is absence of disease
Health is well-being (in mind, body, spirit)
Infectious disease is all about the agent
Infectious disease emerges at the convergence of agent,
host, environment
Zero risk is achievable
Zero risk is unachievable; risk management is the goal
Success is eradication/cure
Success is homeostasis with microbes that are
ubiquitous, constantly evolving, and adapting
Public health function is to react
Public health function is health promotion
Reaction requires agent detection
Risk management can be successful whether or not
microbe is identified
Urgency dictates priority
Surveillance informs policy and guides action on basis
of importance
Answers lie solely in technology
Answers involve people, politics, partners
SOURCE: Hueston (2006).
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status in the United States, which reinforces the tendency of public health to
focus on the urgent (i.e., the disease or agent du jour) rather than the important
(i.e., emergency preparedness); this situation is exacerbated by a budget process
that takes money from “important” programs to fund “urgent” ones. Parochialism
influences our sense of urgency, he observed, causing us “to focus on those things
about which we are most interested in the United States as opposed to looking at
the true [global] public health priorities.” Hueston added that assigning blame for
public health threats—and especially the tendency to “shoot the messengers” who
identify them—suppresses essential collaboration in surveillance. For example,
before the United States adopted a policy of “zero tolerance” for food contamination, companies monitored for more pathogens and kept records of their findings,
a practice that supported scientific evaluation of the impact of new intervention
strategies. Now, he said, “if they monitor and get positive reports, they are culpable and have self-incriminated, so they stopped monitoring.”
Coordinating the spectrum of public health activities associated with disease
surveillance and detection is an inherently political task, and therefore strongly
influenced by societal and organizational culture, Hueston asserted. “To be effective in politics over the long term and to build coordination and collaboration
requires people skills,” he observed, and yet increasingly in educational fields
relevant to public health, considerations of interpersonal and executive skills are
largely ignored under the misguided assumption that science and technology can
replace them. Rather, as Korch noted in the ensuing discussion, in a risk management model of public health, understanding and responding to specific social
contexts is crucial to effective risk reduction and communication.
There is no “magic bullet to change paradigms,” Hueston stated, stressing
that steady progress can be made through small successes. This progress, albeit
slow, needs to be properly recognized and celebrated. Because the most effective engine for change is educating the next generation of leaders early in their
careers, he urged educators to encourage greater global and transdisciplinary
awareness in future public health professionals.
Optimal Surveillance for Risk Management
Clearing the way for true coordination and collaboration would enable optimal surveillance, as Hueston defined it: an integrated and dynamic system with
ongoing data collection and real-time analysis to inform risk management, and
thereby drive policy and action, with a feedback process to facilitate continuous
evolution and adaptation. Information would be drawn from a broad range of
disciplines relevant to physical and mental health, as well as domestic and wild
animal health and plant health, through the complementary processes of agent
surveillance and host and environmental monitoring.
In the discussion that followed his presentation, Hueston noted the potential
economic benefits of surveillance systems for both developing and industrial-
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ized countries, but also warned that too much openness could undermine such
systems. “If our goal is to promote public health, and surveillance precipitates
action to control the disease, do we always have to make the information public?”
he wondered aloud. Forum member Johnston responded emphatically that such
secrecy “has only gotten us in trouble, that it is elitist and that it is only going
to come back and bite us in the long run. If we want to foster a further schism
between the public and the scientific community, the best thing we can do for that
is to withhold information.” Hueston responded that he agreed with Johnston’s
position in principle, but insisted that under some circumstances, the unintended
consequences of publicizing information outweighs the potential benefits, such
as sharing of animal disease surveillance data in wildlife that precipitates unwarranted trade restrictions on commercially produced products. He concluded that
the release of surveillance information should be evaluated on a case-by-case
basis. Forum member Margaret Hamburg noted that timing is crucial to such
communication and observed that public health officials “get into trouble if we
provide information before we fully understand it and before we understand how
we are going to respond.”
Because the definition of risk is individual and fueled by emotion, public
health professionals must address the perception of risk, Hueston explained. Trust
is not built merely by sharing data, but by helping people understand information
by providing it in context, he said. But, he continued, this is only the first stage.
The public must then be actively engaged to discuss their perception of risk and
identify priorities for action.
Needs and Opportunities
This section recounts needs and opportunities for both research and policy
derived from workshop discussions on infectious disease surveillance, detection,
and diagnosis. Participants, including members of a concluding discussion panel
(see Chapter 4 overview), identified a series of issues critical to the development and implementation of effective methods and strategies for the detection
of infectious disease and described key challenges in responding to increasingly
early disease alerts.
Critical Issues in Infectious Disease Surveillance and Detection
The following areas were the subject of extended discussion with reference
to both surveillance and detection.
System Design and Development
Hueston captured a recurring theme in this workshop’s discussion when
he quoted management guru Stephen Covey’s advice to “begin with the end in
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mind” (Covey, 1989). As previously noted, many decried the evolution of surveillance and detection systems based on available technologies and databases,
rather than in response to well-defined public health needs. Participants suggested
the following actions to improve the design and development of surveillance and
detection systems:
• Develop a common design lexicon to improve communication and collaboration between public health practitioners and information technologists.
• Devise methods to analyze surveillance data through time in order to
understand factors and mechanisms that underlie apparent trends.
• Create syndromic surveillance systems that can adapt to signals as they
are received so that an increase in symptom prevalence prompts intensified
testing.
• Broaden the purview of surveillance to encompass social circumstances
that affect public health.
• Incorporate mechanisms to filter surveillance data to reduce false-positive
(and panic-inducing) alarms.
• Recognize and incorporate promising surveillance concepts from noninfectious disease applications.
• Support basic research in disease surveillance, especially among plant and
animal populations.
• Develop incentives to promote the development of infectious disease
diagnostics and to integrate academic and commercial efforts toward this goal.
• Consider models of infectious disease beyond the replication of viruses
or bacteria within organ systems. These would include toxin-producing microbes
(e.g., Clostridium botulinum) and pathogens that affect the immune system or
immune responses (including delayed or chronic effects, such as those associated
with hepatitis C and human immunodeficiency virus [HIV]).
• Do not overlook longstanding and effective elements of disease detection:
pathology, microbiology, and of course, the astute clinician.
System Evaluation
Workshop participants encouraged critical analysis, comparison, and evaluation of the performance of existing surveillance and detection systems, and in
particular, of the U.S. BioSense (syndromic surveillance) and BioWatch (specific
threat detection) programs. Their suggestions include the following:
• Identify the essential components of a global infectious disease surveillance system in order to prioritize funding.
• Support operational research to evaluate and optimize informatic systems for processing epidemiological data, particularly when used in syndromic
surveillance.
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global infectious disease surveillance and detection
• Develop methods to analyze and compare cost-effectiveness of surveillance and detection systems.
• Design mechanisms for continuous feedback and improvement into surveillance and detection systems.
• Reconsider the role of syndromic surveillance in disease control, given
the lack of evidence for its effectiveness in early detection of biological attacks
and its promise for tracking large-scale, natural disease outbreaks such as H5N1
avian influenza.
Integration of Information
Workshop participants also stressed the importance of integrating information on infectious diseases from diverse sources and methods to obtain a
comprehensive view of disease risk and severity. In particular, they encouraged
the development of mechanisms to connect local sources of surveillance data
(including information on animal infections, insect vector distributions, climate,
and vegetation) with global surveillance networks.
Information Transparency, Control, and Access
As noted in the previous section, workshop participants expressed divergent
opinions concerning the risks and benefits associated with the public disclosure of
surveillance findings. Most participants acknowledged a need to balance transparency—a foundation of both public and international trust—against the potential
consequences associated with public misinterpretation and overreaction. Several
participants urged consideration of political and economic factors, as well as
timing (i.e., releasing surveillance information by public health authorities only
after it is fully understood and a response is planned or underway), in making
such decisions.
Reporting
Recognizing that the reporting of unusual findings by health practitioners
(and subsequently by governments) is essential to infectious disease surveillance
and detection, workshop participants considered a range of incentives to promote
the affirmative reporting of human, animal, and plant health status at all levels,
including the following:
• Develop and broadly implement standards for infectious disease reporting
and sample submission to public health laboratories.
• Pay clinicians, especially those in developing countries, to report findings
to national public health authorities.
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• Ensure the confidentiality of health practitioners who report infectious
disease, while recognizing their contribution to public health. In the case of agricultural diseases, provide financial support for farmers who report disease and
guard intellectual property rights of seed companies who assist in identifying
vulnerable germplasm.
Participants also suggested a variety of mechanisms and tools to improve the
collection and use of reported information, as follows:
• Fund the procurement, storage, submission, and diagnostic testing of clinical and animal specimens from a broad spectrum of private and public sources.
• Encourage data collection to support the characterization of natural variation and define baseline health status; reward the reporting of negative data.
WHO’s Health Metrics Network, a global partnership to build capacity and
expertise to provide better health information to decision makers at all levels,
represents a potential source of baseline data.17
• Support the development of global surveillance and laboratory capacity
as mandated by recent revisions to the IHRs. Some suggested that this could
be accomplished through increased funding to WHO; others argued that WHO
must first be reformed and strengthened; others questioned whether a new intergovernmental entity would need to be invented to achieve the goals set by the
IHRs.
• Support parallel efforts by OIE, NATO, USDA, and the European Union
to develop global surveillance capacity for animal and plant diseases.
From Alarm to Action
In the spirit of beginning with the end in mind, workshop participants also
considered the fate of information derived from infectious disease surveillance
and detection systems. Several participants observed that U.S. government investment in the detection of biological threats far outstrips its ability to respond to
such crises. Some decried the shortsightedness of creating global surveillance
networks for infectious disease without also providing for disease control and
containment, as well as for public preparedness and risk communication. As
Kelley acknowledged, far more than science will be required to help affected
communities accept the uncertainty that characterizes the course of an infectious
disease emergency and the ensuing public health response.
17 See
http://www.who.int/healthmetrics/about/whatishmn/en/print.html.
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1
Surveillance Strategies
OVERVIEW
This chapter includes workshop presentations that illustrate a variety of goals,
approaches, and methodologies for disease surveillance in humans, animals, and
plants. As noted in the chapter’s first paper by keynote speaker Patrick Kelley,
director of the Institute of Medicine’s Board on Global Health, current concepts
of public health surveillance, inspired by approaches to military intelligence data
gathering, originated in the 1950s. Today, traditional surveillance practices of
disease reporting (by physicians, veterinarians, infection control practitioners,
laboratorians, and medical examiners), followed by epidemiological and laboratory investigation, constitute the mainstay of local infectious disease surveillance
where such expensive methods are feasible (mainly in developed countries).
However, a range of nontraditional strategies including syndromic surveillance
(the topic of Kelley’s paper, and another in this chapter by Michael Stoto) and
electronic surveillance (the subject of Chapter 2), may prove well suited to settings where clinicians, laboratories, and hospitals are in short supply.
Local Surveillance: New York City
Although New York City’s size, diversity, and significance to international
transportation create considerable opportunities for infectious outbreaks, local
approaches to surveillance resemble those of many communities around the
world, according to presenter Marci Layton of the New York City Department
of Health and Mental Hygiene (DOHMH). New York health codes mandate
disease reporting for more than 70 infectious diseases, ranging from common
45
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global infectious disease surveillance and detection
pathogens such as Salmonella to the potentially disastrous, such as smallpox
and anthrax. The health department receives reports by traditional phone, mail,
and fax and—following a significant recent investment—by electronic and webbased methods as well. Participation in an electronic clinical laboratory reporting
system, a secure network that allows DOHMH to receive laboratory-confirmed
diagnoses in a timely manner, is mandated for all laboratories that diagnose New
York City residents. This system enables DOHMH to spot citywide and neighborhood disease trends in routinely reported data that an individual physician would
not be able to recognize, Layton said.
Upon receiving a report, DOHMH initiates an investigation to examine risk
factors for infection in order to determine disease transmission routes, and, if
appropriate, to arrange prophylaxis. “The most important thing we try to do is to
make sure that every health care provider knows who and how to call to make a
report,” Layton said.
In the event of an apparent or actual public health emergency, New York
City’s health alert system quickly disseminates information to providers on the
nature of the emergency and instructions on preparing and delivering diagnostic
specimens. Because New York City is at high risk for receiving imported disease,
DOHMH stays attuned to global infectious disease issues via surveillance networks such as ProMED-mail (see Morse in Chapter 2) and responds to reports
of significant disease activity abroad by ramping up surveillance and alerting
health-care providers in New York City to look for signs of an outbreak. After an
outbreak of West Nile virus in 1999, and in light of increasing concern regarding the potential use of zoonotic diseases as bioterrorism agents, animal diseases
were made reportable in New York City in 2000.
DOHMH has invested considerable hospital-preparedness funding to improve
the ability of triage systems to recognize patients with significant risk factors for
infectious disease, particularly patients with fever and respiratory illness who
have traveled recently. This is crucial because, in Layton’s words, “New York
City could be the next Toronto, with an unrecognized imported outbreak of severe
acute respiratory syndrome (SARS)—or of bioterrorism, E. coli, or most worrisome of all, avian influenza.”
The realization that many unreported, hospitalized cases of viral encephalitis (a reportable disease) manifested during the West Nile virus outbreak caused
DOHMH to adopt procedures to monitor similar nonspecific clinical syndromes.
In 1998, the city began syndromic surveillance based on ambulance dispatch
data; the system was expanded to monitor the entire emergency department
in the wake of the 2001 World Trade Center attack, then further to monitor
pharmacy sales, employee health, school absenteeism, and primary care visits.
One of the most challenging aspects of responding to a syndromic signal is
getting specimens to a lab for diagnostic testing, Layton observed, particularly
specimens from the acutely ill patients typically seen in emergency departments.
Rapid diagnostic testing is performed for a variety of pathogens at a single New
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SURVEILLANCE STRATEGIES
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York City hospital, but only limited information is obtained from this proof-ofconcept project.
To better balance time spent investigating syndromic surveillance signals
versus outbreaks detected through traditional means, DOHMH is developing
a protocol to reduce time wasted on false positives while ensuring the prompt
investigation of real outbreaks. Syndromic surveillance systems have proven to
be most useful for monitoring citywide seasonal outbreaks of infectious diseases
(e.g., norovirus, influenza, respiratory syncytial virus [RSV]), Layton said, and
less useful for detecting localized outbreaks.
“In my view, syndromic surveillance will never replace traditional surveillance, which is where most surveillance resources should continue to be
invested,” she concluded. “The real public health challenge lies in creating the
necessary infrastructure to analyze surveillance data, set priorities, and conduct
investigations. I am concerned that increased investment in syndromic surveillance may occur at the expense of state and local public health infrastructure.
More generally, if current funding patterns continue, whereby national programs
addressing emerging infections and bioterrorism receive more and public health
at the state and local levels receive less, our ability to make use of surveillance
information will suffer.”
Toward Earlier Warning
Through the use of prediagnostic data, syndromic surveillance aims to provide timelier identification of disease outbreaks than can be attained through
traditional surveillance methods, Kelley writes. After reviewing the theoretical
underpinnings and historical development of syndromic surveillance, he discusses its potential applications in developing countries and its promise as a
vehicle for achieving global disease surveillance as mandated in recent revisions
of the International Health Regulations (IHRs). Unfortunately, “hasty, opportunistic implementations of syndromic surveillance,” including some U.S. projects,
“have not allowed the theoretical power of the method a fair test,” he observes.
In their stead, Kelley advocates the creation of surveillance systems, including
syndromic components, designed to answer clear and specific questions. He also
considers how syndromic surveillance could be applied to detect serious but lowfrequency threats such as bioterror attacks, SARS, or avian influenza in time to
contain their further spread.
Following Kelley’s paper, with its focus on the design of syndromic surveillance systems, Stoto’s essay considers their evaluation. He defines and applies a
framework for gauging the usefulness of syndromic surveillance in public health
practice, then uses it to identify a number of statistical and practical challenges
to using such surveillance for detecting bioterrorist events. By contrast, he finds
promise in using syndromic surveillance to detect natural disease outbreaks
(including seasonal and pandemic influenza), and in monitoring public health
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global infectious disease surveillance and detection
response to disease outbreaks. Realizing this potential will require designing
systems that focus on these uses rather than being optimized for timely detection
of large-scale bioterrorist attacks, Stoto concludes.
The next paper, by Joseph Lombardo of the Johns Hopkins Applied Physics
Laboratory, addresses another aspect of timeliness in surveillance: the implications of “real-time” versus “batch reporting” of surveillance information. Noting
that confusion has arisen around the use of these terms, Lombardo carefully
defines them and provides illustrative examples. He concludes by describing the
possible combination of both modes in surveillance systems that use efficient
“batched” surveillance processes for the routine monitoring of public health,
and more resource-intensive “real-time” processes to examine specific threats
as they arise.
Surveillance of Animal and Plant Diseases
Recognizing that “the health of people, animals, plants, and the environment
in which we all live are inextricably linked,” in the words of workshop presenter
William Karesh, surveillance must encompass far more than human diseases.
Karesh’s contribution to this chapter describes initial efforts toward this goal,
focusing on projects undertaken by his own organization, the Wildlife Conservation Society (WCS). He describes the threat spectrum, origins, risk factors, and
consequences of infectious disease in wild animals, and he observes that “the
immediate effects of the diseases themselves are often the least of the worries.
Infectious diseases of people and animals are drivers of poverty and associated
civil unrest, disrupt ‘free’ ecosystem services such as drinking water and plant
pollination, and can ruin otherwise well-planned and sustainable economic development efforts.”
In two papers that conclude the chapter, plant pathologists Jacqueline Fletcher
of Oklahoma State University and James Stack of Kansas State University define
threats (both natural and intentional) to U.S. crops and provide examples of
high-consequence plant diseases. The first paper outlines components of a strong
plant biosecurity strategy, discusses progress toward its achievement, and notes
opportunities for further improvement. In the second paper, the authors evaluate
each component of the biosecurity strategy (prevention, surveillance, detection,
diagnosis, response, and recovery) and suggest specific actions the United States
could take to support each area.
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SURVEILLANCE STRATEGIES
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SYNDROMIC SURVEILLANCE:
MOVING FROM THEORY TO PRACTICE
Patrick W. Kelley, M.D., Dr.P.H.
The National Academies
Assessing the health of a community has similarities to assessing the health
of a person. A variety of detectors of ill health can be brought to bear in ways that
range from passive monitoring that depends on those affected to raise a concern
to active and aggressive monitoring of those apparently without complaint to
identify the earliest manifestations of a problem. The desire for earlier detection of acute health problems at either the individual or community level has in
recent years stimulated the search for better “detector” mechanisms. Syndromic
surveillance is one of these now in vogue as a solution to the growing challenge
of early disease detection in communities and management of consequent public
health interventions.
Though infectious disease reporting started in Europe and the United States
in the late 1800s, it was not until 1925 that all U.S. states participated in national
morbidity reporting. Only after Alex Langmuir went to the Centers for Disease
Control and Prevention (CDC) in 1950 did the term “surveillance” become conceptualized beyond the monitoring contacts of persons with contagious diseases.
At CDC Langmuir developed a concept of surveillance inspired by military
intelligence data gathering and incorporated the approach into daily public health
practice. Soon CDC had national systems for malaria, polio, and influenza. In
more recent times, advances in laboratory and mathematical methods and technologies have pushed horizons farther and stretched academic definitions. These
cutting-edge approaches to disease detection at the community level encompass
networks for surveillance using molecular fingerprinting and exciting, web-based
methods of information capture and assessment such as the Program for Monitoring Emerging Diseases (ProMED) and the Canadian-World Health Organization (WHO) Global Public Health Intelligence Network (GPHIN). In this
more demanding context, we now have the evolution of automated syndromic
surveillance.
The elaboration of more sophisticated approaches to surveillance has been
stimulated by the recognition over the past 30 years of at least 30 “new” emerging
infectious diseases. These encompass infections of plants, animals, and human
beings. Of course, an acute concern is the threat of bioterrorism but many naturally occurring emerging disease outbreaks have highlighted the need for rapid
detection and characterization. Perhaps the greatest concern now is the need to
promptly recognize the syndromic pattern of an H5N1 influenza outbreak, here
Director,
Board on Global Health and Director, Board on African Science Academy Development,
Institute of Medicine.
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global infectious disease surveillance and detection
or in remote parts of Asia or Africa, so that aggressive attempts to eliminate it
can be instituted before it becomes uncontainable. Similar urgency arose during the 2003 severe acute respiratory syndrome (SARS) epidemic. For some of
these emerging infections, it was months before an agent was isolated, and thus
timely and sensitive public health surveillance and response was syndromic to a
great degree. The tragedies of HIV in Africa and the slow recognition of SARS
in China are reminders of the consequences of slow responses and motivate the
question of what surveillance system designs could have made a difference. With
bioterrorism a rapid assessment and response is even more critical.
“Syndromic surveillance” is defined by CDC as the collection and analysis of
“health-related data that precede diagnosis and signal with sufficient probability
of a case or an outbreak to warrant further public health response” (CDC, 2006a).
This differs from more traditional surveillance in several ways but primarily the
objective is that by using prediagnostic data, syndromic surveillance aims to be
timelier in identifying emerging problems. The phenomena of emerging infections and all the associated aspects of globalization that accompany them, as
well as the specter of bioterrorism, drive the need to be more cognizant of public
health events and to act despite limited information. Timeliness is not the only
advantage of the method, though. An additional goal is that syndromic surveillance should be more sensitive at detecting aberrations in normal patterns because
it does not depend on confirmed diagnoses, something that can be an expensive
proposition, especially in developing countries.
Some advocates have great enthusiasm for transitioning syndromic surveillance from the epidemiologic laboratory into routine practice, but others are skeptical, preferring to put their confidence in traditional approaches and the “astute
clinicians” who have risen to the occasion so often in this country. Unfortunately,
while developed countries have a fair number of clinicians who are astute at
least much of the time, the developing world, where so many disease problems
emerge, is a different case. A system of complementary systems—including clinicians, traditional methods, and well-designed syndromic surveillance tailored to
the setting of a particular community—may ultimately yield the wide range of
perspectives needed to meet the demanding public health challenges of emerging
infections and globalization. The best mix of surveillance interventions will vary
from community to community. A challenge now is to do the operations research
to adapt academic surveillance concepts to unique community circumstances.
This is important not only in communities with strong health systems, but also
in developing countries, where nontraditional approaches may be more essential
and affordable than in places with a relative abundance of astute clinicians, laboratories, and hospitals, such as the United States.
Some observers seem frustrated by syndromic surveillance because it has
detected few outbreaks, as implemented in the United States over the past few
years. Many doubt that it will perform better than alternative mechanisms to alert
the public health community to a problem. Perhaps though hasty, opportunistic
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51
implementations of syndromic surveillance have not allowed the theoretical
power of the method a fair test. Also, the purposes of syndromic surveillance go
beyond earlier detection and provide situational awareness across a community,
something that individual clinicians can rarely provide. Though other mechanisms, to include astute clinicians, may help recognize a problem, an effective
surveillance system, syndromic or otherwise, should also rapidly characterize
a problem epidemiologically because this is essential to efficiently target what
are invariably limited response assets. A system should enable civic leaders to
establish the boundaries of the problem and allay some unjustified fears through
more credible risk communication.
In tabletop exercises of public health crises, the value of information for
management has been highlighted both as being in short supply and as being
something that a properly constructed syndromic surveillance system should
help develop. In one important biodefense tabletop simulation exercise, “Dark
Winter,” Frank Keating, former governor of Oklahoma, said:
You can’t respond and make decisions unless you have the crispest, most current, and best information. And that’s what strikes me as a civil leader . . . that
is . . . clearly missing (O’Toole et al., 2002).
Central to effective surveillance is beginning with a clear appreciation for the
capabilities sought. Precisely what phenomena need detection, in precisely what
populations is the detection needed, and what data would be most effective for
that purpose? Much work has been accomplished in developing syndromic definitions and analytic algorithms but before syndromic surveillance is seen as the
solution, the full range of scenarios that need to be detected must be considered
as well as how best to build epidemiologic “detectors” for demographically different communities in both rich and poor countries.
Although in the United States there is a tendency to associate syndromic
surveillance with the specter of bioterrorism, WHO has come to recognize that
the protection of global health against emerging infections was poorly served by
the last version of the International Health Regulations (IHRs), which mandated
reporting to WHO only three specific diseases: yellow fever, plague, and cholera.
Realizing that some of the most critical recent global public health threats—such
as AIDS, SARS, Ebola, pandemic influenza, and Nipah virus—initially were
ill-defined syndromes, a new version of the IHRs has been adopted by member
states and is set to go into effect in 2007. This document calls on countries to
maintain, at the local level, capabilities to detect and assess not only well-defined
diseases and established causes of death, but also to report any significant levels
of morbidity of potential international public health importance. So, the mandate
for general global public health surveillance is moving beyond defined diseases
to encompassing a global responsibility to detect and report, in a timely manner,
internationally important disease events whether they are well or ill defined and
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global infectious disease surveillance and detection
Percentage treated (per week)
whether they are individual cases or clusters. A capability for syndromic detection
seems central to the new paradigm, especially in countries that lack the resources
for extensive use of more specific approaches.
Although the term “syndromic surveillance” has only been in vogue for
about a decade and is thought to represent somewhat of a frontier in surveillance, the potential contributions of “prediagnostic surveillance” have been long
established. In tracking down the last cases of smallpox and polio in developing
countries, syndromic monitoring has been central. For decades, the military has
also used syndromic approaches to monitor unit health on deployments and in
training because it was the most cost-effective, rapid, and reliable way to monitor the health of the force, especially in austere conditions. The military often
operates in settings with limited laboratory support, but with a critical need to
detect health threats in a timely manner. For example, Figure 1-1 illustrates the
tracking of diarrheal syndromes in a U.S. Marine force during the first Gulf
War of 1990–1991. With regular syndromic tracking of morbidity seen in sick
call, outbreaks were routinely recognized quickly by competent epidemiologists
against normal background rates. Investigations were launched rapidly to contain
problems that could debilitate unit combat effectiveness.
In U.S. military basic training camps, where respiratory syndromes are
particularly devastating, for decades there has been well-developed, centrally
monitored syndromic surveillance for acute respiratory syndromes (Gray, 2005;
Gunzenhauser, 2003). Syndromic surveillance in the basic training setting has
been used routinely to guide the use of mass antibiotic prophylaxis to prevent outbreaks of rheumatic fever when syndromically associated thresholds are crossed.
Week
FIGURE 1-1 Syndromic surveillance of U.S. marines for treated diarrheal syndromes
during the lead-up to the Persian Gulf War, 1990–1991.
SOURCE: Hanson (2005).
1.1
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SURVEILLANCE STRATEGIES
All of these practical implementations of syndromic surveillance reflect
movement from theory and simple systems to complex systems. Moving from
theory to practice involves a larger context where pieces must be made to work
together and adapted to the locality.
Reflecting all the elements to be integrated, one might define a surveillance
system, as distinct from surveillance, as follows:
A system for public health surveillance is a group of integrated and qualityassured, cost-effective, and legally and professionally acceptable processes,
designed for the purpose of identifying in an ongoing, flexible, standardized,
timely, simple, sensitive, and predictive manner the emergence of meaningful epidemiologic phenomena and their specific associations. These processes
include human, laboratory, and informatics activities to skillfully manage information derived from an entire defined community (or a subgroup thereof that
is sufficiently representative and large) and to disseminate that information in a
timely and useful manner to those able to implement appropriate public health
interventions.
As shown in Figure 1-2, a surveillance system needs to be seen in the context in which it works and as reflecting a hierarchy of elements that depend on
each other. One needs a clear and specific idea of what questions the system
should address. Who should be under surveillance and for what are most critical. Developers of syndromic surveillance systems often start to conceptualize
Identification
of system parts
Theory
Research on
parts
Envisioning the
whole system
Research on
integrated parts
Small-scale
proof of concept
Adaptive
development
Recognizing the
question—What
needs to be
detected?
Scale--up and
systems integration
Evaluation and
improvement
FIGURE 1-2 Conceptual steps in development and implementation of a syndromic surveillance system in a community.
SOURCE: Kelley (2006).
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global infectious disease surveillance and detection
a system with opportunistically available data rather than a clear definition of
the range of scenarios that their surveillance system must be able to recognize
as priorities. Typical “opportunistic” data might be routinely collected for other
purposes during an emergency room consultation or from “convenient” sources
such as government clinics regardless of how well they sample the community
of interest. Opportunistic datasets are rarely the strongest cornerstone on which
to build and can handicap an otherwise rigorous implementation.
Different epidemiologic scenarios will affect populations in different ways.
Key though is that if one wants to detect any epidemiologic scenario, the population under surveillance should include the one likely affected. If space and time
separate these populations, as may be the case with the most easily available
“opportunistic” datasets, little signal will be generated. If demographic misclassification affects the description with respect to person, place, and time, associations may be missed. If one lets the surveillance question drive the development
of the database used, there is a better chance that the population under surveillance will generate a strong signal because it will include a substantial fraction of
those exposed. Resources should be invested into negotiating for and developing
data with the richest “veins of ore” rather than focusing it proportionately on the
mining of poorly conceived data sources with ever more complex analytic methods. An example of this became obvious in looking at convenient outpatient data
in the Department of Defense (DoD) Electronic Surveillance System for the Early
Notification of Community-based Epidemics (ESSENCE), developed in the late
1990s for use for surveillance in the National Capital Region.
Like syndromic surveillance systems, the datasets initially available to
ESSENCE routinely classified patients experiencing morbidity by the ZIP code
of residence. The problem is that one could reasonably assume that most exposures, natural or manmade, would occur away from home in places such as the
Pentagon, the Capitol, a sports venue, or the subway. As became evident in a
geographic analysis, the bulk of military health-care beneficiaries tracked through
ESSENCE did not live where many exposures would most likely occur, in the
District of Columbia, but rather had homes scattered over a hundred ZIP codes
throughout the region. This residence-based misclassification, stemming from the
use of “opportunistic data” easily at hand, would have greatly diluted syndromic
signals arising from exposures at the workplace. This misclassification produces
what might be termed the “donut-hole effect” (Figure 1-3).
As exposed persons migrate from a center city worksite of exposure, where
they might be classified most effectively as an “exposed” population, they disperse into the suburbs, where they blend with unexposed populations so completely that any signal is greatly damped out. Overcoming this depends on not
settling for datasets of convenience. Populations in which those under medical
surveillance have limited geographic mobility can help correct for the donuthole effect. Students at universities might be one example. Residents of nursing
homes and prisons may be other populations where there is less risk that place of
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SURVEILLANCE STRATEGIES
National Capital Area
Counts of military beneficiaries by ZIP
NCA
1-500
500-1,000
1,000-5,000
5,000-10,000
10,000-50,000
50,000+
FIGURE 1-3 The donut-hole effect.
SOURCE: Kelley (2006).
exposure and place of residence differ.
1-3Another setting is military basic training.
However, a limitation of many of these populations is that they may not be near
the locations where surveillance is most critically needed, making their ability to
serve as sentinels less than ideal.
With the DoD ESSENCE, some of the most impressive syndromic signals
have come from basic training outbreaks, where the exposed population lived and
worked in the same location. This meant there was no problem with the migration
phenomena causing people exposed in one place to be classified geographically
in another. The strength of the signal and its rapid detection was also greatly
facilitated by the ability to attribute morbidity to a well-defined denominator
population that included most cases. For populations on the move, if they work
in high-value targets such as centers of government, it may be a high-yield investment to develop a way to ensure that they can be classified by both their primary
residence and primary workplace.
In moving from syndromic surveillance theory to practice, the first step is
appreciating not what data are at hand, but what are the “who, what, and when”
questions that need to be answered. The most effective surveillance systems will
likely be systems of systems because the questions to be answered will reflect
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global infectious disease surveillance and detection
multiple scenarios, each of which presents a different challenge. The classic
incident is an exposure to a whole community. In the bioterrorism scenario, this
might be a regionwide aerosol plume, but many other scenarios may be even more
likely and successful. Potential exposure scenarios include the following:
• Regionwide aerosol plume
• Seeding of a focal or traveling population with contagious (suicidal) persons (e.g., smallpox)
• Contaminated food distribution (e.g., Salmonella spp., hepatitis, E. coli,
or bovine spongiform encephalopathy)
• Contaminated water supply (focal or general)
• Focused attack against high-value worksite or event (e.g., letters to
Congress)
• Generalized aerosol plume against high-value site
• Focused aerosol attack against general population (e.g., mass transit)
The classic image is of a region-wide aerosol plume that distributes kilograms of an agent upwind from a population center with the idea of causing tens
of thousands of deaths and incapacitations. This is perhaps the worst case, but
likely the easiest to detect because it could affect large numbers of people across
a wide geographic swath. Perhaps a more likely challenge for public health would
be the seeding of a focal or traveling population with an infectious agent, such
as SARS or pandemic influenza. Debate is needed on the question of how best
to apply syndromic surveillance methods to detect serious, but lower frequency,
events in time to contain their further spread. Beyond the astute clinician, who
may be an uncommon commodity especially in some developing countries, what
is the most sensitive mechanism to detect aberrancy at the population level when
only a handful of nondescript cases are initially involved, as might be the case
with an early human pandemic influenza scenario? Could the initial hands full
of cases of SARS in Viet Nam or China have been better contained if alerts had
been raised earlier and if communications to those who could have acted had been
more rapid? How could syndromic surveillance have been adapted to supplement
the astute clinician in the scenarios in Hanoi, Hong Kong, Singapore, or Toronto?
Does syndromic surveillance have a role in scenarios such as these or in identifying clusters of avian flu in Indonesia or Cambodia?
In considering rare but important low-frequency emergences of a new infectious disease, the example of West Nile further illustrates the fact that the questions asked of a surveillance system differ based on the agent and the scenario
to be detected. For West Nile encephalitis, tracking infrequent and not highly
unique human syndromes across a large general human population may not
be the most effective way to achieve the rapid recognition envisioned in the
new IHRs. Figure 1-4 shows the estimated sensitivity for West Nile virus by
different surveillance methods. A system of systems that includes animals that
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SURVEILLANCE STRATEGIES
Surveillance Method
Human cases
Disease activity
Veterinary cases
Mosquitoes
Sentinel hosts
Dead bird
Time
FIGURE 1-4 Estimated sensitivity for West Nile virus by different surveillance
methods.
SOURCE: CDC (2003).
1-4
manifest aberrations earlier in time would be preferable to waiting until larger
numbers of people develop encephalitis and are admitted to intensive care
units.
One of the more recent national public health concerns in the United States
has been the outbreak of E. coli O157:H7 associated with consumption of raw
spinach. Could a configuration of syndromic surveillance detect a focal or a dispersed outbreak from contaminated food? The E. coli outbreak involved a few
hundred cases across the country (Figure 1-5) (FDA, 2006). Would a focus on
unexplained hemolytic uremic syndrome be a way to complement the impressive
but slow molecular fingerprinting approaches that ultimately carried the day?
The molecular approaches to DNA fingerprinting for outbreak identification
were certainly valuable, but more than 10 days could easily pass between when
a patient develops symptoms and when a case is confirmed and linked with other
cases with the same fingerprint (Figure 1-6). Syndromic surveillance seeks to
narrow the gap.
Another important outbreak scenario to detect is the contaminated water
supply. The infamous Milwaukee cryptosporidiosis outbreak caused hundreds
of thousands of cases of diarrhea, but its nature was such that recognition of
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global infectious disease surveillance and detection
Cases
1-4
5-9
10-14
15>
199 Persons
3 Deaths
26 States
FIGURE 1-5 E. coli O157:H7 spinach-associated outbreak, 2006.
SOURCES: CDC (2006b) and Kelley (2006).
1-5
Patient eats
contaminated
food
Patient
becomes ill
Stool sample
collected
E. coli O157
identified
Public health lab
receives sample
Average time
from patient
becoming ill
to case
confirmation in
current spinach
E. coli outbreak
= 15 days
Cases confirmed
FIGURE 1-6 Time associated with confirming spinach-related illness.
SOURCE: CDC (2006c).
1-6
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59
cryptosporidiosis as the specific cause was quite delayed (MacKenzie et al.,
1994). Most sick people did not seek care. Labs were not testing for the agent
routinely, and many cases were just diagnosed as viral gastroenteritis. Could a
thoughtfully designed syndromic system of systems have led to more prompt
recognition and mitigation of the outbreak? The epidemiology of this significant
public health event should make operators of syndromic surveillance systems
consider how well their systems and the datasets used would pick up a problem
with a municipal water system. For example, this outbreak pointed out how small
a fraction of those affected may actually seek medical care (6.5 percent here),
much less go to an emergency room. How can the morbidity represented by these
individuals not be lost for surveillance purposes? Furthermore, as noted earlier,
many syndromic systems analyze data routinely by residential ZIP code, but how
many routinely group residences based on an appreciation for how water flows
through the municipal water distribution system in their city? In Milwaukee it
was clear that the map of the distribution system would have correlated powerfully with a pattern of attack. The sparing of special populations such as nursing
home residents was reminiscent of John Snow’s observations on the sparing of
the Whatney’s Brewery workers from the cholera outbreak in London in the late
19th century.
Another important scenario to think about is the focused attack against a
high-value site such as the 2001 anthrax letter attacks. Tragically in this attack a
number of people died, but some lives were probably saved by the action of the
hoped for astute clinician. Beyond the astute clinicians, however, what system
configuration would pick up those low-frequency cases that may reflect serious
morbidity as a harbinger of a more widespread exposure? Individual cases were
identified in emergency rooms in this attack. Some were not so quickly recognized and may have taken on a different characterization if appreciated in a larger
epidemiologic context rather than counting on an individual astute clinician to
sense a “big picture” beyond his field of vision. Perhaps rigorous surveillance of
intensive care units (ICUs) for epidemiologically unexpected admissions may be
a critical underdeveloped element of syndromic surveillance for problems such
as this anthrax episode and outbreaks of problems such as West Nile or SARS.
ICU surveillance may permit the time for more detailed epidemiologic characterization of epidemiologically suspect cases, that is, cases that are admitted with
no obvious predisposing reason. Pooling across a municipal region may allow
appreciation of patterns that no single astute clinician could be counted on to
detect, much the same way that unexplained death surveillance may be helpful,
if not too late.
Perhaps the most important scenario to detect is the “failed scenario.” We
know that the worst case scenario of a biological attack would not be easy for
most perpetrators, but that does not necessarily discourage them from trying.
Being able to detect a modest trial run outcome would be a much more useful capability than designing a system for a more obvious worst case scenario.
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The first generation of an avian influenza cluster would also be the best time
to appreciate a problem. A goal of surveillance systems should be to not only
detect the classic worst case attack early or the widespread deaths of chickens,
but also to detect what may more often be a botched attempt that falls far short
of the perpetrators’ hopes or the earliest generation avian flu outbreaks. The
unsuccessful 1993 attempts by Aum Shinrikyo to spray anthrax over the city of
Tokyo illustrate this point (Takahashi et al., 1994). Fortunately this incompetent
attempt did not cause a single case, but if it had, even one case could have been
valuable to recognize as a harbinger of future threats. Perhaps the complete
failure of this anthrax attempt caused Aum Shinrikyo to move on and use sarin
in the Tokyo subway. A lesson is that motivated enemies will keep trying and
could get better with practice. A comprehensive surveillance system should set
its sights on detecting a wide range of scenarios to include trial runs or largely
botched low-yield events that may indicate that more effective efforts are in the
offing.
A recent review of abstracts accepted for presentation at the October 2006
International Disease Surveillance Conference in Baltimore, Maryland, showed
that more states than not have started to explore syndromic approaches to disease
detection and management. In addition to the United States, seven foreign jurisdictions also came to the meeting to present systems for syndromic surveillance.
In comparing the datasets represented in systems described at the 2003 meeting
with the 2006 abstracts, implemented systems are still overwhelmingly focused
on emergency rooms and hospital diagnoses—81 percent in 2006 (Figure 1-7
and Table 1-1). Although these data sources are obviously relevant for many
scenarios mentioned and may be the most convenient, they are not necessarily
the answer to all challenges. Other populations and venues may lend themselves
to better classification with respect to person, place of exposure, and time. To get
the most power out of the analytical methodologies being developed, there may
be justification to put the focus on other datasets to illuminate different aspects
of the clinical continuum and work so they contain the most informative fields.
Each of these varied data sources in Table 1-2 may provide a unique perspective on a particular epidemiologic scenario, especially if public health practitioners help shape the characteristics of the data rather than just settling for what
data are readily available. If public health practitioners are on the alert for emerging infections, including bioterrorism, the aim should be to do more than detect
only large unexplained outbreaks, but also to have the ability to detect isolated,
unexpected cases with unusual age, gender, or occupational characteristics. The
need to do this is driven not only by American concerns over bioterrorism, but is
also reflected in visions of the new IHRs. If public health officials are to detect
and contain pandemic influenza, it is doubtful that they will be very successful if they fail to recognize emerging patterns until there is a large unexplained
outbreak.
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61
FIGURE 1-7 Locations of surveillance systems in abstracts for the 2006 International
Society for Disease Surveillance (ISDS) meeting. Countries represented include United
States, Canada, Netherlands, Taiwan, Hong Kong, France, Scotland, and Greece. States
represented include AZ, CA, CT, DC, 1.7
FL,color
GA, IN, LA, MA, MD, NC, ND, NH, NV, NY,
OH, PA, TX, UT, VA, VT.
SOURCE: Kelley (2006).
To summarize, as demonstrated by Figure 1-8, public health surveillance
begins with understanding the questions “who, what, and when” that need to be
asked, and then it seeks the most effective data sources.
A system for public health surveillance, which is what needs to be built in the
move from academic theory to practice, is built on that data foundation, but it also
needs a set of powerful analytic tools and skillful people to use them and interpret
the findings. The skill sets of local public health staff to interpret data of this type
need expansion. Because this is a complex science still under development, perhaps academic partnerships need to be sought for all serious adaptations of these
concepts to specific localities. Few approaches can be just “dropped in” without
an appreciation for local epidemiologic and demographic peculiarities. Perhaps
most in short supply are the resources to do something promptly to respond to
findings. Budgets for surveillance systems should be accompanied by budgets
for a serious response capability. Finally, the underlying population demographic
structures and exposure likelihoods of some localities may make syndromic surveillance a low-yield, cost-inefficient activity. This may not be the destination for
every community. Guidelines for where performance is expected to be lower are
needed as well as insights into where value is likely to be added.
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global infectious disease surveillance and detection
TABLE 1-1 Sources for Syndromic Surveillance, 2003 and 2006 Annual
Meeting Abstracts
2003
2006
Data Sources
# of
Abstracts
% of
Abstracts
# of
Abstracts
% of
Abstracts
Emergency departments
Hospital diagnosis
Office/clinic visits
Over-the-counter drugs
911/emergency medical service runs
Laboratory results
Nurse advice lines
Laboratory orders
School nurse records
Poison control center
Veterinary diagnosis
Health-care employee absenteeism
School absenteeism
School perception of an outbreak
Medical examiners
Thermometer sales
Evacuation shelter primary reports
Local/regional news sources
Web logs
Online obituaries
Medical center parking lot volume
29
7
13
5
6
2
4
1
—
5
3
—
7
1
2
—
—
—
—
1
1
48
12
22
8
10
3
7
2
—
8
5
—
12
2
3
—
—
—
—
2
2
38
17
11
7
6
5
3
1
1
1
1
1
1
—
—
1
1
1
1
—
—
56
25 ↑
16 ↓
10 ↑
9 ↓
7 ↑
4 ↓
1
1
1 ↓
1 ↓
1
1 ↓
—
—
1
1
1
1
—
—
SOURCES: Sosin and DeThomasis (2004) and Kelley (2006).
TABLE 1-2 Potential Sources of Data for Syndromic Surveillance
•
•
•
•
•
•
•
•
•
•
•
Emergency rooms
Over-the-counter drug sales of symptomatic therapies
School and/or work absenteeism
Nurse advice lines
Ambulatory clinics
Laboratory test requests (e.g., fecal ova and parasite)
Prescriptions
Emergency medical systems (911)
Hospital and intensive care unit surveillance for syndromes
Unexplained deaths
Wild and domesticated animal health
SOURCE: Kelley (2006).
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SURVEILLANCE STRATEGIES
Agent,
host,
scenario
A reasonable
question
Operations
research
Analytic
methods
The right
data
Person,
place,
time
Tools
Skills
Information
technologies
Training
ENABLERS
ACTIONS
Data capture
Armchair and
shoeleather
epidemiologic
interpretation
Staff and
infrastructure
Laws; policies;
standard operating
procedures;
Command, Control,
Communications,
Intelligence
Warning and
response
Roles, structures,
and systems
FIGURE 1-8 System requirements for public health surveillance.
SOURCE: Kelley (2006).
SYNDROMIC SURVEILLANCE
1-8 IN PUBLIC HEALTH PRACTICE
Michael A. Stoto, Ph.D.
Georgetown University
Heightened awareness of the risks of bioterrorism since 9/11, coupled with a
growing concern about naturally emerging and reemerging diseases such as West
Nile, severe acute respiratory syndrome (SARS), and pandemic influenza, have
led public health policy makers to realize the need for early warning systems and,
more generally, improved surveillance. The sooner health officials know about an
attack or a natural disease outbreak, for example, the sooner they can treat those
who have already been exposed to the pathogen to minimize the health consequences, vaccinate some or all of the population to prevent further infection, and
identify and isolate cases to prevent further transmission. In addition, improved
surveillance systems should allow for better “situational awareness” and thus help
to manage the response to public health emergencies.
School
of Nursing and Health Studies.
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global infectious disease surveillance and detection
Traditional public health surveillance approaches monitor disease using prespecified case definitions and employ manual data collection, human decision
making, and manual data entry. In contrast, newly developed syndromic surveillance systems employ sophisticated information technology (IT) and statistical
methods to gather, process, and analyze large amounts of data and display the
information for decision makers in a timely way. For example, syndromic surveillance systems assume that during an attack or a disease outbreak, people will
first develop symptoms, then stay home from work or school, attempt to self-treat
with over-the-counter products, and eventually see a physician with nonspecific
symptoms days before they are formally diagnosed and reported to the health
department. To identify such behaviors, syndromic surveillance systems regularly
monitor existing data for sudden changes or anomalies that might signal a disease outbreak. Syndromic surveillance systems have been developed to include
data on school and work absenteeism, sales of over-the-counter products, calls
to nurse hotlines, and counts of hospital emergency room (ER) admissions or
reports from primary physicians for certain symptoms or complaints (Mandl et
al., 2004).
Recognizing that the “ability to gather and analyze information quickly
and accurately would improve the nation’s ability to recognize natural disease
outbreaks, track emerging infections, identify intentional biological attacks, and
monitor disease trends,” the Institute of Medicine (IOM) recently called for more
research on syndromic surveillance and other “innovative systems of surveillance
that capitalize on advances in information technology.” However, because surveillance systems in the United States “remain fragmented and have not evolved
at the same rate as . . . electronic technological advances,” the IOM calls for these
systems to be “carefully evaluated for their usefulness in detection of infectious
disease epidemics, including their potential for detection of major biothreat
agents, their ability to monitor the spread of epidemics, and their cost effectiveness” before widespread implementation (IOM, 2003).
To address the issues identified by the IOM, this paper begins by describing
a framework for evaluating the usefulness of syndromic surveillance in public
health practice. Application of this framework to existing systems identifies a
number of statistical and practical concerns when syndromic surveillance is used
to detect bioterrorist events. The analysis suggests, however, that these systems
may be more useful in detecting natural disease outbreaks (including seasonal
and pandemic influenza) and in the public health response to known disease
outbreaks.
Evaluation of Syndromic Surveillance Systems’ Usefulness
Asking whether syndromic surveillance “works” or not is not particularly
helpful. Rather, just as clinicians need to know the performance characteristics
of screening and diagnostic tests, public health epidemiologists need to charac-
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65
terize the performance of syndromic surveillance detection systems in terms of
the kinds of events that can be detected as a function of the responsible antigen,
outbreak size, timing, and other characteristics. Thus, evaluation of syndromic
surveillance systems’ usefulness involves a number of dimensions.
Evaluations of data accuracy and use, for example, include studies of the
accuracy of electronic records that form the basis of the systems compared with
an independent source, the accuracy of use of standard codes, the accuracy of
data preprocessing, and similar issues. This aspect of evaluation also includes
studies of the appropriateness of methods and protocols for data analysis, data
display, monitoring, and reporting, as well as how these methods are applied and
how they lead to action.
Evaluations of system utility include studies of the costs and benefits of
day-to-day use of syndromic surveillance, relative to existing systems, to identify
communicable or reportable diseases, to increase situational awareness, or to
assist in investigation and management of a disease outbreak. These studies also
assess the costs and benefits to users of identifying and evaluating data anomalies
using the system, as well as flexibility, acceptability, and stability. Finally, evaluation studies characterize statistical properties such as sensitivity, false-positive
rates, and timeliness. As illustrated below, statistical evaluations can be based
on simulation studies and comparisons of syndromic surveillance findings with
known actual events.
Concerns About Syndromic Surveillance in Public Health Practice
Despite the generally recognized promise of syndromic surveillance systems,
there are many practical concerns about the use of these systems in state and
local public health practice. The possibility of earlier detection and more rapid
response to a bioterrorist event has tremendous intuitive appeal, but its success
depends on local health departments’ ability to respond effectively. When a syndromic surveillance system sounds an alarm, health departments typically wait a
day or two to see if the number of cases continues to remain high or if a similar
signal is found in other data sources. Doing so, of course, reduces both the timeliness and sensitivity of the original system. If the health department decides that
an epidemiological investigation is warranted, it may begin by identifying those
who are ill and talking to their physicians. If this does not resolve the matter,
additional tests must be ordered and clinical specimens gathered for laboratory
analysis. Health departments might also choose to initiate active surveillance by
contacting physicians to find out if they have seen similar cases.
The detection of a sudden increase in cases of influenza-like illness (ILI)—
the kind of condition that syndromic surveillance can detect—can mean many
things. It could mean a bioterrorist attack, but is more likely a natural occurrence,
perhaps even the beginning of the annual flu season. An increase in sales of flu
medication might simply mean that pharmacies are having a promotion. A surge
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global infectious disease surveillance and detection
in absenteeism could reflect natural causes, or even a period of particularly pleasant spring weather. Similar problems can occur when changes in local hospital
systems, or even in coding practices, can result in substantial changes that could
raise concern if they are not understood.
Additionally, a syndromic surveillance system that says only that “there have
been five excess cases of ILI at hospital X” is not of much use unless the five
cases can be identified and reported to health officials. For example, if there are
65 cases rather than the 60 expected, syndromic surveillance systems cannot say
which 5 are the “excess” ones, and all 65 must be investigated.
Like all alarm systems, syndromic surveillance detection algorithms have
intrinsic statistical tradeoffs. The most well known is between sensitivity, the
ability to detect an attack when it occurs, and the false-positive rate, the probability of sounding an alarm when in fact there is no attack. The costs of excessive false alarms are both monetary, in terms of resources needed to respond to
phantom events, and operational, as too many false events desensitize responders
to real events. Taking into account the different data types and multiple jurisdictions, thousands of syndromic surveillance systems soon will be running simultaneously in cities and counties throughout the United States. If 1,000 data streams
are being monitored, each with a 0.1 percent false-positive rate (which is very
low), there will be approximately one false alarm per day.
The timeliness of a surveillance system depends on the time it takes to generate and acquire data, analyze it, and take action (Buehler et al., 2003). Even when
the cause and route of exposure are known, the available control strategies—
quarantine of suspected cases, mass vaccination, and so on—are expensive and
controversial, and often their efficacy is unknown. Coupled with the confusion
that is likely during a terrorist attack or even a natural disease outbreak, deciding
what to do could take days to weeks.
With syndromic surveillance, an additional component is the time required
to accumulate enough evidence of an outbreak to trigger a detection algorithm.
To illustrate this point, Stoto and colleagues used a simulation approach to analyze ILI emergency department admissions data from a typical urban hospital. A
hypothetical number of extra cases spread over a number of days were added to
actual baseline data to mimic the pattern of a potential bioterror attack. Figure 1-9
(A and B) indicates the size and speed that outbreaks must attain before they are
detectable, according to four statistical detection algorithms. The solid bar represents an algorithm that uses only one day’s data. The other three detection algorithms, shown with shared bars, average cases over several days. These results
are sobering: Even with an excess of nine cases over two days (the first two days
of the “fast” outbreak), three times the daily average, there was only about a
50 percent chance that the alarm would go off. When 18 cases were spread over
nine days, chances were still no better than 50-50 that the alarm would sound by
the ninth day (Stoto et al., 2004).
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SURVEILLANCE STRATEGIES
A
100%
Probability
of detection
80%
60%
40%
20%
0%
1
2
3
Day of attack
B
60%
Probability
of detection
40%
20%
0%
1
2
3
4
5
6
7
8
9
Day of attack
FIGURE 1-9 Sensitivity of syndromic surveillance (probability of detection by day) for
influenza-like illness at a typical urban hospital emergency room using four detection algorithms, as indicated by shading pattern (see text). A) fast outbreak: 18 cases over three
days, B) slow outbreak: 18 extra cases over nine days.
SOURCE: Stoto et al. (2004). Reprinted with permission from Chance. Copyright 2004
by the American Statistical Association. All rights reserved.
1-9B
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global infectious disease surveillance and detection
Can Performance Be Improved?
Simulation studies such as the one summarized in Figure 1-9 (A and B)
has shown that unless a bioterrorism outlook is exceptionally large, syndromic
surveillance detection algorithms take days to be detected (Stoto et al., 2004;
Jackson et al., 2006; Buckeridge et al., 2006; Stoto et al., 2007). Results like this
naturally lead one to ask whether this performance can be improved. Indeed, there
are a number of approaches; however, although these approaches may lead to better performance for some outbreak types, they are less able to detect others.
Syndromes other than ILI, for example, might be more easily detected
because they are less common, but this only works if a terrorist—or nature—
chooses to use an agent that caused those symptoms. Systems can and typically
are set up to monitor eight or more separate sets of symptoms. Doing so increases
sensitivity simply because more conditions are monitored, but as discussed above,
increasing the number of syndromes monitored will also increase the number of
false positives.
Another possibility is to pool data over multiple data streams, perhaps from
all hospitals in a metropolitan area or state. A number of cities are currently doing
this. If this results in both the signal and the background increasing proportionally, it will result in a more effective system. If, however, there were 18 extra
cases of ILI in a city, but they all appeared at one hospital, this signal would be
lost in the noise of the entire city’s cases. Moreover, such an increase would be
clear without any sophisticated surveillance system. One can analyze the data for
the entire city and for each hospital individually, but with 10 separate analyses,
the number of false positives would also increase.
Finally, the data can be analyzed geographically. If there were 18 extra cases
of ILI in a city, and all lived in the same neighborhood, that would be more informative than 18 cases scattered throughout the city—it would suggest a biological
agent released in that area. This is only effective, however, for a geographically
focused bioattack, and would not work if terrorists chose to expose people in an
office building or at an airport. It is also less likely to detect seasonal or pandemic
influenza, which spreads rapidly before symptoms appear
Alternative Applications of Syndromic Surveillance
Since 9/11, the focus of syndromic surveillance efforts has been on early
detection of bioterrorist events. The most value, however, may ultimately come
from its use in the detection of natural disease outbreaks. More generally, if 21st
century syndromic surveillance means effective use of health information technology in identifying cases before they are formally diagnosed, it can supplement
traditional public health approaches and improve their effectiveness.
One potential use is in detecting influenza outbreaks. In an “ordinary” year,
influenza results in 36,000 or more deaths and more than 200,000 hospitalizations
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69
in the United States alone. In addition to this human toll, influenza-related costs
are more $10 billion a year. A pandemic, or worldwide outbreak of a new influenza virus, perhaps evolving from the H5N1 avian flu virus circulating in Asia,
could dwarf this impact by overwhelming our health and medical capabilities,
potentially resulting in hundreds of thousands of deaths, millions of hospitalizations, and hundreds of billions of dollars in direct and indirect costs. Syndromic
surveillance systems feature prominently in federal, state, and local plans to prepare the United States for pandemic flu (Homeland Security Council, 2005).
The Centers for Disease Control and Prevention (CDC) has a number of
influenza surveillance systems in place (CDC, 2007), yet they do not provide
population-based rates of incidence or prevalence rates on a national level because
many infected persons are asymptomatic or experience only mild illness and do
not seek medical care. Also, laboratory testing is not common and test results
become available late in the course of the illness. Epidemiological characteristics
of both seasonal and pandemic influenza, however, suggest that syndromic surveillance and other surveillance systems are likely to make an important contribution beyond the capabilities of existing surveillance systems, and thus enable a
more effective public health response. Simulation studies have shown that unless
a bioterrorism outlook is exceptionally large, syndromic surveillance detection
algorithms take days to be detected (Stoto et al., 2004; Jackson et al., 2006;
Buckeridge et al., 2006; Stoto et al., 2006). This time frame is longer than some
proponents of syndromic surveillance as a tool to detect bioterrorism suggest is
needed (Wagner et al., 2001). Compared to the current influenza surveillance
systems, however, a one-week lead time would provide valuable information, and
this is likely to be achievable for syndromic surveillance.
Furthermore, a number of studies have demonstrated the potential that syndromic surveillance of ILI offers at the national, state, and local levels. Sebastiani
and colleagues (2006) have shown that children and infants presenting to the
pediatric emergency department (ED) with respiratory syndromes are an early
indicator of impending influenza morbidity and mortality, sometimes by as much
as three weeks. Using data from New York City, Lu and colleagues (2006) have
shown that monitoring both outpatient and ED data can enhance detection of ILI
outbreaks. With similar data, Olson and colleagues (2005) note that age-stratified
analyses of ED visits for fever and respiratory complaints offer the potential
for more precise quantification of the burden of illness, earlier warning of the
arrival of epidemic influenza, and greater sensitivity for detecting the characteristic age shift of pandemic influenza. Comparing unspecified infection cases in
Washington, DC, hospitals using optimal detection algorithms to CDC’s sentinel
physician data for the South Atlantic states for four years in which there was a
discernable influenza outbreak, Stoto and colleagues (2007) found that in two of
those years, the DC syndromic surveillance based on hospital emergency room
data outperformed the other two systems, and in one year it flagged only two days
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global infectious disease surveillance and detection
after the CDC system. Given a built-in delay of about two weeks in the CDC
system, this is a substantial advantage.
In normal flu seasons, laboratory analysis to determine whether a case is
truly influenza, or to identify the viral strain, is rarely done. Testing, however, is
critical for identifying pandemic influenza, in which an antigenic shift results in
a new viral strain to which few people are immune by virtue of previous exposure. Syndromic surveillance of flu-like symptoms might trigger more laboratory
analysis than is typically done and in this way hasten the public health response.
In a normal flu season, Labus (2005) has reported that early identification of
the start of the influenza season using syndromic surveillance in Clark County,
Nevada, enabled the notification of the medical community. Physicians were
encouraged to submit specimens for culture, and the county health department
provided kits to help them do this, which allowed for rapid identification of
the major circulating strain. In 2003–2004 (a period with a marked increase of
early season influenza and deaths in children in other parts of the country) this
syndromic surveillance system allowed for better tracking, and provided data for
daily reports to decision makers and the media.
Because of their focus on the early detection of bioterrorist events, most
syndromic surveillance systems are designed to detect large increases in the
number of people with common symptoms such as ILI. As a result, they cannot
be expected to detect small numbers of cases, even if very unusual. One reason
is that in a small disease outbreak or the early stages of a larger one, each case
will be seen by only one physician. The natural tendency of physicians who see
only one case, however suspicious it may be, is to discount it. After all, physicians are appropriately taught “when you hear hoofbeats, think horse, not zebra.”
Some may fear the embarrassment of reporting a case that may turn out to be a
false alarm.
Modern health informatics systems provide the potential to identify the presence of small numbers of cases of concern before they are formally diagnosed.
For example, automated systems can aggregate data for a metropolitan area, spanning local reporting jurisdictions, to identify, say, cases of rash and fever, which
would suggest smallpox. Systems can also be set up to enable and encourage early
reporting of cases based on symptoms only. For example, the Syndrome Reporting Information System (SYRIS) system, now operating in Lubbock, Texas, and
elsewhere, enables physicians to report suspicious cases to the local health department without waiting for laboratory confirmation, and encourages them to do so
by providing feedback in the form of information about practice guidelines and
other similar cases (Lindley and Ward, 2007). This can be thought of as a kind of
“active syndromic surveillance” or as IT support for astute physicians.
Real-time access to prediagnostic data can also help health authorities
respond to public health threats. If person-to-person transmission of avian flu
virus is documented in Asia, for example, health departments in Europe and the
United States might want to identify and follow up on local cases of people hos-
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SURVEILLANCE STRATEGIES
71
pitalized with flu-like symptoms, and syndromic surveillance systems could be
designed to identify them. If an environmental sensor detects signs of the terrorist
agent tularemia, syndromic surveillance systems can be checked for cases with
appropriate symptoms. This actually occurred in Washington, DC in 2005, and
the lack of cases in area emergency rooms reassured local officials that the alarm
was false. Syndromic surveillance systems can also be queried to determine background rates when it is not clear whether a reported cluster of cases is unusual.
The E. coli O157:H57 outbreak in the New York City area in late 2006
provides an example of how syndromic surveillance could have been used for
case finding. The outbreak came to light on November 17 when the first case
was reported to a local health department in New Jersey. By November 27,
11 cases were reported in that jurisdiction. Three days later the Taco Bell restaurant, where people in 9 of the 11 cases had eaten closed voluntarily. On December 1, a similar case (originally attributed to another cause) was reported to a
local health department in New York state, and it turned out that this person and
three others in that jurisdiction had eaten at a different Taco Bell restaurant. By
December 4, all Taco Bells in the New York metropolitan area were closed, and
two days later a particular food item, green onions, was identified as the likely
source of contamination. By December 9, more than 61 E. coli O157:H57 cases
in at least four states were reported (CDC, 2006d).
Although a number of syndromic surveillance systems were operating at this
time in New York City and the surrounding jurisdictions, there were too few cases
in any location to detect. However, once the outbreak was identified in New Jersey, an advanced syndromic surveillance system could have searched emergency
department admissions for cases of bloody diarrhea and abdominal cramps in the
entire metropolitan area. Cases so identified could have been interviewed to take
a food history, and lab samples obtained to test for E. coli O157:H57. In addition, health departments could have initiated active surveillance by physicians in
the area, searched data from surrounding states to identify additional cases for
follow-up and to confirm lack of cases elsewhere. If these steps had been taken,
it is possible the restaurant chain and green onions could have been identified
and remedial steps taken earlier—either closing the restaurant or removing the
green onions. It is also likely that the additional data from syndromic surveillance
systems could have resolved the uncertainty about what was happening and thus
diminished public concerns.
Using syndromic surveillance—essentially, prediagnostic health information
in existing electronic databases—as these examples suggest requires flexible and
easily accessible IT systems, as well as a relationship between data providers and
health departments that enables the systems to be used when needed. A benefit
of developing these relationships may be improved communications between
health-care providers and public health, which is essential to responding to any
health emergency.
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global infectious disease surveillance and detection
Conclusions
Any careful review of the development of syndromic surveillance in the past
five years would have to conclude that much impressive work has been done with
respect to information technology, including the real-time integration of many
disparate data streams, and analysis—the development of statistical models,
detection algorithms, and methods to visualize syndromic data. From a public
health practice point of view, however, the value of syndromic surveillance for
detecting bioterrorist attacks has not yet been demonstrated. There are two major
reasons for this conclusion. First, in statistical terms, there is a relatively narrow
window between what can be detected in the first few days and what is obvious.
Second, better integration with public health systems is needed before information generated is useful in guiding a public health response. The analysis in this
paper, however, suggests that the most important contribution of syndromic
surveillance to public health practice may be for natural disease outbreaks, such
as seasonal and pandemic flu, and as a tool to monitor outbreaks and guide the
public health response. Realizing this potential will require designing systems
that focus on these uses rather than being optimized for timely detection of
large-scale bioterrorist attacks. Instead of automating the process of detecting
outbreaks with statistical detection algorithms, it might be more useful to build
flexible analytical tools into syndromic surveillance systems so they can monitor
ongoing bioevents and facilitate epidemiological analysis.
IMPLICATIONS OF “REAL TIME” VERSUS
“BATCH REPORTING” FOR SURVEILLANCE
Joseph Lombardo, M.S.
The Johns Hopkins University
Introduction
In the context of disease surveillance, there has been confusion promulgated
by vendors of systems on the requirement for “real-time” data feeds. The Institute
of Medicine requested the author to present material addressing the subject, “Real
Time” Versus “Batched” Reporting for Surveillance. The following discussion is
based on the author’s career of 37-plus years in developing, evaluating, operating,
and improving surveillance systems in different domains. Ten of these years have
been spent on developing and improving the Electronic Surveillance System for
the Early Notification of Community-Based Epidemics (ESSENCE), a disease
Center
of Excellence in Public Health Informatics.
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SURVEILLANCE STRATEGIES
surveillance system being used globally and locally by public health organizations (Lombardo and Buckeridge, 2007).
Definition
The terms “real time” and “batched” for disease surveillance can be used
to mean different things by different authors. Any discussion must begin with
some formal definition of these terms. The Institute of Electrical and Electronics
Engineers’ (IEEE’s) Computer Society Technical Committee defines real-time
systems as those “in which its temporal properties are essential for reliability
and correctness; the example applications include embedded systems, control
systems, monitoring systems, and multimedia systems” (IEEE-TCRTS, 2007).
Real-time computing systems are required for time-critical applications
where the result of a computing process is time critical. Examples with which
most everyone is familiar are video games where a split-second delay could
change the result of an outcome, or the use of antilock brake systems in cars to
provide immediate feedback and response to avoid a collision.
The term “batch” is used in computing much as it is in baking: a set of programs or jobs processed on a computer at one time, like baking a batch of cookies
in the oven. The Encarta (Microsoft Encarta, 2007) definition includes:
• Process items as batch: To process or assemble items as a batch or in
batches.
• Computer programs processed together: A set of programs or jobs
processed on a computer at one time.
Batched reporting of surveillance data, however, can mean a variety of things.
The following are just a few:
• Batched collection of health indicator data;
• Batched processing of indicator data;
• Reporting to health surveillance monitors that one or more rules have been
triggered at a periodic time interval; and
• Sending reports for reportable diseases in a group at some specific reporting interval.
The term “reporting” is used when the provider of the data (e.g., hospital, pharmacy, laboratory) sends data to the site where surveillance is being
conducted. This is usually the first step in the surveillance process. The term
“batched processing” is the processing of several files by applying mathematical
algorithms to derive information from the data. These algorithms can be used to
convert unstructured text data into structured data, for the identification of abnormal trends in the data, or for transforming data and information to be viewed in
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global infectious disease surveillance and detection
a manner that would permit easy interpretation by a variety of users. Batched
reporting is also used to refer to the actions needed to present data and algorithm
outputs to the users of surveillance systems. Collection and processing of data do
not occur at the same time as when data and results are being made available to
the user. Batched health data may be reported to users as soon as it is processed,
or it may be delivered at regular intervals, or accessed on demand.
The term “batched reporting” also has been used in the context of providing
notification of reportable disease to a higher public health authority. Reports of
animal diseases occurred monthly in some jurisdictions for those diseases that
are reportable, but do not pose an immediate threat.
Surveillance Context
Data Acquisition and Archiving
Figure 1-10 presents an example of a generic disease surveillance system.
Data acquisition occurs on the left of the figure. User interfaces are on the right,
and archiving and analytic processes are in the center. Possible sources of early
indicators of population health include 911 calls, emergency medical services,
emergency department chief complaints, over-the-counter self-medications, etc.
Some of the indicator data can be made available in real time while others can not.
Health Condition
Indicator Data
Sources
Emergency
department
chief
complaint
Secure
Communications
Archiving
Signal
Processing
Data
cleansing
Ambulance
calls
School
absenteeism
and nurse visits
Data
archive
Detection
algorithms
Web server
Military data
Text
parsing
Public Health
Information
Network
Messaging
System
FIGURE 1-10 Electronic health monitoring components.
SOURCE: Lombardo (2006).
1-10
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User
interfaces
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Only data that is captured in real time can be made available for surveillance in
real time. When a cashier in a large retail chain scans an item the transaction can
be captured and transmitted to the company’s distribution center. Several large
retailers of over-the-counter medications capture their sales in real time so they
can keep track of inventory in each store. Schools track absenteeism on a daily
basis and not throughout the school day. School nurses could potentially track
every student visit as it occurs. Many hospitals now have automated information
systems based on the Health Level Seven (HL-7) format. These systems provide
a comprehensive framework for the exchange, integration, sharing, and retrieval
of electronic health information. Such information includes the instruction of
orders; clinical observations and data, including test results; admission, transfer
and discharge records; and billing information. HL-7 has become a standard for
the interfacing of clinical data for many large hospitals (Health Data Standards:
The Players, 2007). Monitoring a hospital’s HL-7 message traffic creates a record
of activities within the hospital as information is entered and archived. Monitoring an HL-7 data stream provides hospital record data as close to the time they
are created as possible.
To preserve the timeliness of HL-7 records, many developers and surveillance system users believe the records need to be transmitted to the automated
surveillance system as quickly as they are created. One method for preserving
this timeliness is to provide continuous transmission of HL-7 records between the
hospital and the surveillance system. The use of a virtual private network (VPN)
permits HL-7 records to be transmitted as soon as they appear on the hospital’s
network.
Another popular mechanism for data transmission uses the File Transfer
Protocol (FTP). Records are accumulated and “batched” over some time interval, then sent at a specific time to the FTP site, where they are picked up by the
surveillance system for archiving and processing. The Center for Disease Control
and Prevention’s (CDC’s) BioSense program aggregates HL-7 hospital records
every 15 minutes, and transfers them to CDC using the Public Health Information
Network (PHIN) Messaging System.
Most state and local health departments have varying requirements for the
timeliness in which data are provided for surveillance. Many health departments
believe that receiving data once a day may be sufficient, while others believe
that real time is mandatory. The Department of Health and Human Services for
Montgomery County, Maryland, has implemented its data collection surveillance
component so it can acquire data at higher rates during times when the department is concerned about a possible health risk.
Data Processing
Once the data are acquired and archived by the surveillance system several
processing steps could occur. Initial processing is needed to reduce entry and
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global infectious disease surveillance and detection
transmission errors. The term used in Figure 1-10 to describe these processes is
“data cleansing.” Separate processing algorithms are needed to convert text data,
such as chief complaint, clinical notes, and radiology reports, into a structured
data for use in signal analysis. These processes are referred to as “text parsing”
in Figure 1-10.
Automated surveillance systems employ a variety of algorithms to process
data for early detection of a health event. “Signal processing” is a term frequently
used for these processes. If the datasets are large or diverse, or come from many
different sources, the signal processing steps can require several minutes to hours
of computing time. Certain algorithms, such as those for spatial analysis (e.g.,
attempting to form spatial clusters across hundreds of ZIP codes) are particularly
time consuming; as a result, such cases tend to be processed as batches because
they simply cannot be performed in anything resembling real time. Processing is
initiated and results are provided after well-defined periods, such as every four
hours.
Some surveillance systems are interactive and allow the user to invoke
specific processes to get an immediate result. These systems permit the user
to analyze and view data as they are being received. ESSENCE provides both
options. Data are processed at regular intervals and results available for display,
but they are also available for user-defined analysis as soon as they are received,
archived, and preliminary processes are completed.
User Interfaces
Many advanced disease surveillance systems take advantage of modern
Internet technology. Typically, a user/analyst views a website once a day, but in
the event of an emergent health threat, more frequent or ongoing analysis is possible if data are available.
Most modern disease surveillance systems provide outputs to users as soon
as the signal processing phase is complete. Users log on to the surveillance system and view the alerts or data. The alerts may be in the form of “flags” indicating
that a predetermined “threshold” has been exceeded or an anomalous condition
detected; temporal and spatial data displays; or lists of cases that contributed to
the alert.
“Real Time” Versus “Batched”
Most modern disease surveillance systems have multiple processes that must
be completed before the data are provided to users. Collecting data in real time
while processing it in batch due to the constraints in computing time does not make
An
algorithm is a set of well-defined rules or procedures for solving a problem in a finite number
of steps, or providing an output from a specific set of inputs (Banner Engineering Corp., 2007).
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SURVEILLANCE STRATEGIES
for a real time system. Going through the extra expense of maintaining a VPN to
collect HL-7 hospitals as they are being created makes little sense unless these data
can be processed and made available to the analyst also in real time However, the
question remains whether real time is even needed by public health.
It is hard to conceive of any public health need for the more timely collection of data than that provided by CDC’s BioSense program. This program has
implemented the collection of “batched” HL-7 hospital records every 15 minutes.
The total throughput or time delay of the current BioSense processing steps is not
known to the author, but it can safely be estimated to be greater than 15 minutes.
The BioSense data feed is batched, but more timely than systems claiming to be
real time.
Given constraints on time and resources, one could envision two modes of
operation for electronic surveillance systems: one for the routine monitoring of
public health, and the other to examine a specific threat based on case definition.
For routine monitoring purposes, it will be of paramount importance to keep alert
rates to a manageable level. The focused monitoring of perceived threats should
be a rare occurrence, but essential information should be obtainable in sufficient
time to mount an effective response to an emerging crisis.
Summary
The term “real time” as defined by the IEEE’s Computer Society Technical
Committee is not appropriate for use in describing modern automated disease
surveillance systems. The benefits of real-time data collection are only realized
if all other components of a surveillance system satisfy the real-time criteria.
Receiving and processing health indicator data several times an hour should be
more than adequate for public health needs, even during public health emergencies. The use of the term “real time” is often confused by vendors who misuse the
term in an effort to distinguish their product as being better than someone else’s.
Consumers should attempt to understand the actual system characteristics rather
than relaying the misuse of terms by vendors of surveillance systems.
ONE WORLD—ONE HEALTH:
WILDLIFE AND EMERGING DISEASE SURVEILLANCE
William B. Karesh, D.V.M.
Wildlife Conservation Society
Outbreaks of avian influenza, severe acute respiratory syndrome (SARS),
Ebola hemorrhagic fever, bovine spongiform encephalopathy (mad cow disease),
Director,
Field Veterinary Program; Co-Chair, The World Conservation Union (IUCN) Species
Survival Commission’s Veterinary Specialist Group.
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global infectious disease surveillance and detection
and other emerging diseases are surprising the public, disrupting globalization,
resulting in massive economic losses, and jeopardizing business and diplomatic
relations. These diseases, which are able to cross the Darwinian divide between
animals and people, do not depend on humans for their survival and easily live far
from the reaches of most medical interventions. Their competitive advantage in
this regard demands that we revisit basic strategies for disease control, including
the assumptions from the 1950s declaring the chapter on the threat of infectious
diseases closed. Not only was this narrow, urban human health point of view
premature, but it diverted resources away from preparedness for dealing with the
modern-day world of rapid travel and transportation of both goods and people,
higher human population densities, and a growing dependence on intensified
livestock production.
Although many in the developed world would hardly recognize meat not
wrapped in clear plastic, the vast majority of humans still live in a world like
our great-grandparents’, buying their food fresh, salted, or smoked in open-air
markets, or gathering it themselves. For much of the world, there are no systems
of inspections for these markets, and few people have access to good health care,
education on hygiene, common vaccinations, or antibiotics. The global transport
of animals and animal products, which includes hundreds of species of wildlife
(Karesh et al., 2005), also provides safe passage for their bacteria, viruses, fungi,
and even the prion proteins that cause insidious illnesses such as mad cow disease
and chronic wasting disease of deer and elk. Surveillance of infectious diseases
is most useful when it occurs as close to the source as possible, rather than waiting to measure morbidity and mortality in distant lands. This requires a new
approach, one that engages people around the world to work together in earnest
and share findings in a timely manner.
Currently, no government agency is responsible for, or capable of, the surveillance and prevention of the myriad diseases residing around the world. None
are given the responsibility for robustly pursuing the simplest of concepts—the
health of people, animals, plants, and the environment in which we all live are
inextricably linked. The great gains from specialization in the fields of human
health, public health, livestock health, and wildlife health have unfortunately
resulted in academic hubris and reduced communication across disciplines by the
end of the 20th century. Avian influenza serves as the most recent reminder that,
in fact, there is only “one health.” Over the last decade, the Wildlife Conservation Society (WCS) has been working to engage stakeholders in this concept with
projects and a series of symposia utilizing the One World—One Health theme
in Durban in 2003 (Osofsky et al., 2005a, b), New York in 2004, Bangkok and
Beijing in 2005 (Karesh and Cook, 2005), and Brasilia in 2007. The products
of these meetings as well as guidelines for future efforts such as the “Manhattan Principles” are openly available. This one health concept is gaining wide
See
http://www.wcs-ahead.org and http://www.oneworldonehealth.org.
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acceptance and most recently has been endorsed by both the American Medical
Association and the American Veterinary Medical Association. However, putting
words into action presents the biggest challenge, and the world’s agencies and
academies devoted to human and animal health were built to support separate
sectors rather than to facilitate collaboration.
The U.S. Department of Agriculture (USDA) is mandated and funded to
protect the U.S. livestock industry. Radar screens are set to blink when livestock
are threatened. Even the more recent concerns of agroterrorism have not done
enough to support the global outreach necessary to understanding and reducing
diseases overseas before they reach U.S. shores. The wildlife services branch of
USDA traditionally was focused on wildlife control and eradication in order to
protect livestock. It is rapidly trying to remake itself in a modern world that is
recognizing the cultural, ecosystem, and economic value of wildlife itself. But
developing an effective program, building a reputation and trust among the wildlife community, and developing expertise in wildlife surveillance will take a longterm commitment that may or may not be on the horizon (or appropriate, in all
fairness) for a federal agency focused on agricultural production and markets.
The United Nations’ Food and Agriculture Organization’s (FAO’s) priorities
are the production of livestock and crops, with a focus on the urgent needs of
developing countries. Traditionally, few resources were devoted to exploring the
linkages of the health of wild plants and animals with their domesticated cousins.
This has changed since 2005, and a small program was begun in collaboration
with the WCS to coordinate responses and investigations of highly pathogenic
avian influenza virus in wild birds.
The World Organization for Animal Health (OIE) has a volunteer committee
composed of six people who meet for three days per year to address all of the
world’s wildlife-related disease issues. In the past two years, they have formed a
parallel committee to address zoonotic and emerging diseases but the two committees are not linked to one another. The World Health Organization (WHO)
is directed at human health, but until the change in the International Health
Regulations (IHRs) that took effect this year, they could only respond on official
invitation from a country that may or may not know about, or want to reveal, the
presence of a disease. The changes in scope will allow for gathering of information without going through official channels. This could help significantly in
global response time, but the IHRs are still institutionally entrenched in a world
of human disease. The U.S. Centers for Disease Control and Prevention (CDC)
has the responsibility to prevent human diseases in the United States, and extend
their reach around the world, but also only when invited.
No government agency or multilateral organization is charged with uniting
knowledge and efforts that span the diversity of disease threats to people, domestic animals, and wildlife. No one is ensuring that health solutions are based on the
Office
International des Epizooties.
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global infectious disease surveillance and detection
input of expertise from human, domestic animal, and wildlife health professionals
and equally important, communicated across disciplines in terms that effectively
motivate all stakeholders and demonstrate common goals.
Clearly, there is an urgent need for a new health paradigm that not only
integrates the efforts of disparate groups, but possibly more important, balances
their respective influences to prevent both the gaps and the biases that we are now
coming to recognize. The failure to recognize and aggressively address the broad
range of diseases that have no respect for hundreds of years of earnest scientific
classification, places animals and people in great danger. The immediate effects
of the diseases themselves are often the least of the worries. Infectious diseases
of people and animals are drivers of poverty and associated civil unrest, disrupt
“free” ecosystem services such as drinking water and plant pollination, and can
ruin otherwise well-planned and sustainable economic development efforts.
Analyses indicate that more than 60 percent of the over 1,400 infectious diseases currently known to modern medicine are shared between humans and animals (Taylor et al., 2001). From an anthropocentric point of view, most of these
infectious agents are labeled zoonotic, or diseases of animals that infect people.
Anthrax, Rift Valley fever, plague, Lyme disease, and monkeypox are just a few
examples. Receiving less attention is the other group that moves across species
boundaries, the anthropozoonotic diseases. These infectious diseases are typically
found in humans but can, and do, infect animals. Human herpes virus, human
tuberculosis, and human measles are all transmissible to a variety of animal species, with devastating consequences. This traditional division of infectious agents
into two groups is convenient for teaching purposes, but lacks the broader and
critically important concept that these diseases can move back and forth, and
change characteristics in the process. Avian influenza is but one disease that is
teaching the medical world about the need for a more holistic point of view.
The consensus of scientific opinion on the origin of HIV/AIDS links it to
human consumption of nonhuman primates along with their simian immunodeficiency viruses, estimated to have taken place in Africa late in the first half of
the 20th century (Feng et al., 1999). Recent Ebola hemorrhagic fever outbreaks
in humans in Africa have a similar history. The disease was first recognized by
the western world when it appeared in the Democratic Republic of Congo in
1976, around the Ebola River. The virus infects people, gorillas, chimpanzees,
and monkeys (Leroy et al., 2004). It causes severe internal and external hemorrhaging, and can be extremely deadly, killing up to 90 percent of its human victims. Infection spreads quickly, especially via caregivers and by those who flee
to escape the illness. Outbreaks have been recorded in Sudan, Gabon, Republic
of Congo, Democratic Republic of Congo, Côte d’Ivoire, and Uganda. But it is
clear that both people and nonhuman primates suffer equally from the disease.
Outbreaks have caused declines in lowland gorillas and chimpanzees in Gabon
and the Republic of Congo, and chimpanzees in western equatorial Africa. Other
forest animals, such as duikers—small antelopes—and bush pigs may also be
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affected. When subsistence hunters discover a sick or dead animal in the forest,
they view it as good fortune and bring it home to feed their families and trade
with neighbors. The Ebola virus then easily infects those handling the meat, and
a chain of contacts and infections ensues. Each human outbreak in central Africa
during the late 1990s and the first years of this century was traced to humans
handling infected great apes.
The SARS coronavirus has been associated with the trade in small wild carnivores. This disease first appeared to the world in China’s Guangdong Province
in late 2002. People began complaining of high fever, cough, and diarrhea, and
eventually developed severe pneumonia. It was an unknown disease, and it was
very contagious. Within a matter of weeks, it spread via a hotel visitor in Hong
Kong to five continents. By July 2003, WHO had tallied 8,437 cases, with 813
deaths. Mostly because of a lack of understanding of this “new” disease, global
travel and trade were disrupted as fear spread. A coronavirus (a family of viruses
found in many animal species) was finally discovered to be the culprit, and it
was also detected in masked palm civets that were farmed in the region and sold
for human consumption. Later, evidence of the virus was also found in raccoon
dogs, ferrets, and badgers in the wildlife markets, as well as domestic cats living
in the city and a closely related coronavirus in bats commonly sold in the same
markets. Epidemiological studies have concluded that the first human infections
did indeed come through animal contact, though the exact species has not been
definitively identified (Tu et al., 2004). In the weeks after SARS, the Chinese
government responded by closing down live wildlife markets. Within 10 days,
nearly a million animals were confiscated, many brought in from other parts of
the world with their exotic viruses and bacteria, demonstrating that law enforcement can in fact be used to reduce or control the trade in wildlife and wildlife
products. The animals were mixed and matched, exposed to each other’s wastes
and even fed to each other. If a virus or bacteria was hoping to win the big lottery
of jumping among species, going to the markets of Guangdong would be like
buying a million lottery tickets. The profits from the wildlife trade in China pale
in comparison with the estimated U.S. $50 billion global economic costs resulting
from the brief SARS event of 2003 (Newcomb, 2003).
The inadvertent movement of infectious agents due to wildlife handling
and trade, as well as domestic animal movement, is not limited to human pathogens, but also extends to those that can devastate native wildlife, which serve as
biological linchpins for environmental integrity and provide a range of cultural
and quantifiable economic values (Karesh et al., 2005). In 2005, H5N1 Type A
influenza virus was isolated from two mountain hawk eagles illegally imported
from Thailand in airline cabin carry-on baggage to Belgium (OIE, 2004). Tuberculosis originating from domestic cattle has now infected wild herds of bison in
Canada, deer in Michigan and Wisconsin, and Cape buffalo and lions in South
Africa. Surveillance of these wild populations is now needed not only to assess
risk for humans and livestock, but for the wild animals themselves. In one swift
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global infectious disease surveillance and detection
outbreak of rinderpest, a disease originally introduced to Africa by the importation of domestic cattle, more wild buffalo died in Kenya in 1999 than were killed
by illegal poaching during the previous two decades.
Exact quantification of the global wildlife trade is impossible because it
ranges in scale from extremely local to major international routes, and much is
illegal, or through informal channels. WCS figures compiled from a variety of
sources for just the live wildlife trade indicate that each year, roughly 40,000
live primates, 4 million live birds, and 640,000 live reptiles are traded globally
(Karesh et al., 2005). Daily, wild mammals, birds, and reptiles flow through trading centers where they are in contact with humans and dozens of other species
before being shipped to other markets, sold locally, and even freed back into the
wild with new potential pathogens as part of religious customs such as merit
release or because they become unwanted pets. Conservative estimates indicate
that in east and southeast Asia, tens of millions of wild animals are shipped
regionally and from around the world annually for food or use in traditional
medicine. The estimate for trade and local and regional consumption of wild
animal meat in Central Africa alone is more than 1 billion kg per year (Wilkie
and Carpenter, 1999). In Central Africa, estimates of the number of animals consumed by humans annually vary, but a figure of 579 million has been proposed.
Estimates for consumption in the Amazon Basin range from 67 to 164 million kg
annually, comprising, for mammals alone, between 6.4 million and 15.8 million
individuals (Peres, 2000).
Hunters, middle marketers, and consumers make some type of contact with
each animal traded. Additionally, domestic animals and wild scavengers in villages and market areas consume the remnants and wastes from the traded and tobe-traded wildlife. These numbers combined suggest that at least some multiple
of 1 billion direct and indirect contacts among wildlife, humans, and domestic
animals result from the handling of wildlife and the wildlife trade annually.
In addition to the direct health effects of the pathogens on people and
animals, animal-related disease outbreaks have caused hundreds of billions of
dollars of economic damage globally, destabilizing trade, and resulting in devastating effects on human livelihoods. According to studies performed by BioEconomic Research Associates, the rash of emerging or reemerging livestock
disease outbreaks around the world since the mid-1990s—including mad cow
disease, foot-and-mouth disease, avian influenza, swine fever, and other diseases—has been estimated to have cost the world’s economies more than $100
billion. The costs are rarely borne by the same individuals that profit from the
movement of animals and their pathogens. As mentioned earlier, the cost of SARS
alone to the global economy has been put at more than $50 billion (Newcomb,
2003). Wildlife market traders did not bear the costs of the SARS outbreak. The
rodent importer in Texas did not reimburse government agencies for the millions
of dollars spent on the response to monkeypox in the United States. Hundreds of
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millions of public dollars will be spent in attempting to remove tuberculosis and
brucellosis from wildlife populations infected by domestic animals.
In early 2003, FAO reported that more than one-third of all global meat trade
was embargoed as a result of mad cow disease, avian influenza, and other livestock disease outbreaks. The projected growth of industrial livestock production
in developing countries to meet rising global protein demand will increase both
the economic and the food security impacts of future disease outbreaks, and the
global economic impacts do not adequately reflect the local, direct effects.
Preventing and controlling infectious diseases in the modern world requires
a far broader range of expertise than needed for previously isolated systems in
highly developed countries. The challenges seen in controlling avian influenza in
Asia and Africa are just one example of the multispecies disease dilemma. Most
of these diseases threaten local people directly, as well as their livestock and their
livelihoods. They decimate wildlife and undermine ecosystem stability and services, and with modern travel and transport, they can quickly pose a threat to any
nation. Fear, understandably founded on a lack of information, can drive global
responses and economic reactions far beyond the actual cost of disease control.
Currently, it appears that a few people in some of the most remote places on
earth, many from nongovernmental organizations (NGOs) and many working at
local government levels but unlinked to larger formal networks, are working to
fill the intersectorial gaps in health care as they relate to emerging diseases and
wildlife. WCS’s global health programs are an example of a private-sector effort
linked to governmental and multilateral agencies that bring together stakeholders,
from civil society and a variety of government sectors, to develop surveillance
and information-sharing networks. The work is directed where rare infectious
diseases are least understood and local institutions have the fewest capabilities to
effect prevention and control. Our staff and partners routinely encounter diseases
such as anthrax, avian influenza, monkeypox, and Ebola where they naturally
occur. We build local capacity to conduct surveillance and reporting networks at
very low costs. When attention was being misdirected at wild birds in efforts to
control the current avian influenza outbreaks in Southeast and East Asia, these
new, but informally recognized participants in health discussions, were the first
to point out that migratory routes and seasonal timings did not correspond with
the regional spread of the disease as posited by articles in prestigious scientific
journals—it was the largely uncontrolled movements of domestic birds that were
spreading this disease, not wildlife. Control efforts would be needlessly misdirected without this simple input to decision makers.
Building bridges across disciplines to solve health problems can have simple
but significant synergistic effects. Studies in South America have shown that,
contrary to common opinion, livestock diseases pose more threats to wildlife
than the other way around. In much of the world, reducing disease in domestic
animals would benefit several industries, improve human health and livelihoods,
and help protect wild animals from livestock and other domestic animal diseases.
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global infectious disease surveillance and detection
In Central Africa, gorillas and chimpanzees have little to no immunity to common
human diseases. Local people and tourists threaten wild populations with these
illnesses, which could be simply avoided by implementation of good preventive health programs and practices in villages. People and wildlife both benefit.
WCS’s work with Ebola hemorrhagic fever in gorillas and chimpanzees has
shown that when investments are made for working not just in the cities but in the
forests, natural resource managers can help to detect the presence of the disease
in wildlife months before the first human cases—providing the lead time to warn
villagers not to hunt or handle the animals that are the source of infection.
Over the past two years, the WCS network of local villagers and hunters,
park managers and staff, government public health officials, and regional laboratories has detected outbreaks of Ebola in great apes and notified local communities. For the first time, known human outbreaks resulting from the disease
in animals have not occurred. This broader, one-health approach is much more
effective and inexpensive than the traditional “quarantine and stamping out”
efforts after an outbreak has begun. A set of guiding concepts on these themes,
called the Manhattan Principles, was developed by human and animal health
specialists in conjunction with wildlife conservation professionals.
Another large-scale example of a worldwide private–public collaborative
effort is the Global Avian Influenza Network for Surveillance (GAINS) of wild
birds. The U.S. Agency for International Development (USAID), CDC, and
USDA are providing support to WCS to develop and administer the wild bird
GAINS program. GAINS is a smart and targeted investment in the U.S. government’s fight against avian influenza, because wild birds around the world can
serve as sentinels for the early detection of the virus’s presence.
Awareness of and interest in the GAINS program continues to grow. Working relationships with local institutions are being built in more than 28 countries,
with many more anticipated. This network of partners builds a “window on the
world” and has helped GAINS bring timely and pertinent information that will
help combat the threats posed by highly pathogenic avian influenza to both
humans and animals.
The GAINS program has made significant progress in its global implementation since receiving start-up funding in summer 2006. Collaborations have
been established between WCS and U.S.-based and international organizations—
including governments, NGOs, and universities—to work together to improve our
understanding of the dynamics of avian influenza, and to evaluate disease risks
for people, biodiversity, and domestic poultry. WCS staff have been in active discussions with colleagues from USAID, CDC, Department of Homeland Security
(DHS), Department of Defense (DoD), U.S. Geological Survey (USGS), USDA,
National Institutes of Health (NIH), Department of State (DoS), WHO, FAO, as
well as university and private-sector experts to address integrated approaches to
See
http://www.oneworldonehealth.org.
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global disease information management issues. Together with FAO, WCS has
conducted training efforts in Eastern Europe, Latin America, and the Caribbean,
and a recent agreement with USDA will expand training and bird monitoring in
Latin America. WCS is providing technical expertise related to health monitoring
of wild birds and capacity-building activities around the world.
GAINS fieldwork also enables the isolation of new viral strains, which can
contribute to vaccine development and help guide preparedness in the United
States and abroad. One of the primary purposes of GAINS is to share international disease information through an interactive, publicly accessible web-based
database, a working prototype of which has already been made available on the
GAINS website. The database is starting to map sample collection sites, flyways, and results of biological surveillance. The goal is to alert decision makers
about disease occurrence rather than waiting for traditional scientific journal
publication.
From Afghanistan to Zimbabwe, field surveillance for avian influenza is currently underway. Our work in Mongolia illustrates the field methodology being
used in many sites. Mongolia has been a hot spot for avian influenza outbreaks
in the past two years and is a country where wild birds appear to be of particular
importance to the ecology of the disease. Last year WCS staff collected more
than 3,500 samples at 42 sites across the country. WCS staff collected an H5N1
strain of avian influenza virus from wild birds that have been selected by WHO
to be used in human pandemic vaccine development and testing. Working with
WCS staff in Mongolia, USGS scientists fitted whooper swans from the region
with satellite transmitters (supplied by FAO) in early August, and some have
been tracked to China, Korea, and Russia. These types of data may shed light on
possible viral transmission routes across Asia.
The early successes with the Wild Bird GAINS program has led to expansion of the program to a broader range of infectious diseases and species. Named
the Wildlife Global Animal Information Network for Surveillance (Wildlife
GAINS), the effort is designed to establish a comprehensive, worldwide wildlife health surveillance system to enhance preparedness for and awareness of
emerging infectious diseases. This nongovernmentally managed network would
connect a wide variety of U.S. government agency partners, multilateral agency
partners, conservation organizations, veterinary and medical schools, and other
national and international partners. The unique strengths and capacities that
NGOs such as the Wildlife Conservation Society have to work with developing
country governments and scientific colleagues must be harnessed to develop
and enhance surveillance mechanisms that are of great importance to human
security and well-being.
Workers in the fields of health and global governance need to find ways to
focus skills and expand resources to make the entire world safer from infectious
See
http://www.gains.org.
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global infectious disease surveillance and detection
disease. The financial costs of disease outbreaks are currently borne by the global
economy and will only serve to slow economic development where it is needed
the most. There is an obvious need to break down barriers among health disciplines to prevent any one of them from restricting funding to their area of interest, and there is an urgent need to build bridges among the government agencies
and the privately operating individuals and organizations around the world that
now take responsibility with only scarce resources. Immediately, before the next
global pandemic, trade in wildlife needs to be dramatically reduced and, like the
livestock industry, properly regulated. Finally, global health will not be achieved
without a philosophical shift from the “expert dictates” paradigm inherent to
both science and medicine, to a broader, multistakeholder approach, based on the
understanding that there is only “one world and one health.”
AGRICULTURAL BIOSECURITY: THREATS
AND IMPACTS FOR PLANT PATHOGENS
Jacqueline Fletcher, Ph.D.10
Oklahoma State University
James P. Stack, Ph.D.11
Kansas State University
Plant Vulnerability to Disease
Plant resources in the United States, including crops, rangelands, and forests,
are vulnerable to endemic, introduced, and emerging pathogens (American Phytopathological Society Public Policy Board, 2002; Casagrande, 2000; Madden
and Wheelis, 2003; Wheelis et al., 2002; Whitby, 2002). An estimated 65 percent
of U.S. crop losses, valued at $137 billion, are attributed to introduced pathogens
annually (Pimentel et al., 2000). Increasing globalization and international trade
activities create a strong likelihood that many other exotic plant pathogens will
arrive in the United States in the coming years.
The vulnerabilities of U.S. agricultural production to emerging diseases
result from a number of factors. Huge acreages are planted with grains and forage crops, or are covered with grasslands or forests. Because it is impossible to
regularly or frequently monitor such extensive areas for disease symptoms, long
periods are likely to pass between the time a pathogen is introduced and when
it is detected. A second source of vulnerability is the lack of genetic diversity
in our plant resources; most of our nation’s production is centered on just three
10 National Institute for Microbial Forensics & Food and Agricultural Biosecurity, and Department
of Entomology and Plant Pathology.
11 Biosecurity Research Institute.
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crops: wheat, corn, and soybeans. Within these and other crop species, certain
genotypes conferring attributes important for yield and quality are preferentially
grown over large areas, increasing the chance that a pathogen detrimental to that
cultivar will have serious impact.
More than 50,000 plant diseases occur in the United States (Madden, 2001;
Madden and Wheelis, 2003), caused by a variety of pathogens, including fungi,
viruses, viroids, bacteria, nematodes, and parasitic plants. These organisms are
disseminated by various means, including wind, water, agricultural equipment,
seeds or propagative plant parts, insect vectors, animals, or farm workers. For any
given region and crop, producers may deal with up to 10 to 15 serious plant diseases that can cause severe economic repercussions (Pinstrup-Andersen, 2001).
About 65 percent of U.S. crop losses are due to nonindigenous (introduced)
pathogens, amounting to an estimated cost of $137 billion annually (Pimentel et
al., 2000). All crop pests (pathogens, arthropods, and weeds) combined caused
preharvest losses of 42 percent and an additional 10 percent loss after harvest.
Of these, 13 percent were due to plant pathogens, 15 percent to arthropods, and
13 percent to weeds. Worldwide, losses for the eight major crops that comprise
half of the global croplands were estimated at $300 billion in 1988–1990 (Oerke
et al., 1994).
A number of pathogens that occur elsewhere in the world are of significant
concern to U.S. plant production, should they arrive. Most past introductions of
plant pathogens to the United States have been unintentional. Many pathogens
not yet in the United States would pose significant threats to our current crops.
Because eradication of plant pathogens is rarely physically or financially feasible,
the only effective approach is to manage the disease so that its impact falls below
an economic threshold—the point at which management costs exceed the profits
associated with production.
The use of microbes, such as the anthrax bacterium, against human targets is a highly visible act with immediate consequences. Directing pathogens
toward agricultural targets may be less visible, and effects may not be apparent
for some time. However, such actions, which effectively target the nation’s food
supply—from its production in the field to its place on the plate—may have
serious and long-range impacts (Adam, 2006). Many plant pathogens can be
acquired readily by those wanting to use them intentionally for purposes of harm.
Furthermore, they may be attractive agents for nefarious applications because
they can be handled, grown, transported, and disseminated with little technical
expertise or equipment, and pose little or no danger to the health of the handler.
The Institute of Medicine (IOM)/National Research Council (NRC) Committee
on Advances in Technology and the Prevention of Their Application to Next
Generation Biowarfare Threats recently concluded (2006) that the increasing
accessibility and simplicity of technological information related to pathogens
increase the likelihood that rogue states or individuals may use such knowledge
in a criminal manner.
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History of Biological Warfare
Biological warfare has been targeted to agricultural systems in the past.
Around the world, state-sponsored programs supported research to enhance the
suitability of microorganisms for use as weapons (Casagrande, 2000; CIDRAP,
2003; Madden and Wheelis, 2003; Wheelis et al., 2002; Whitby, 2002). Before the
Biological and Toxin Weapons Convention outlawed state programs on biological
weapons in 1972 (IOM/NRC, 2006), U.S. research programs had focused on the
pathogens causing anthrax, foot-and-mouth disease, and rice blast. Germany had
bioweapons programs during World Wars I and II, the former Soviet Union during
World War II and the Cold War, and Iraq at the time of the Iran–Iraq War. Islamic
militants in Afghanistan were involved in weaponization of the fungus Puccinia
graminis, causal agent of wheat rust. Canada, France, Japan, and the United Kingdom also considered the use of bioweapons against agricultural targets.
Despite knowledge of such research activity in multiple countries, no
reports of the deliberate use of pathogens against crops or other plants have been
published. Yet, indicators of increasing likelihood of such use point to the need
for preparedness. The United States must develop the capabilities and knowledge to ensure the safety and security of our food at all levels, and at all points
of production—the distribution pathway from farmers’ fields to the consumer.
Rapid action is critical if we are to have these capabilities in place before they
are needed for a devastating incident.
Impacts of Plant Diseases
Past incidences of the impacts of crop diseases on human health and society
may be helpful in illustrating the potential damage of plant pathogens. The Irish
potato famine (1845–1846), caused by the plant pathogen Phytophthora infestans, led to extensive famine and resulted in the deaths of a million people and the
emigration of another 1.5 million Irish, many to the United States (Large, 1940;
Carefoot and Sprott, 1969; Schumann, 1991). During the same timeframe, the
severe impact of a rust fungus on coffee production in Ceylon (now Sri Lanka),
the prime supplier of coffee to Great Britain, forced much of British society to
turn to tea as their primary hot beverage (Large, 1940; Schumann, 1991). Weather
conditions in both the United States and Europe during World War I were favorable for the development of plant diseases in wheat and potatoes, crops essential
for nourishing the troops on both continents. The critical food shortages that
ensued were factors in the movement and strength of the troops and changed the
course of the war. Brown spot of rice contributed to the Great Bengal Famine
of 1943, and in the United States, a 1970 epidemic of corn leaf blight destroyed
about 20 percent of the $1 billion crop (Rogers et al., 1999).
U.S. agricultural infrastructure is strong, diverse, and resilient. Temporary
unavailability or elimination of a certain food product because of plant disease
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is unlikely to result in significant nutritional hardship for Americans. The same
cannot be said for all countries, however; a serious rice disease in Southeast
Asia, for example, could lead to malnutrition and hunger, destabilizing social
infrastructures in affected areas.
Deliberate introductions of plant pathogens to crops and other plant resources
in the United States could have serious non-nutritional impacts (Budowle et al.,
2005a, b; Murch et al., 2003; Fletcher et al., 2006). Likely impacts of crop diseases in the United States include losses in the quality and quantity of our food,
increases in consumer food prices, costs of growing crops that are less desirable,
and costs of management strategies, both short term (crop destruction, pesticide
application, or redirecting use of the crop) and long term (development of resistant varieties) (Casagrande, 2000; Madden and Wheelis, 2003; Wheelis et al.,
2002; Whitby, 2001, 2002). Several plant pathogens can also infect humans; these
are primarily opportunistic pathogens of greatest concern to immunocompromised patients, the very young, or the old. Some plant pathogenic fungi produce
mycotoxins that can pose important health risks for humans, and other species
produce spores that are allergenic. There also can be important indirect impacts
on human nutrition, as well as on the agricultural community, if plant products
used for livestock feed are lost.
The most significant impacts of deliberate plant pathogen introductions,
however, are likely to be economic in nature. Imposition of quarantines and
embargoes on U.S. agricultural products not only affect producers, but have
downstream effects on the commercial enterprises that harvest, store, package,
transport, add value, and market the commodity. Perhaps more importantly, there
could be a loss of trading partners and markets worldwide. Furthermore, knowledge of intentional targeting of the food supply by those intending harm would
lead to a loss of public trust in our food and in the ability of government to ensure
its safety. Ultimately, rural communities that rely on agricultural production may
be destabilized and grower livelihoods threatened.
At the other end of the food system continuum, there has been an alarming
rise in the incidence of foodborne illnesses due to microbial contamination of
fruits and vegetables. A recent survey by the U.S. Food and Drug Administration
(FDA) of samples from major distributors showed that 1.6 percent of domestic
produce was contaminated with human pathogens (FDA, 2001). Recent incidents
of contamination of leafy greens and peanut butter with the human pathogens
E. coli O157:H7 and Salmonella spp. demonstrate the devastating impact that may
result from the introduction of microbes into fresh food plants. Today’s mass food
production operations and national distribution systems have caused a significant
increase in the scope of such foodborne illnesses (Maslanka et al., 2002). Once
primarily local events, with local response, food contamination incidents are now
far more widespread. In the fall 2006 E. coli outbreaks, 205 victims in 26 states
suffered severe disease and 3 died. As a result, consumers changed their buying
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habits, producers of the affected crops suffered significant economic losses, and
downstream enterprises were negatively impacted (FDA, 2007).
High-Consequence Plant Pathogens and Diseases
In 2004, the U.S. Department of Agriculture (USDA) Animal and Plant
Health Inspection Service (APHIS), as designated in 7 C.F.R. Part 331 of the
Agricultural Bioterrorism Protection Act of 2002, first established a list of
plant pathogens of high consequence to be designated as Select Agents 12 (Table
1-3). Although this list is similar in nature to the Select Agent lists for human
and zoonotic diseases, there is one important difference. Plant pathogen Select
Agents are, at the time of their placement on the list, exotic microbes not endemic
or established in the United States. This contrasts with the policy of listing
indigenous human and animal pathogens on their respective lists. The fact that,
by definition, plant Select Agents are not indigenous within the United States
necessitates the imposition of strict regulations, registrations, restrictions, and
security13 on any research or possession of these microbes.
Originally consisting of 10 plant pathogens, the recent removal of 2 pathogens (Plum pox virus and Phakopsora pachyrhizi, the causal agent of soybean
rust) after their arrival and establishment in the United States has left the list with
8 agents. A mandated biannual review and possible revision of the plant Select
Agent list is underway at the time of this writing.
Citrus Canker: A Recent Example of Significant Disease Impact
Florida produces about 80 percent of the citrus grown in the United States,
and most of the state’s fruit is processed for juice. The industry is worth about
$1.4 billion per year. Although Xanthomonas axopogonis pv. citri, the bacterium
that causes the devastating citrus canker disease, is not on the Select Agent list,
it has occurred in Florida citrus-growing areas several times since the turn of the
century, each time causing brown, necrotic, raised scars or cankers on leaves,
stems, and fruit.
Canker is a quarantine disease; fruit from affected areas cannot be moved
across state lines or sold in the world market. Because the disease was not considered established in the United States, an eradication strategy has been in place
for many years. This approach was successful in Florida in the early 1900s and
again in the 1980s. APHIS and the Florida Department of Agriculture and Consumer Sciences adopted that same strategy for the most recent outbreak, which
was first detected in 1995. However, the latter outbreak presented new challenges.
12 See http://www.apsnet.org/online/feature/BioSecurity/ and http://www.cdc.gov/od/sap/docs/salist.pdf.
13 See http://www.aphis.usda.gov/programs/ag_selectagent/index.html.
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TABLE 1-3 U.S. Select Agent List for Plants
• Liberobacter africanus
• Liberobacter asiaticus
• Ralstonia solanacearum R3 Bv2
• Xanthomonas oryzae pv. oryzicola
• Xylella fastidiosa
• Peronosclerospora philippinensis
• Sclerophthora rayssiae var zeae
• Synchytrium endobioticum
• *Pathogens not yet established in the United States
• Pathogens recently removed from Select Agent list
• Phakopsora pachyrhizi*
• Plum pox virus
Citrus greening (African)
Citrus greening (Asian)
Potato bacterial wilt
Rice bacterial leaf streak
Citrus variegated chlorosis bacteria
Philippine downy mildew of corn
Brown stripe downy mildew of corn
Potato wart fungus
Soybean rust
Pox of stone fruits
*Also spelled pachyrhizae.
SOURCE: Fletcher (2006).
First, the initial eradication guidelines called for elimination of the diseased tree,
plus any citrus trees within a 125-foot radius of the symptomatic plant. Although
this policy was not popular, it was relatively well accepted. However, in the late
1990s, these measures failed to prevent disease spread. Further research led to
an eradication strategy modification requiring the elimination of all citrus trees
within a 1,900-foot radius of any infected tree. Complicating matters was the
fact that the 1995 outbreak was not confined to commercial groves. It also was
widespread in residential areas of Miami where landowners objected, some filing
lawsuits to stop the eradication campaign. While the legal issues were debated
in court, the disease continued to spread. The eradication plan eventually was
upheld by the courts and the program was reinstated (Gottwald et al., 2002);
overall, $200 million was spent and more than 10 million trees were destroyed
(Brown, 2001). However, the occurrence of several hurricanes in Florida in 2005
spread the pathogen far beyond its previous locations and eliminated hope of
eradication. In 2006, USDA APHIS revised its approach to focus on managing
the disease.
Arrival of Two Plant Pathogen Select Agents
Two plant pathogens on the Select Agent list have arrived in the United
States in the past two years. Were we ready for them?
Soybean rust, caused by the fungus Phakopsora pachyrhizi, affects a major
U.S. crop that is grown over 75 million acres and is worth more than $18 billion
a year (USDA-ERS, 2007). In areas where the rust is endemic, such as Asia and
South America, yield losses commonly range from 10 to 30 percent, but can
be much higher. U.S. producers, who grow 74 million acres of soybeans/year
(accounting for about $15.7 billion), feared that the arrival of the fungus would
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severely impact the industry. U.S. epidemiologists had been monitoring the global
movement of the pathogen for several years in an effort to provide warning for
its inevitable arrival to U.S. territory. The disease was first detected in the United
States in fall 2004 (Schneider et al., 2005). The first diagnosis, in Louisiana, was
quickly followed by detection in several other states, but because the disease
arrived after the soybean crop had been harvested there was no impact on production that year. Indeed, the 2005 and 2006 growing seasons were characterized by
weather patterns unsupportive of P. pachyrhizae infection and disease, so actual
losses have not yet approached the damaging levels anticipated. This has been
good news for producers, but ironically, has prompted a sense of security that
may be unfounded in future years when conditions may be more conducive to
pathogen establishment.
Regardless of the seriousness of soybean rust to date, the fact that the pathogen was distributed widely—again likely by hurricane winds in 2005 (Stokstad,
2004)—and the fact that it establishes easily and overwinters in a variety of hosts,
including an extremely invasive vine called kudzu, means it is now considered
to be established in the United States (Pivonia and Yang, 2004). Since the plant
Select Agent list contains only exotic pathogens, APHIS removed P. pachyrhizae
from the list in 2006. “Delisting” has several implications, both positive and
negative. Federally mandated response to, and management of, a Select Agent is
extremely expensive for both federal and state agencies. In addition, the extensive
and expensive policies, certifications, permits, and containment requirements for
scientific research on Select Agents are significant disincentives for plant pathologists to work on the pathogens of greatest concern. The removal of P. pachyrhizi
from the list will facilitate research, but it also changes the responsibility of
federal agencies in their response to the disease.
The bacterial pathogen Liberobacter asiaticus, a Select Agent that causes a
disease officially known as “huanglongbing,” or citrus greening, was discovered
in Florida in fall 2005 (APHIS, 2007). Its possible arrival had been a concern for
at least two years, after it was learned that its insect vector—the citrus-feeding
Asian citrus psyllid, Diaphorina citri—had arrived in the state and would be
likely to spread the pathogen quickly should it arrive. Like citrus canker, huang
longbing was more damaging than anticipated because it, too, occurred during
the 2005 hurricane season, when extensive wind dissemination of inoculative
vector insects quickly resulted in the pathogen becoming endemic in the state.
The question of whether L. asiaticus will or should be removed from the Select
Agent list is complicated by the fact that, although the bacterium may be established in Florida, it is not yet known to occur in citrus-growing regions of Texas,
California, and other southern states.
Components of a Strong Plant Biosecurity Strategy
A robust system of preparedness for threatening exotic or emerging plant
diseases will require the following elements:
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• Early detection and diagnostic systems
• Epidemiological models for predicting pathogen spread
• Reasonable but effective strategies and policies for crop biosecurity
• Distributed physical and administrative infrastructure
• A national system for strategic planning and response coordination
• Microbial forensic capability: validated technology and investigative
capability
Before 2001, our national capability in plant disease diagnostics and recovery
was fragmented, poorly supported. and of limited effectiveness due to declining
resources. In the past five years, however, significant improvements in infrastructure will help to ensure preparedness for a serious plant pathogen introduction
event. In 2004, President George Bush issued Homeland Security Presidential
Directive 9 (HSPD-9), which mandated a National Plant Disease Recovery System (NPDRS). The USDA Office of Pest Management Policy, assigned by the
Secretary of Agriculture to develop the NPDRS, has worked to develop specific
Recovery Plans for each of the Select Agents as well as for several other plant
diseases of high consequence. Their approach, which is well underway at this
time, has been to bring key experts from federal agencies, private industry, and
academia together for the development of each plan, and to partner with the
American Phytopathological Society (a 5,000-member professional society dedicated to plant health) to ensure broad-based community input and participation.
Another important initiative has been the establishment—by USDA-Cooperative
State Research, Education, and Extension Service (CSREES)—of the National
Plant Diagnostic Network, an interconnected system of diagnostic laboratories
affiliated with land grant universities and/or state departments of agriculture in
each state (Stack et al., 2006).
At this writing, it is clear that many individual improvements and initiatives
have enhanced our nation’s ability to prevent and prepare for emerging plant
diseases and pathogens. Individual efforts within federal agencies concerned
with agricultural biosecurity (USDA APHIS, CSREES, and Agricultural Research
Service [ARS]; Departments of Defense and Homeland Security; Environmental
Protection Agency; and Food and Drug Administration) also have enhanced our
preparedness. However, significant gaps remain.
Preparedness for events involving intentional introductions of plant pathogens, whether for purposes of bioterror or biocrime, must include a strong
national security plan that encompasses microbial forensics and criminal attribution. However, U.S. crop producers, consultants, and agricultural scientists,
unaccustomed to considering the possibility of intentional pathogen introduction,
traditionally focus disease management strategies on prevention, rapid eradication, or long-term management. A recent study (Fletcher et al., 2006) assessed
currently available information, technologies, and resources, developed for peaceful applications, which can be utilized for plant pathogen forensics. The authors
also prioritized activities and resource expenditures needed to enhance our plant
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pathogen forensics capabilities. Strategies needed for a comprehensive national
microbial forensic capability, to determine the source of the pathogen and provide evidence for attribution, include (1) assuring high stringency of investigative technologies (validation, confidence, statistical significance, consistency);
(2) tracing pathogen origin and movement; (3) identifying the timing and site
of initial introduction; (4) identifying the perpetrators; (5) collecting evidence
for criminal attribution; and (6) forming linkages with the law enforcement and
security communities.
One of the most pressing gaps, because it impacts all the others, is the
need for greater communication, cooperation, and coordination between and
among federal agencies, academic institutions, and industry. Each of the agencies and entities contributing to national agricultural security has a unique mission and specific goals for which it is accountable to its stakeholders, and each
is responsible for different elements of an outbreak response. Currently, there is
no single entity, such as the Centers for Disease Control and Prevention (CDC)
or a national center, to ensure strategic planning for future preparedness and the
most effective and efficient response to a plant pathogen emergency. To be effective, this coordinating function should be established at a level above individual
agencies. The coordinating entity would not duplicate or unnecessarily overlap
the diverse elements of a robust national biosecurity plan because most of these
responsibilities are charged to existing components of government. It would focus
on strategic planning, program reviews, and coordination of activities among
federal agencies, private entities, and academia; prioritization of research and
education needs for allocation of limited resources; database and pathogen collections; and coordination of public relations.
Conclusions
Our nation’s agricultural industry is strong and our food supply is among
the safest in the world, but vulnerabilities do exist. Recent initiatives in various
branches of government, academia, and industry have enhanced the security of
our plant resources, but gaps and needs remain. Fortunately, the actions needed
to sustain and protect our plant resources from intentional pathogen introduction,
and to recover from deliberate plant disease outbreaks, will also enhance the effectiveness and productivity of normal U.S. agricultural enterprises. For example, in
addition to the threat of intentional introductions of exotic plant pathogens and
pests, new pathogen species or races emerge naturally. Globalization of markets,
unprecedented international travel, and changes in climate from various causes
all contribute to an increased likelihood that pathogens will move across national
borders and employ adaptive strategies in response to exposure to new environments. Let us use the opportunities provided by these challenges to strengthen our
agricultural production systems, and ensure that our nation continues to lead the
world in providing food that is abundant, reliable, nutritious and safe.
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SURVEILLANCE STRATEGIES
PLANT BIOSECURITY INFRASTRUCTURE FOR
DISEASE SURVEILLANCE AND DIAGNOSTICS
James P. Stack, Ph.D.14
Kansas State University
Jacqueline Fletcher, Ph.D.15
Oklahoma State University
Introduction
The vital role of plants in society is not well understood by the general population or by most policy makers. Healthy plant systems are a prerequisite to the
health and welfare of human and animal systems, and are essential to the economies of developed nations. Human, animal, and plant systems are intricately
linked; the intersection of these three systems forms the basis of our economy,
our culture, and our standard of living. The emerging one-medicine concept of
holistic health that encompasses animal and human systems is rational and obvious when we consider the value inherent in these systems and the impact that
zoonotic diseases have had over the past 50 years (Dudley, 2004; Karesh and
Cook, 2005; Potter, 2004). However, we must expand that holistic one-medicine
concept to include plant systems.
When we assess value within our primary living systems, it is appropriate
that human systems have the most value, animal systems second, and plant systems third. However, plant systems are the foundation of all three. Plants generate
the oxygen we breathe. They are the food we consume directly and the feed we
provide to the animals we consume. They are the fibers that clothe us and the
timber that shelters us, and they are becoming the fuels that power the technologies associated with our high standard of living. They stabilize our ecosystems
and beautify our landscapes. Plants have great aesthetic value and great economic
value. Healthy plant systems are vital to our national economy and consequently
to our national security. The stability of societies and economies depends on the
health of plant systems (Diamond, 2005). Therefore, we must protect our natural
and agricultural plant systems to ensure the sustainability of our food production
systems and ultimately our society.
A Biosecurity Framework
A national strategy for plant biosecurity must be comprehensive with respect
to science and policy and must address issues of infrastructure, technology, and
14 Biosecurity
Research Institute.
Institute for Microbial Forensics & Food and Agricultural Biosecurity, and Department
of Entomology and Plant Pathology.
15 National
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education. One conceptual approach to the development of plant biosecurity infrastructure is based on a simple outbreak model. In its simplest form, this model
includes the following components: the source of the outbreak agent; the introduction of the agent into some new environment; the detection of that agent at some
point after the introduction event; the accurate diagnosis of the new agent at some
point after the detection event; the response to the outbreak; and the resolution of
the outbreak. Each component requires a unique strategy for preparedness: potential introductions require a prevention strategy; detection requires a surveillance
strategy; diagnosis requires a technology strategy; response requires a communications and mitigation strategy; and resolution requires a recovery strategy.
Prevention
The U.S. Departments of Agriculture (USDA) and Homeland Security (DHS)
share responsibility for preventing the introduction of new plant pathogens and
insect pests that threaten our plant systems. This is accomplished through the
activities and programs of Customs and Border Protection (CBP) and USDA’s
Animal and Plant Health Inspection Service Plant Protection and Quarantine
(USDA-APHIS-PPQ). Due to the extremely large and increasing volume of
imports of plants and plant products, port and border inspections can never be 100
percent effective in preventing the accidental or intentional introduction of new
agents. The increase in Internet-based commerce further adds to this challenge
by providing a means to circumvent the inspection and quarantine process associated with interstate and international trade. Consequently, we must anticipate
the introduction of agents that threaten our plant systems, whether accidental due
to global trade, intentional due to terrorism or crime, or natural due to weather
events (e.g., hurricanes).
A prevention strategy should include the capability to intercept those agents
with a high probability of introduction and establishment. Several lists of highconsequence pathogens and pests have been generated by government agencies
and scientific societies. One such list identified more than 500 plant pathogens
and nematodes and over 700 insects and mites that pose threats to U.S. plant
systems (Huber, 2002). We lack the resources necessary to develop specific plans
for over 1,200 organisms. Because there is no defining set of characteristics
to determine which threat agent will become established and cause significant
damage, a prioritization process is needed to identify those high consequence
agents with the greatest potential to cause persistent, wide-scale damage such
that specific interception protocols are required. For example, if a new race of a
pathogen emerged with the potential to destroy over 50 percent of the U.S. wheat
crop, its characteristics indicate that the pathogen will establish and spread, there
are no effective management tools, and pathways for pathogen introduction exist,
then a comprehensive preparedness, response, and recovery strategy should be
developed for that specific pathogen.
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Surveillance, Detection, and Diagnosis
An Institute of Medicine study identified six critical elements necessary to
a food safety system (IOM, 1998). These same six elements would provide the
framework for biodefense against threats to national food security (King, 1999).
Among those elements was a comprehensive surveillance and monitoring system. This element is as important for plant-based systems as it is for human and
animal systems.
For the purposes of this paper, surveillance is the process of searching,
detection is the process of finding, and diagnosis is the process of determining
and/or verifying what is found. The National Plant Diagnostic Network (NPDN)
was established by USDA in 2002 to provide the necessary critical infrastructure
to facilitate early detection and rapid diagnosis of disease and pest outbreaks in
natural and agricultural plant systems (Stack et al., 2006). This is accomplished
through the primary mission areas of building infrastructure for diagnostics and
communications and through training and education programs that target first
detectors and diagnosticians.
Surveillance and detection We should assume that introductions will continue to occur as a result of global trade and the increasing threats of intentional
introductions due to bioterrorism and biocrime. If the projections for increased
trade and climate change are accurate, it is quite possible that the frequency and
severity of introductions will increase.
Our current surveillance and detection systems vary significantly according
to plant system, target pathogen or pest, and geographic region. Funding for
surveillance of plant systems is most often allocated for specific target agents;
consequently, those programs are executed only in areas at risk. Because of limited funding, general surveillance at the field level is minimal. For some plant
systems, industry has implemented very effective surveillance programs, and the
data are provided to APHIS. Mechanisms to share data are being explored.
Among the major limitations to an effective surveillance system is not having enough trained personnel in the field. Unlike human and animal systems, in
which doctors and veterinarians are distributed throughout rural and agricultural
areas, few plant doctors with diagnostic expertise operate at the local level with
plant-based systems. NPDN, in collaboration with Cooperative State Research,
Education, and Extension Service (CSREES), APHIS, the Extension Disaster
Education Network, and the Regional Integrated Pest Management (IPM) Centers, has developed a training and education program targeting first detectors at
the local level. Its registry of trained first detectors may serve as a resource for
outbreak management.
Diagnosis NPDN was established to provide a triage system for the rapid
and accurate diagnosis of introduced plant pathogens and insect pests. Because
of a decline in national and local support for plant diagnostics over many years,
state labs varied tremendously in diagnostic infrastructure and experience. With
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funding from USDA, NPDN has rebuilt and enhanced much of that infrastructure
and implemented programs to train diagnosticians in the latest diagnostic technologies (Stack et al., 2006).
Morse identified three elements for an effective early warning system; clinical recognition, epidemiological investigation capability, and laboratory capacity
(Morse, 2002). NPDN has become an integral component for early warning and
NPDN labs provide surge diagnostic support during outbreaks.
NPDN has created a national database for the diagnostic data collected at the
network labs. An NPDN epidemiology group is developing data analysis tools
that include syndromic analysis. Many of the issues and challenges associated
with syndromic surveillance in human systems (Stoto, 2005; Stoto et al., 2004)
also apply to plant systems. Because there are many natural introductions in plant
systems, syndromic surveillance might prove to be a useful approach. Coordination and communication among all the disciplines will be important.
Response
Response to plant disease outbreaks resulting from new pathogen introductions is a responsibility of USDA APHIS. For most introductions, APHIS provides the leadership for a coordinated response that often includes APHIS-led
rapid deployment teams, state departments of agriculture, industry, and in some
cases, land grant university diagnostic labs. An elaborate structure exists within
APHIS for the development of response plans to high-consequence pathogens
and pests.
NPDN, in partnership with APHIS and state departments of agriculture, has
developed and implemented a training exercise program to facilitate preparedness for outbreak response. All 50 states have participated in at least one exercise
involving local, state, and federal governments, as well as state, regional, and
national diagnostic labs. The exercise scenario makes clear the roles and responsibilities of all participants. After the exercise scenario, action reports are analyzed
to identify areas in need of improvement.
Recovery (A Superficial Treatment)
Recovery, which follows response, is the strategy by which to return a system
to the preevent mean or to a new, but stable, mean. An effective recovery strategy
will be comprehensive in nature and include short-term plans that address the
transition from response to the new system mean, while long-term plans will need
to address prevention and recovery from subsequent introductions. The scope
of recovery plans vary as a function of the scale of the outbreak and the ripple
effects throughout the national and global economies. While response revolves
around outbreak delineation, containment, eradication, and management, recovery is focused on local and system-level issues, including ecological impacts,
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production shortfalls, effects on transportation systems, impacts on trade agreements, market reentry strategies, and replacement markets or systems.
Mandated by Homeland Security Presidential Directive 9 (HSPD-9), the
National Plant Disease Recovery System (NPDRS) was established within the
USDA Agricultural Research Service. NPDRS has involved other federal agencies (e.g., APHIS and CSREES), state departments of agriculture, scientific
societies, and universities in the development of national response plans for the
Select Agents and other high-consequence pathogens.
Among the challenges of an effective plant disease recovery strategy will
be to find cost-effective solutions for low profit margin systems. Deriving a
cost–benefit premium that achieves sustainable plant systems without significantly raising the percentage of the U.S. income spent on food or without causing
irreversible ecosystem damage will be challenging. One goal for such a strategy would be establishing mechanisms for national cooperation among public
and private sectors and international cooperation that facilitates collaboration
without compromising trade. The true cost of risk reduction is not known. More
effective predictive models for invasiveness, impacts, and recovery outcomes
will be needed.
To date, NPDRS has focused on response plans. The challenge for NPDRS
will be to transition into the development of recovery strategies in the face of
increasing introductions that call for more response plans.
Challenges
The Select Agent Paradox
The Select Agent program includes a requirement for the identification of
high-consequence plant pathogens and toxins having a reasonable potential to
cause significant ecological or economic damage and the potential for deliberate
introduction. Once a pathogen is designated as a Select Agent, strict laws regulate
its possession, handling, and dissemination. Responsibility for managing a plant
disease outbreak caused by a Select Agent resides with APHIS. If it is suspected
or determined that the introduction was intentional, then the Federal Bureau of
Investigation would share primary responsibility.
The original Select Agent list for plant pathogens included 10 pathogens
(see Fletcher and Stack earlier in this chapter). Since its adoption, at least four
of these agents have been introduced into the United States either accidentally
as a result of trade (Ralstonia solanacearum, Liberobacter asiaticus, Plum pox
virus) or naturally as a result of a weather event (Phakopsora polysora) (Stokstad,
2004). Two of those agents are now considered to be endemic and were removed
from the Select Agent list. Once removed from the list, the management of the
threat agent shifted from primarily a federal responsibility to primarily a state
and local responsibility.
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global infectious disease surveillance and detection
The utility and effectiveness of the Select Agent program should be reviewed.
At best, it reduces the potential for an accidental escape from a domestic lab and
impedes the illicit acquisition of a viable culture or toxin preparation from a
domestic lab or commercial culture collection. At worst, it precludes achieving a
state of preparedness at the state and local levels. Pathway analyses indicate that
for most of the Select Agents, there is an equal or greater probability of being
introduced accidentally or naturally than intentionally. If these agents are truly
the organisms of greatest concern, we should be encouraging many of our scientists to conduct the research necessary to ensure that we can detect them quickly,
diagnose them correctly, and respond effectively to minimize the potential negative impact. If working with these agents is too difficult for U.S. scientists then
we will not be building the necessary expertise for the organisms that pose the
greatest threat to the country. A reevaluation of the goals and effectiveness of the
Select Agent Rule should be executed with specific reference to the unintended
consequences that impair preparedness and response.
Animal and Plant Health Inspection Service
The authority for regulating high-consequence plant pathogens and insect
pests resides within APHIS. Responsibilities include providing emergency
response to outbreaks; issuing permits for interstate transport and international
importation of pathogens and pests; coordinating national and regional pest surveys; providing training programs; and developing and validating diagnostic protocols. Most of these tasks are time sensitive and resource intensive, sometimes
with significant legal ramifications. Yet, among the USDA agencies, APHIS has
historically received the least funding. Its level of support seems disproportionate
to its responsibility. If we are to develop and maintain a national state of preparedness in the face of increasing plant pathogen and pest introductions, increased
support within USDA for APHIS and increased support within APHIS for plant
programs will be necessary.
Sampling
Sampling underpins the successful implementation of every strategy on
which a successful biosecurity program depends. A sampling protocol depends
on the characteristics of the target agent, the environment in which it exists, and
the matrix from which it is to be sampled. Consequently, much effort should be
applied to the development and validation of the methods deployed. However,
the extremely large number of potential threat agents in plant systems precludes
implementation of a comprehensive sampling strategy for each agent. Therefore,
more general sampling strategies are needed that increase the probability of
interception for a wide array of agents.
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Formulating and implementing a national strategy for recovery from single
or multiple introductions to plant systems is a challenge beyond the mission
of any single agency or department. It will require the coordination of several
government departments at the local, state, and federal levels; public and private
educational institutions; and the many industries that support plant systems in the
United States. As has been identified for zoonotic disease surveillance (Dudley,
2004), a central body with responsibility for plant disease health that would
develop a national strategy does not exist.
Summary
There are many challenges to achieving plant biosecurity within the United
States and across the world. The success of U.S. agriculture has made possible
a high standard of living with a safe, inexpensive, and dependable food supply
system. But it has also left us complacent with respect to food production. Educational programs are needed to increase awareness among the general population
and among policy makers regarding the interdependence of plant, animal, and
human systems. Appropriately, human systems have the greatest value in society
and require the greatest investment of our time and resources. Sustenance of
healthy human and animal systems requires healthy plant systems. Having less
value does not mean having little value.
The world at the beginning of the 21st century is vastly different than it
was at the beginning of the 20th century. Among the challenges to sustainable
living systems are globalization, climate change, population growth, and bioterrorism/biocrime. There is neither a single strategy nor a single technology that
will ensure the security of our living systems. The benefits of globalization are
tremendous, but so too are the risks if we do not prepare for the consequences
with respect to emerging diseases of humans, animals, and plants. Consequently,
all nations must be secure if any nation is to be secure. Through modern transportation systems and international commerce, some of the natural barriers (e.g.,
oceans) to the dispersal of pathogens have been circumvented or eliminated.
Most plant pathogens once took decades to disperse naturally around the world.
Through normal commerce it may now take only a few days to a few weeks.
Two introductions of the Select Agent Ralstonia solanacearum r3b2 in 2003 and
2004 from Kenya and Guatemala, respectively, are good examples. The threat of
intentional introduction could reduce that dispersal interval to one day.
Historically, pathogens have moved naturally and accidentally among nations
around the world. However, the rate of their border crossings has increased dramatically, resulting in drastically reduced time to prepare for an introduction.
International cooperation is essential to achieve plant biosecurity. The importance
of global management of disease outbreaks to minimize large-scale impacts was
justified effectively for animal and human diseases (Karesh and Cook, 2005).
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The same case can be made for plant diseases. Many of the plant pathogens that
have caused epidemics in North America over the past 150 years were introduced
from Africa, Asia, Europe, and South America. Intuitively, the health and stability
of plant production systems in the United States depends on good plant surveillance systems in other parts of the world. Improved cooperation among nations
is required for prevention and rapid outbreak intervention.
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Taylor, L. H., S. M. Latham, and M. E. J. Woolhouse. 2001. Risk factors for human disease emergence. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
356(1411):983-989.
Tu, C., G. Crameri, X. Kong, J. Chen, Y. Sun, M. Yu, H. Xiang, X. Xia, S. Liu, T. Ren, Y. Yu, B. T.
Eaton, H. Xuan, and L. F. Wang. 2004. Ant���������������������������������������
������������������������������������������
ibodies to SARS coronavirus in civets. Emerging
Infectious Diseases 10(12):2244-2248, http://www.cdc.gov/ncidod/EID/vol10no12/04-0520.
htm (accessed May 25, 2007).
USDA-ERS (U.S. Department of Agriculture, Economic Research Service). 2007. Soybeans and oil
crops, http://www.ers.usda.gov/Briefing/SoybeansOilCrops/ (accessed May 1, 2007).
Wagner, M., F. C. Tsui, J. U. Espino, V. M. Dato, D. F. Sittig, R. A. Caruana, L. F. McGinnis, D. W.
Deerfield, M. J. Druzdzel, and D. B. Fridsma. 2001. The emerging science of very early detection of disease outbreaks. Journal of Public Health Management and Practice 7(6):50-58.
Wheelis, M., R. Casagrande, and L. V. Madden. 2002. Biological attack on agriculture: Low-tech,
high impact bioterrorism. Bioscience 52(7):569-576.
Whitby, S. M. 2001. The potential use of plant pathogens against crops. Microbes and Infection
3(1):73-80.
Whitby, S. M. 2002. Biological warfare against crops. Basingstoke, UK: Palgrave Macmillan.
Wilkie, D. S., and J. F. Carpenter. 1999. Bushmeat and hunting in the Congo Basin: An assessment of
impacts and options for mitigation. Biodiversity and Conservation 8(7):927-955.
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2
Surveillance Networks
OVERVIEW
As several of the contributors to this chapter note, clinical surveillance of
infectious disease is inadequate in much of the developing world due to limited
funding for public health infrastructure. Because many impoverished regions are
also at high risk for emerging disease threats, alternative methods of surveillance
are crucial to global health. The papers collected in this chapter describe a variety
of electronic surveillance networks, designed to gather and integrate information
on infectious disease from a variety of nontraditional sources (e.g., Internet sites,
news outlets, observers with little or no medical training) and to disseminate
alerts broadly and rapidly.
The chapter begins with a description of the first infectious disease surveillance network, ProMED-mail. Stephen Morse, one of the network’s founding
members, provides a brief history of the free, nonprofit, noncommercial, moderated e-mail list that today serves over 37,000 subscribers in more than 150 countries, as well as anyone with Internet access. Since it began as an experimental
system in 1993, ProMED-mail has helped to demonstrate the power of networks
and the feasibility of designing effective, low-cost global reporting systems. It
has also encouraged the development of additional electronic surveillance networks—such as the Global Public Health Information Network (GPHIN) and
HealthMap, described in subsequent contributions to this chapter—and the World
Health Organization’s (WHO’s) “network of networks,” the Global Outbreak
Alert and Response Network, or GOARN (see Summary and Assessment).
The chapter’s second paper, by presenter Abla Mawadeku and coauthors from
GPHIN, offers descriptive comparisons of that network along with ProMED-mail
107
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global infectious disease surveillance and detection
and the European Commission’s Medical Intelligence System (MedISys), which
is available only to European Union member states. GPHIN, a primary source of
electronic surveillance for WHO, also serves a host of government institutions,
nongovernmental agencies and organizations, academic institutions, and private
companies, who pay between 30,000 and 200,000 Canadian dollars per year in
subscription fees, depending on the specific services provided.
HealthMap is a freely accessible, automated network that collects information from multiple web-based data sources on infectious outbreaks (currently
news wires, Really Simple Syndication (RSS) feeds, ProMED mailing lists, and
EuroSurveillance and WHO alerts). The network then organizes and displays this
information in real time as graphic “maps” featuring geography, time, and infectious disease agent. In their contribution to this chapter, workshop presenter John
Brownstein of Harvard Medical School and his colleagues at Children’s Hospital
Boston discuss their efforts to evaluate the HealthMap system with reference
to four characteristics that have been used to evaluate syndromic surveillance
systems: data acquisition; information characterization; signal interpretation; and
dissemination. The authors’ preliminary evaluation of HealthMap according to
these criteria appears to demonstrate that the aggregation of multiple sources of
data—each potentially biased or otherwise flawed—increases the sensitivity and
timeliness of alerts while reducing false alarms.
The concluding paper of the chapter describes a different sort of electronic
surveillance network: one powered by cell phones, enabling observers in some
of the world’s most remote and impoverished communities to report disease
outbreaks. The authors are workshop speakers Pamela Johnson of Voxiva, a
company that provides information technology to establish surveillance networks
in low-resource settings, and David Blazes, of the U.S. Naval Medical Research
Center Detachment in Lima, Peru, which used an Internet- and cell phone-based
electronic system developed by Voxiva to support disease surveillance by the
Peruvian navy along that country’s coast and remote rivers. This experience is
presented as a case study in surveillance and evaluated according to the Centers
for Disease Control and Prevention (CDC) guidelines for public health surveillance systems. The authors also share lessons gleaned from six years of building
surveillance systems, based on cell phones and other cost-effective information
technologies, for use in low-resource environments.
Workshop participants raised a series of issues in response to the presentations upon which the papers in this chapter are based. A detailed account of this
discussion appears in the Summary and Assessment section, “Considerations for
Surveillance Networks.” Discussants were especially concerned about the potentially devastating economic consequences to a country—particularly a developing
country—of being labeled (accurately or inaccurately) as harboring a feared infectious disease. In his contribution to Chapter 4, speaker Will Hueston assesses the
tradeoff between health and development inherent in the release of surveillance
information such as HealthMap’s geographic depictions of outbreak reports.
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SURVEILLANCE NETWORKS
GLOBAL INFECTIOUS DISEASE SURVEILLANCE AND EARLY
WARNING SYSTEMS: PROMED AND PROMED-MAIL
Stephen S. Morse, Ph.D.
Columbia University
A number of emerging infections have appeared throughout the world
in recent years (Morens et al., 2004; IOM, 1992, 2003; Morse, 1995). Or, in
the words of Marci Layton (New York City Department of Health and Mental
Hygiene), we must learn to expect the unexpected. It is widely agreed that one of
the most important measures for both emerging and existing infectious diseases
is an effective early warning system, that is to say, global infectious disease
surveillance. Here, I will discuss ProMED, the nonprofit international Program
for Monitoring Emerging Diseases, and its best known progeny, ProMED-mail
(PMM). ProMED itself was founded in 1993 to design and help implement
global surveillance systems that could detect both known and emerging infections
(Morse et al., 1996).
A Brief History of ProMED and ProMED-Mail
ProMED had its roots in the same Institute of Medicine (IOM) report that
led to the development of the Forum on Microbial Threats (IOM, 1992). The
Committee that developed the 1992 IOM report was chaired by Joshua Lederberg
and the late Robert E. Shope. After the report was released, there was considerable concern about maintaining the momentum. Many of the original Committee
members (including me) believed the problem required long-term attention. In
addition, for specific reasons the charge to the IOM Committee and consequently
the report were limited to the United States. However, there was a clear need
to consider these infections as global threats that would require international
solutions. In an attempt to fill what many (including this author) saw as the
fragmentation of disease surveillance systems and the lack of global capacity,
ProMED was begun in 1993 under the auspices of the Federation of American
Scientists (FAS).
Several years earlier, I had been asked by Barbara Hatch Rosenberg, then
chairing a working group on biological nonproliferation issues at FAS, to provide
technical advice for her working group. After the 1989 National Institutes of
Health (NIH) meeting on emerging viruses and the 1992 IOM report, Rosenberg
and I discussed the possibility of developing an initiative for global infectious
Mailman
School of Public Health.
article on the early history and activities of ProMED is available at http://www.fas.org/faspir/
pir1293.html, with an update at http://fas.org/promed/announce.htm. Additional materials are available at http://fas.org/promed/.
An
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global infectious disease surveillance and detection
disease surveillance, with start-up resources from FAS. Dorothy Preslar served
as the project staff at FAS.
The group held a small initial organizational meeting in February 1993 at
The Rockefeller University in New York. In addition to Rosenberg, and myself
as Chair, among those present at that meeting were Ruth Berkelman (then at the
Centers for Disease Control and Prevention, or CDC), Scott Halstead (then at the
Rockefeller Foundation), D. A. Henderson (then at Johns Hopkins and the U.S.
Department of Health and Human Services), James M. Hughes (then at CDC),
John LaMontagne (then at NIH’s National Institute of Allergy and Infectious
Diseases, or NIAID), and Shope (then at Yale). At that time, it was decided that a
conference would be held in Geneva in fall 1993, that the group’s purview should
include animal and plant diseases in addition to human disease (a view especially
advocated by Berkelman), and that the group should be named ProMED (Shope
suggested the name).
The next activity was a conference, cosponsored by FAS and the World
Health Organization (WHO) and held on September 11 and 12, 1993, at WHO
headquarters in Geneva. Part of the challenge at that time was that the thenDirector General of WHO did not believe that surveillance for infectious diseases
was part of the organization’s core responsibilities. Unfortunately, many clinicians and most of the lay public naïvely believed otherwise, and thought that
WHO was already doing it.
The September 1993 ProMED meeting, co-chaired by Francis Nkrumah of
Ghana and myself, was held in the WHO Executive Board Room, and included as
speakers a number of people who had been influential in WHO affairs, including
Jan Kostrzewski, a former chair of the WHO Executive Board, Henderson, and a
number of members of the World Health Assembly. At that event, 60 prominent
scientists and public health officials working on human, animal, and plant health
from all parts of the world met, unanimously endorsed the concept of global
surveillance, and formed ongoing working groups to assess present capabilities
and develop and implement plans for a suitable global program that could address
both known and emerging infections. We also invited John P. (Jack) Woodall
(then at WHO) onto the Steering Committee, and James LeDuc (then at WHO,
seconded from CDC) agreed to serve as a special consultant.
One would think it should be fairly simple to strengthen and network regional
centers of excellence to augment official systems and develop mutual cooperation, whether through WHO (preferably) or through regional intergovernmental
organizations. On the other hand, if diseases can emerge anywhere, how can one
get early warning from literally everywhere? The latter seemed the harder task,
so we decided to try tackling what everyone considered the easier one first. At
meetings in Geneva and elsewhere, we recommended developing a coordinated
The
list of the early Steering Committee members can be found at http://fas.org/promed/about/
steering.html.
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111
system of regional centers and a minimum set of capabilities to identify and
respond to unusual disease outbreaks. A plan was subsequently published (Morse
et al., 1996), in part elaborating on the system Henderson had proposed at the
1989 NIH/NIAID meeting on emerging viruses (Henderson, 1993). The strategy
developed was vigilance for unusual clinical presentations of special concern
(e.g., encephalitis or acute respiratory distress with fever in adults); a minimum
set of microbiological capabilities at each site to identify common diseases; and
a system to refer unidentifiable samples to successively more sophisticated reference laboratories, through the network, for possible identification. The plan also
included epidemiologic capacity, which could be provided rapidly through the
network if needed (Morse et al., 1996).
The effort continued with meetings at other places. At a Steering Committee
meeting in June 1994 at Airlie House in Virginia, we realized that our members
from all over the world had no reliable means to communicate with one another.
Nkrumah of Ghana, for example, had a Telex, which in any major American city
usually required a trip downtown to a special office building to send, but no fax
machine. In Russia, they had fax machines but no fax paper because of a lack of
money. We decided to try to put everyone on a common communications system. Charles Clements, then at a nonprofit organization called SatelLife, which
specialized in inexpensive e-mail connections for remote and underserved areas
through satellite radio links, had been invited to the meeting. I appointed Woodall
as head of a new Communications Task Force. By the end of the meeting a plan
had been developed to connect everyone by e-mail. SatelLife provided connectivity for places without e-mail connections, for example (at that time) in Africa,
China, and Russia. The rest of us learned how to use the existing e-mail systems
at our institutions (quite an ordeal in those days). Thus ProMED-mail was born.
Although only about 10 years ago, it was another era technologically.
As the system developed and people started using e-mail for communications, we realized it could also be used as an international outbreak reporting
system. (So much for deferring those “more challenging” goals, such as how
to get reports from everywhere.) Woodall and I served as the initial moderators
(or “editors”), a time-consuming task. Woodall deserves tremendous credit for
his dedication and enormous contributions to the subsequent development of the
system. Since 1995, the system has been available on the Web, as well as by
e-mail subscription. The partnership between ProMED and SatelLife continued
fruitfully until 1999, when the ProMED reporting network was transferred to
the International Society for Infectious Diseases (ISID), headquartered at
Harvard’s Channing Laboratory in Boston. The communications network was
renamed ProMED-mail, to distinguish it from other ProMED activities then
underway.
See
http://www.promedmail.org.
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global infectious disease surveillance and detection
ProMED-Mail: A Prototype Infectious Disease Reporting System
Many people think of PMM as synonymous with ProMED, as it has taken on
a robust life of its own. PMM was designed as an open reporting and discussion
system. It is a nonprofit, noncommercial e-mail list that now has some 40,000
subscribers, with over 165 countries represented. Not all of them, of course, send
in reports because the editors would be overwhelmed, but many subscribers do
read the e-mails on a regular basis. Although numbers vary, incoming e-mails
(roughly 100 a day) generate an average of 7 to 10 reports every day.
The e-mail listserv is moderated, which means that messages coming in
are first read by people with scientific or medical expertise. Originally this
was Woodall and at times me until I left for government service in 1996. As
the list grew, a number of other moderators were recruited in various specialty
areas, and the system is fortunate to have a number of distinguished experts as
moderators.
In principle, subscribers send in reports and information. Rapporteurs take
additional responsibility to report regularly in their own geographic or special
interest areas. Rapporteurs report from Russia, China, and a number of other
places as well as within the United States. When someone sends in a report
from somewhere (one of the earliest reports of Ebola in Kikwit, Zaire, now the
Democratic Republic of Congo, came from a medical missionary who had a radio
e-mail link), the report is assigned by the editor-in-chief or someone acting in
that capacity, to the appropriate moderators for editing and, if appropriate, posting to the list. The moderator reads the report for scientific plausibility. If the
report looks credible, the moderator edits and formats as needed, probably adds
comments to put the item in context, and send it out as a posting to the list. All
subscribers are free to comment or add information after reading the posting.
In addition to the full list, which includes outbreak reports and discussions
on human, veterinary, and plant diseases, there are several sublists for those
who want only certain parts of this information. It is possible to subscribe to the
animal and plant disease lists separately. The human disease list includes both
human and animal disease. This causes occasional complaints from physicians,
but we have believed strongly from the beginning that it is essential to improve
the connections between animal and human health. Justifying this is the fact that
many emerging infections are zoonotic. Those who are interested in getting only
the breaking news, without the ensuing discussion, can subscribe to the Emerging
Disease Reports (EDR) sublist. I get EDR on my BlackBerry wireless device.
In recent years sub-lists have been developed in Portuguese, Spanish, and
Russian, and there is interest in developing other foreign language lists as well.
Some of the regional reports of wide interest are translated into English.
The PMM architecture is simple. Technically, the e-mails are 7-bit ASCII
text, the most basic format. When the system was started in August 1994, people
in developing countries had very limited bandwidth. It is amazing how much
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113
this has changed in the past decade, with broadband Internet cafes now even in
remote areas.
The editors also search the Web and press reports, an increasingly important source of information. This strategy was originally adopted by GPHIN (the
Canadian government’s Global Public Health Intelligence Network), which is
described in another chapter. GPHIN was started in 1999 and is based largely on
news sources from the Web. Unfortunately such material was not available when
PMM was started. Since then, the explosive growth of the Web and of improved
methods for searching have made such strategies very effective.
Perhaps one of the most important value-added features of PMM is the distinguished and hard-working team of moderators or editors (for this chapter, I am
using these two terms interchangeably). Although they are essentially volunteers,
all are subject-matter experts. The moderators also have their own e-mail lists and
personal networks for follow-up, which demonstrates the power of networking.
Larry Madoff is the current editor-in-chief of PMM, while Woodall (now associate editor) remains as active and involved as ever. He has had a critical role in
developing PMM into what it is today. Eduardo Gotuzzo, in addition to being a
member of the IOM Forum, is Chair of the PMM Policy Committee.
All this is probably obvious to anyone who has read PMM. Anyone can contribute; data come from clinicians (those proverbial astute clinicians in the field
all over the world), public health officials and epidemiologists, lab scientists, or
medical missionaries, but also journalists and interested laypeople.
There was a concern initially that the method of obtaining data would give
rise to many rumors that health authorities would then have to verify, expending
valuable resources. This has not turned out to be a major problem. Of course,
sometimes information is incorrect, but in general the reliability turns out to
be more than 95 percent, according to figures that Madoff tabulated. However,
PMM has developed several mechanisms to deal with the possibility of erroneous reports. One is personal follow-up by moderators. The moderators, experts
in their fields and generally well connected, can use their own personal networks
to try to get more information to include. Second, an uncertain report could also
be posted as a request for information (RFI), an inquiry which is simply a way
of asking people if they have more information they can contribute. Others on
the network may also spontaneously add to or correct a posting if they have
additional facts.
Subsequently, WHO, in response to information from PMM and GPHIN,
developed a very effective mechanism of its own, called the Outbreak Verification List. WHO sends this list out regularly to a limited group of public health
officials and scientists to try to follow up on various outbreak reports. It is a sign
of WHO’s increasing capacity and interest that the reports increasingly are coming from WHO’s own country and regional representatives. WHO has developed
its own network of networks, the Global Outbreak Alert and Response Network
(GOARN), which includes a number of formal and informal sources. It should
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global infectious disease surveillance and detection
be noted that the situation at WHO has greatly improved in the last few years,
thanks to the concerted efforts of a number of people, including James LeDuc in
the early days, and notably David Heymann more recently.
One particularly interesting aspect of a system like PMM is that it can be
used to compare reports from a number of places. In addition to outbreak reporting, it provides the ability for people to recognize that what they are observing
may be happening elsewhere, too. An initial report may encourage others to
contribute local information that may help to estimate the extent and numbers of
an infectious disease outbreak, and to monitor spread. One example was a 1995
outbreak of meningococcal meningitis occurring simultaneously in several states
and in the United Kingdom. The outbreak became evident when the reports from
various places appeared on PMM.
PMM has been available on the Web since the Ebola outbreak of 1995 in
Kikwit, when it partnered with and later incorporated an independent effort
called “Outbreak.” As the Web itself grows, the website has had an increasing
presence. If one prefers not to receive e-mail alerts, it is a simple matter just to
search the website and read any of the reports. The Web archives include some
of the earliest reports, such as the first reports of Ebola in Kikwit. Among other
PMM “firsts” was Venezuelan equine encephalitis, coincidentally in Venezuela.
It was originally denied by the government; when it was verified it led to the
resignation of the health minister. West Nile virus in 1999 was another event
PMM extensively covered. During this period, Ian Lipkin generously wrote in
to offer reagents for people internationally. Other firsts include reports of H5N1
influenza in Indonesia in November 2003 and fatalities in China in 2005 attributed to Streptococcus suis.
The first report of severe acute respiratory syndrome (SARS) that appeared
on PMM was a rumor about an unusual outbreak in south China with unexplained
deaths. Steve Cunnion picked this up, and information was posted on February
10, 2003. Shortly after that, China officially reported the disease, and WHO was
able to release information officially. By that time, China reported 305 cases.
SARS had actually been infecting people for at least several months (IOM, 2004).
SARS then spread to Toronto, where it was originally called “atypical communityacquired pneumonia” and was reported on PMM.
Madoff has tabulated the PMM disease reports over the past 10 years. Dengue, which is quite common, is one constant, as are a number of others. Many are
known conditions, but at least 209 are not. Some will eventually be added to the
known category. There have also been reports of CDC Category A agents, normally more closely associated with bioterrorism or biowarfare. However, anthrax
exists naturally throughout the world in livestock. In developing countries, there
may be thousands of cases of gastrointestinal anthrax from contaminated meat.
More than 200 cases of anthrax in livestock were reported on PMM before the
intentional anthrax attacks of fall 2001. Botulism and tularemia are also natu-
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rally occurring diseases, which reminds us that many of the classic bioweapons,
including the Category A agents, are zoonotic agents.
PMM was developed as a prototype, and continues to evolve. There have
been increasing efforts since then. GPHIN and WHO’s GOARN have already
been mentioned. A later paper, by Pamela Johnson, will discuss Voxiva, which
uses the power of networks with another technological base, the cell phone
network.
PMM has also elicited some kind comments. Henderson referred to CNN
and PMM as the major sources of information for infectious diseases. Steven C.
Joseph (formerly New York City Health Commissioner, Dean of the Minnesota
School of Public Health, and Assistant Secretary of Defense for Health Affairs)
referred to PMM as “the CNN of infectious diseases” (Personal communication,
S. C. Joseph, June 1995). Perhaps the most intriguing characterization comes from
Steven Johnson, in his book The Ghost Map, about cholera in Victorian London.
A sentence in the book caught me by surprise as I was leafing through it:
The popular ProMED-mail e-mail list offers a daily update on all the known
disease outbreaks flaring up around the world, which surely makes it the most
terrifying news source known to man (Johnson, 2006).
For an infectious disease surveillance system, that seems high praise indeed.
Since PMM was started as an experimental system more than a decade ago, it
has helped to demonstrate the power of networks and the feasibility of designing
widely distributed, low-cost reporting systems, and it has encouraged the development of additional systems using additional technologies. All these efforts help
to begin building the heavily networked surveillance systems that will be needed
to deal with threats in an increasingly globalized and unpredictable world.
Acknowledgments
Sincere thanks to Jack Woodall and Larry Madoff for their hard work and
helpful discussions, and to all the editors/moderators and funders of ProMEDmail for their dedication and good work. Stephen S. Morse is supported by
CDC cooperative agreements A1010-21/21, U90/CCU224241 (Centers for Public
Health Preparedness), and U01/CI000442, the Arts & Letters Foundation, and
by NIH/NIAID cooperative agreement 5U54AI057158 (Northeast Biodefense
Center RCE).
A
list of current PMM personnel is at http://www.promedmail.org; click on “Who’s Who.”
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global infectious disease surveillance and detection
GLOBAL PUBLIC HEALTH SURVEILLANCE: THE ROLE OF
NONTRADITIONAL SURVEILLANCE TOOLS
Abla Mawudeku, M.P.H.
Public Health Agency of Canada
M. Ruben, M.D., Ph.D.
Public Health Agency of Canada
R. Lemay, B.Sc., M.B.A.
Public Health Agency of Canada
Introduction
In a world deeply interconnected by traveling and trade, the spread of infectious agents is inevitable. Regions once isolated are now integrated into the global
community and have the risk of being exposed to infectious agents that they previously were unexposed to, as well as sources of old and new agents, and even
new pandemics. Therefore, there is global concern about surveillance and control
of diseases (particularly infectious diseases) around the globe.
Any global surveillance system has to overcome several challenges; basically,
it requires a good system for communications to and from the field to get timely
collection, analysis, and dissemination of data, and to be able to force political
decisions and allocation of resources. However, susceptibility to infectious diseases and increased risks of infection are usually associated with poverty, and
poverty is more frequent in those countries where epidemiological and laboratory
surveillance is defective or nonexistent (Heymann and Rodier, 2001). In addition,
while several countries, particularly in the Western world, have already national
surveillance systems to monitor for potential public health threats, in many circumstances these systems are inadequate, fairly erratic, or too disease specific
to identify new diseases early (Butler, 2006). Also, countries have been reluctant
to report outbreaks due to the perception of a negative impact of such news on
the country’s economy (trade and tourism). Public alarm, sometimes fueled by
the press, has resulted in many occasions in important losses for the countries,
which then try to hide or delay the recognition of the presence of human or animal
diseases (Cash and Narasimhan, 2000). Nevertheless, the electronic era, in which
press reports and the Internet keep societies informed and interconnected, have
begun to break down all attempts of “secrecy.”
Currently there is no comprehensive global public health surveillance system. The World Health Organization (WHO) is the only organization that has the
mandate to monitor and respond to global public health threats, as established
Chief.
Scientist.
Senior
Surveillance Officer.
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in the International Health Regulations (IHRs). WHO not only uses information
gathered from traditional surveillance systems but also uses information from
nontraditional surveillance systems to leverage in order to capture a more comprehensive outlook of the situation about potential public health threats occurring
worldwide. The use of nontraditional surveillance systems has contributed to the
improvement of epidemic intelligence used for the early detection of potential
public health threats. This has enabled WHO and other public health organizations such as the European Center for Disease Control (ECDC) to better assess,
investigate, and respond to events of concern (Figure 2-1).
A revised version of these regulations, IHR 2005, will be implemented in
June 2007. These new IHRs will strengthen WHO’s authority in surveillance and
response because they include more demanding surveillance and response obligations and apply human rights principles to public health interventions (Baker
and Fidler, 2006). The new regulations require that member countries report to
Event-based surveillance
EWRS
MS
DSNs
EWGLI
Enternet
EISS…
BSN
EMEA, EFSA
MedISys
GPHIN
WHO-OVL
ProMED
OIE
FAO
…
Indicator-based surveillance
Report
Data
Capture
Filter
Verify
Collect
Analyze
Interpret
Signal
Assess
Disseminate
Public health alert
Investigate
Control measures
DSNs
BSN
Laboratory network
EWRS
MS
Commission
Other healthrelated EU
agencies
WHO-IHR?
FIGURE 2-1 Epidemic intelligence framework.
EWRS = Early Warning Response System; MS = messaging system; DSN = disease surveillance network; EWGLI = European Working Group for Legionella Infections; EISS
= European Influenza Surveillance Scheme; BSN = Basic Surveillance Network; EMEA
= European Agency for the Evaluation of Medicinal Products; EFSA = European Food
and Safety Authority; WHO-OVL = Outbreak Verification List; OIE = Office International
des Epizooties (World Organization for Animal
2-1 Health); FAO = Food and Agriculture Organization; EU = European Union; and Enter-net is an established and thriving EU-wide
network for the laboratory-based surveillance of human Salmonella and Verocytotoxinproducing Escherichia coli (VTEC) infections.
SOURCE: Based on Kaiser et al. ��������
(2006).
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global infectious disease surveillance and detection
WHO “all events which may constitute a public health emergency of international
concern” (i.e., unexpected or unusual public health events that might include
communicable and noncommunicable disease events, whether natural, accidental,
or intentionally created). IHR 2005 also requires from member countries (if practicable) to report to WHO all public health risks identified outside their territories
that might cause international disease spread (Baker and Fidler, 2006). They also
give WHO more autonomy from the governments of member countries; WHO
can now use nontraditional surveillance information (i.e., data from the news
media) and ask the countries about “rumors” of circulating infectious agents.
Several innovative nontraditional surveillance systems leverage the advancements in modern Internet and information technologies to efficiently and rapidly
gather information about events of public health concern. The Global Public
Health Intelligence Network (GPHIN), the Program for Monitoring Emerging
Diseases (ProMED), and Medical Intelligence System (MedISys) are examples of
such systems that are commonly used by the public health community. All these
surveillance systems disseminate relevant reports to the public health community
in a timely manner.
Global Public Health Intelligence Network
GPHIN is an early warning system that takes advantage of existing information technology to continuously scrutinize news media sources through news
aggregators who have contracts with newspapers around the world, as well as
with health and science websites. The multilingual system gathers information
by monitoring global media on a 24/7 basis and in nine languages, including
Arabic, Chinese (simplified and traditional), English, Farsi, French, Russian,
and Spanish. More recently, Portuguese has been added. In addition, and with
the help of automated translation software, non-English articles are translated
into English, and English articles translated into French, Portuguese, Spanish,
Russian, Chinese (simplified and traditional), Farsi, and Arabic. The translations
give the essence of the news report.
The system, which has automated and manual components, searches for
information on disease outbreaks and other emerging and reemerging public
health threats (e.g., contaminated food and water, bioterrorism, chemical or
radiological threats, natural disasters) and then generates timely alerts (Figure
2-2). The automated process helps to organize and prioritize the relevant news
media reports that are reviewed and analyzed by a team of analysts who are
multilingual and multidisciplinary (Figure 2-2). The analysts work in shifts and
provide analytical coverage on a 24/7 basis. The analysts have the responsibility
of identifying events that may have serious public health consequences, and of
flagging them as alerts following preestablished criteria. The analysts also review,
periodically, the items kept in the database as irrelevant, to ensure that none of
these items represents a potential alert. In addition, the analysts are responsible
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Data collection
Advanced analytics:
Automated processes
Duplicate
elimination
Automated
gathering of
multilingual
news media
sources
Multilingual real-time intelligence
rendering
En
Fr
Metadata
insertion
Fa
Categorization
Ru
(Taxonomy )
100
Automatically published
85
1.Publish
Es
or
2. Publish with
alerts
Ar
Translation
Manual
gathering of
multilingual
news media
sources
Relevancy
score
or
Zhs
Zht
Manual analysis by
analysts
3. Irrelevant
30
Irrelevant
0
FIGURE 2-2 Global Public Health Intelligence Network (GPHIN) flow of information.
SOURCE: Public Health Agency of Canada.
for identifying trends or relationship of events, checking clarity of machine translations, and updating search syntaxes
2-2 and keywords used to monitor and gather
relevant news media reports. The users are also able to interact with the analysts
to request assistance or to provide feedback.
GPHIN is currently one of the primary sources of information for WHO.
Other GPHIN users include government institutions, nongovernmental agencies and organizations, as well as academic institutions and private companies that conduct public health surveillance worldwide. Users have access to
GPHIN through a password protected website and also receive e-mail alerts
(Mykhalovskiy and Weir, 2006).
ProMED-Mail
ProMED
offers a free public website and an e-mail list that has subscribers
from around the world (currently more than 37,000 subscribers from over 150
countries). Its mission is “to provide early warning, 7 days a week year around,
of outbreaks of emerging infectious diseases and episodes of acute toxicity, and
the spread of antibiotic and disease vector resistance, worldwide, free of charge
by e-mail” (Woodall, 2001; Woodall and Calisher, 2001). The system distributes
information about outbreaks often early on, before it is confirmed by WHO;
ProMED-mail,
International Society for Infectious Diseases, http://www.isid.org.
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global infectious disease surveillance and detection
therefore, it complements the global surveillance done by WHO and countries
(Woodall, 2001).
It allows communications by e-mail all over the world, and includes sublists
of reports in Spanish, Portuguese, and Russian, with some of the most interesting
local reports translated into English. ProMED publishes media reports, personal
reports, and summaries; it presently covers not only human diseases, but also
animal and plant diseases, and it is also available on the Web (Woodall, 2001).
Most data published by ProMED comes from individuals (clinicians, public
health officers, epidemiologists, laboratory scientists, and lay individuals) or from
academic or official organizations worldwide.
ProMED has several moderators who cover their own geographic areas (e.g.,
Russia, China) and search the Web and press reports for relevant news. These
moderators are subject-matter experts and provide their expertise as volunteers
(Mykhalovskiy and Weir, 2006); they also have their own e-mail lists and personal networks to follow up the reports, and they frequently add their comments
and their knowledge to the news.
MedISys
MedISys is a near real-time news alert automated system managed by the
Directorate General Health and Consumer Affairs of the European Commission.10
MedISys covers emerging and reemerging public health issues related to communicable diseases and bioterrorism. It monitors on a 24/7 basis approximately
800 Web sources (news and medical sites) daily in 25 languages, including the
languages of European Union (EU) member states, Arabic, and Chinese. Access
to MedISys is limited to EU member states.
Conclusions
The continuous proliferation of emerging and reemerging pathogens able
to infect humans, domestic animals, plants and wildlife seems to have increased
in the past years, helped by the increased and faster movement of people and
goods. This has generated international concern and increased efforts to improve
the early warning capacity to detect potential public health threats worldwide in
order to control and prevent the spread of diseases (Heymann and Rodier, 2001;
Formenty et al., 2006).
Today’s advancements in communication technology (e.g., blogs, wikkies),
and information technology are used liberally by the news media and the public;
this makes possible the rapid dissemination of worldwide news about events of
public health concern. Such proliferation of information has made it challenging for the public health community, with limited resources, to be aware of and
10 See
http://medusa.jrc.it/medisys/homeedition/all/home.html.
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121
analyze all the data available in an efficient and effective manner. Current early
warning tools, such as GPHIN, MedISys, and ProMED also find it challenging to
keep abreast of all the sources of information available. Therefore, the most feasible and cost-effective solution would be to establish a network of nontraditional
early warning surveillance systems in order to leverage the expertise provided by
each system. GPHIN, MedISys, and ProMED, which are complementary, could
then strengthen the mutual abilities of monitoring, gathering, analyzing, and disseminating information about events of public health concern.
In such a collaboration, ProMED’s team of experts would provide reports
of relevant events; GPHIN’s would add a team of multilingual, multidisciplinary
analysts plus its technical capacity to process high volumes of disparate multilingual data; and MedISys would add its capacity to monitor the Internet for news in
more than 20 languages, improving the gathering of information about potential
public health threats in remote areas. In addition, this collaboration would make
possible the dissemination of synthesized information (from the numerous news
sources) about relevant events, highlighting major points and strengthening epidemic intelligence. Furthermore, visualization features, like the ones provided by
the Geographic Information System (GIS), could also facilitate the epidemiological analysis of public health threats.
For such a comprehensive and ambitious network to be effective, and to reach
the entire planet, it would also need the support of the public health community
and wildlife, animal, and agricultural experts, when possible (Jebara, 2004; Butler,
2006). It also would need technologic and economic support from the private sector. It is expected that a network like this could adapt to the needs of the different
customers, and provide support to all countries, worldwide, to strengthen their
surveillance systems and be able to accomplish the mandate of the IHR guidelines.
These guidelines anticipate that each member state should assess its capability to
strengthen and maintain core surveillance capacities by 2009 and develop a plan
to accomplish this (Hardiman, 2003; Baker and Fidler, 2006).
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global infectious disease surveillance and detection
HEALTHMAP: INTERNET-BASED EMERGING INFECTIOUS
DISEASE INTELLIGENCE
John S. Brownstein, Ph.D.11
Harvard Medical School
Clark C. Freifeld, B.S.12
Children’s Hospital Boston
Ben Y. Reis, Ph.D.13
Children’s Hospital Boston
Kenneth D. Mandl, M.D., M.P.H.14
Children’s Hospital Boston
Although many developed countries are strengthening their traditional clinically based surveillance capacities, the required health information infrastructure
is lacking in parts of the world that may be most vulnerable to emerging health
threats. At the same time, an enormous amount of information providing situational awareness about infectious diseases is found in web-accessible information sources, such as Internet-based discussion sites, disease reporting networks,
news outlets, and blogs. These data also exemplify unprecedented potential for
increasing public awareness on public health issues prior to their widespread
recognition. Despite the growing use of these unstructured information sources
for monitoring emerging infectious diseases, there has been little, if any, formal
evaluation of their utility, accuracy, coverage, or timeliness. Building on established evaluation approaches for public health surveillance systems, we present
a surveillance framework that defines important challenges and critical research
questions that define a research agenda. The framework is informed by evaluation of the performance of HealthMap, a freely accessible, automated system for
real-time monitoring of online information about emerging diseases. This chapter
highlights the value of a robust research agenda, continued organic evolution of
existing and new technologies, and scrutiny through a rigorous evaluation framework to help ensure that the global public health enterprise maximally leverages
11 Instructor, Department of Pediatrics, Harvard Medical School, Children’s Hospital Boston, 1
Autumn St, Room 541, Boston, MA 02215. Phone: 617-355-6998. Fax: 617-730-0267. E-mail:
[email protected].
12 Research Software Developer, Children’s Hospital Informatics Program at the Harvard–MIT
Division of Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave.,
Boston, MA 02115.
13 Instructor, Children’s Hospital Informatics Program at the Harvard–MIT Division of Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave., Boston, MA 02115.
14 Associate Professor, Children’s Hospital Informatics Program at the Harvard–MIT Division of
Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave., Boston, MA
02115.
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new electronic sources for surveillance, communication, decision making, and
intervention.
Introduction
Real-time public health surveillance represents a critical tool for controlling
infectious diseases, an effort that requires a timely and global approach addressing the complex and dynamic interactions among infectious agents, animals, and
the environment (Heymann and Rodier, 1998, 2001; Woodall, 2001). Although
many developed countries are strengthening their traditional clinically based
surveillance capacities, the required health information infrastructure is lacking
in parts of the world that may be most vulnerable to emerging health threats
(Butler, 2006). The existing network of traditional surveillance efforts by health
ministries, institutes of public health, multinational agencies, and laboratory and
institutional networks has gaps in geographic coverage and often suffers from
poor information flow across national borders.
At the same time, an enormous amount of information providing situational
awareness about infectious diseases is found in web-accessible information
sources, such as Internet-based discussion sites, disease reporting networks, news
outlets, and blogs (Heymann and Rodier, 2001; Grein et al., 2000; M’Ikanatha et
al., 2006). Even web-based clickstream and keyword searching aggregated across
Internet users can provide important insights (Eysenbach, 2006). These resources
provide valuable and highly local information about disease outbreaks and related
events, even from areas relatively invisible to daily global public health efforts
(Woodall, 1997). In fact, the majority of outbreak verifications currently performed by the World Health Organization’s (WHO’s) Global Outbreak Alert and
Response Network (GOARN) initially begin as reports from informal electronic
data sources such as mailing lists and local news media (Heymann and Rodier,
2001; Grein et al., 2000).
While these web-based data sources can facilitate early detection of outbreaks, they may also support increasing awareness of public health issues prior
to their formal recognition. Through low-cost and real-time Internet data mining combined with open-source and user-friendly technologies, participation in
global disease surveillance is no longer limited to the public health community
(Keystone et al., 2001; Petersen, 2005). Furthermore, the availability of webbased media across national borders greatly ameliorates the potentially suppressive effects of political influence on the spread of information.
The HealthMap Project
Though valuable, electronic sources of emerging infectious disease news are
not well organized or integrated. We sought to develop HealthMap, a freely accessible, automated approach to organizing data about infectious outbreaks accord-
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global infectious disease surveillance and detection
ing to geography, time, and infectious disease agent (Figure 2-3) (Holden, 2006;
Larkin, 2007; Captain, 2006). HealthMap is a multistream real-time surveillance
system that aggregates multiple Web-based data sources (currently news wires,
Really Simple Syndication (RSS) feeds, ProMED mailing lists, and EuroSurveillance and WHO alerts). Information is acquired automatically through screen
scraping, natural language interpretation, text mining, and parsing to obtain disease name and geocode the location of the outbreak. HealthMap also addresses
the computational challenges of integrating multiple sources of unstructured
online information in order to generate robust meta-alerts of disease outbreaks.
Through this approach, we achieve a unified and comprehensive view of current
global infectious disease outbreaks in space and time.
System Challenges
Despite the success of Internet-based surveillance systems such as HealthMap,
important technological and methodological challenges remain. Four principal
development and deployment issues are as follows:
(1) Value. Though there is an abundance of disparate electronic resources,
none is comprehensive. Each has gaps in coverage of certain geographic areas,
population sectors, medical expertise, and availability.
(2) Standards. No universal standards exist for capturing, processing, reporting, interpreting, or sharing structured data. Such standards would greatly facilitate
the communication and use of information by computationally based systems.
(3) Performance. Metrics for systematic evaluation of these data sources and
the performance of these systems are still needed. Though there has been some
description of individual data sources (M’Ikanatha et al., 2006; Cowen et al.,
2006), there is still limited understanding of their value for spatial and temporal
detection and monitoring of disease outbreaks.
(4) Accessibility. Important issues require attention to system ownership,
target audience, restrictions, cost, and sustainability.
Surveillance Framework
A good starting point for design of a surveillance framework is the one
currently used for the syndromic surveillance systems that have evolved over
the past eight years (Mandl et al., 2004a; Buehler et al., 2004; CDC, 2000). The
anthrax attacks of 2001 gave rise to large-scale surveillance efforts directed at
early detection of an outbreak, prior to confirmed diagnosis (Perkins et al., 2002).
These novel surveillance systems also use data that are not diagnostic of a disease, but that might indicate the early stages of an outbreak, often earlier than
might otherwise be possible with traditional public health methods. The ideal
syndromic surveillance system has the following traits: it acquires data automati-
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FIGURE 2-3 Screenshot of the HealthMap system.
SOURCE: http://www.healthmap.org.
2-3
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global infectious disease surveillance and detection
cally; collects ongoing data in real time or near real time; electronically stores
and transmits data to an analytic module; has sufficient demographic, geographic,
and temporal coverage to support anomaly detection; captures data in standard
formats across data sources; protects private information and patient confidentiality; and scans for outbreaks, correctly distinguishing an abnormal pattern from
a normal or expected one (Mandl et al., 2004a). While Internet-based surveillance represents a paradigm shift from indicator-based to event-based sources of
information, the existing framework is designed to support the evaluation of all
public health surveillance systems. The standard set of evaluation metrics used
to interpret data quality and signal detection should apply across both traditional
and Internet-based surveillance approaches (Mandl et al., 2004a, b; Buehler et
al., 2004; Wagner et al., 2001). Both Internet-based surveillance and traditional
syndromic surveillance require four stages: (1) data acquisition, (2) information
characterization, (3) signal interpretation, and (4) dissemination and alerting
(Figure 2-4).
Here we present a summary of initial evaluation efforts based on this surveillance framework. To help inform our evaluation, we analyzed the HealthMap alert
data stream, over a 20-week period (October 1, 2006, through February 17, 2007),
FIGURE 2-4 Framework for Internet-based surveillance.
SOURCE: Brownstein (2006).
2-4
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applying standard evaluation metrics (volume, geography covered, diseases captured, timeliness, sensitivity, and specificity). Over this period, HealthMap found
3,194 news reports of infectious disease outbreaks (a mean of 22.8 per day, 95
percent confidence interval, 20.6–25.0).
Data Acquisition
Data can be acquired by search either of the open Web or of specific restricted
or open websites. The choice of data sources has critical implications for early
outbreak detection and disease monitoring across all metrics. Here data sources
are evaluated across three dimensions: quality, cost, and availability.
Data Quality
The ideal information sources would be sensitive to even the smallest aberrations. However, as in all surveillance activities, there is an inherent tradeoff
between the timeliness and specificity of a system. For example, local news
sources may report on strange incidents involving a few cases that would not be
picked up at the national level. However, local news reports may be less reliable,
reporting stories without adequate confirmation. Information is not always validated, and the credibility of the sources is not always vetted. Thus, without proper
filtering, these local news sources may be responsible for substantial noise in
the system and increasing the overall false alarm rate. Furthermore, other biases
may be introduced for political reasons, resulting either in disinformation (false
positives) or censorship (false negatives). In the case of ProMED, its hierarchical
curation structure helps minimize false positives. However, while expert review
does increase specificity, the required manual processing delays alert reporting.
Data Cost
Internet-based surveillance data have been limited largely to automated
mining of information from news aggregators. An important question is whether
paid subscription sites provide more value than freely available information. For
example, news aggregators such as LexisNexis®, Factiva®, and Magenta News®
may all be useful sources of information, especially for local news in a substantial
number of languages. However, free online news aggregators, such as Google
News and Yahoo News, potentially integrating up to 10,000 sources, may have
almost equal value.
The use of free data means that these systems may be provided at minimal
cost to the public and to countries that lack the resources to pay high subscription rates. For paid data, cost-effectiveness of various data sources becomes an
important issue. Data for HealthMap are acquired strictly through free news
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global infectious disease surveillance and detection
sources. Whether these data sources differ substantially from paid sources is the
subject of future evaluation.
Data Availability
The time interval at which these sites are updated can have critical implications for the efficacy of the public health response. Ideally the source should
provide timely reports. In reality, media reporting may be guided by external
factors such as a weekly health/science section or unrelated news events that
might delay reporting. For example, news volume is strongly affected by day of
the week, with high volume on Fridays and low volume on Sundays.
News media reports may also be subject to bias about which diseases are
covered. Our evaluation found that the richness of pathogen reporting across
news sources was substantial, with 66 unique infectious diseases reported through
Google News in the 20-week period (Table 2-1). However, we found that distribution of reports across pathogens (or pathogen evenness) was low, with a
substantial skew toward reporting of outbreaks of avian influenza and norovirus.
The more skewed distribution in the news sources is expected given the tendency
for the media to focus and sustain reporting on stories of public interest. We also
TABLE 2-1 Top Infectious Disease Alerts from the
HealthMap System, October 1, 2006–February 16, 2007
Disease Reported
Total Number
of Reports
Avian influenza
E. coli
Norwalk-like virus
Salmonellosis
Influenza
Dengue fever
Herpes
Cholera
Undiagnosed
Gastroenteritis
Pertussis
Rift Valley fever
C. difficile
Staphylococcal disease
Diarrhea
Legionellosis
Tuberculosis
Malaria
Chickenpox
Measles
661
492
242
217
169
133
118
81
78
46
52
46
33
32
29
28
28
26
25
25
SOURCE: http://www.healthmap.org.
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found that news outlets often picked up more common seasonal and endemic
conditions (e.g., epidemic influenza, dengue, E. coli, Salmonella). This is in
contrast to the ProMED system that explicitly avoids reporting on endemic infections—such as tuberculosis and HIV—or vaccine-preventable diseases (Madoff,
2004).
Geographic coverage of data sources also merits quantitative evaluation (Figure 2-5). During the evaluation period, 88 countries had reports of infectious
disease outbreaks, with the greatest reporting from the United States (n=1,346),
Canada (n=235), and the United Kingdom (n=226). Given that the analysis
included only English-language news sources, the skew toward English-speaking
countries is not surprising. However, it is also clear there is a bias toward reporting from countries with larger populations (e.g., China), numbers of media outlets,
public health resources, and availability of electronic communication infrastructure (approximated by number of Internet hosts).
Future Work in Data Acquisition
Gaps in population and geography covered by news sources need to be
understood and adjustments need to be made. For example, important gaps in
media reporting exist in tropical areas, which also have the greatest burden of
infectious diseases. Monitoring other Internet-based sources such as blogs, discussion sites, and listservs could complement news coverage. In particular, the
use of clickstream data and individual search queries is a promising new surveillance source (Eysenbach, 2006). Ultimately, informal news-based sources should
be considered as part of a comprehensive multistream surveillance system that
provides an integrated view of global health information.
Characterization
Although free and unrestricted websites have large quantities of useful information about infectious diseases, the information is not well organized. News
media output usually comes as unstructured free text, making analysis of the
geographic and temporal relationships between different reports and data sources
difficult. Automated disease and geographic location grouping is usually accomplished through natural language interpretation and automated text mining and
parsing. Search criteria can include disease names (scientific and common),
symptoms, keywords, and phrases. Once gathered, automated approaches for
initial filtering often require human verification.
Classifying Information
Extracting a pathogen name from a free text report presents a number of
formidable challenges. In HealthMap, we draw from a continually expanding
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FIGURE 2-5 HealthMap geographic coverage, October 1, 2006–February 16, 2007.
SOURCE: Brownstein (2006).
130
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131
dictionary of pathogens (including both human and animal diseases) to organize
unstructured and semistructured disease outbreak alert information. Locations are
extracted by matching geographic names with a master table of latitude and longitude coordinates of centroids of certain geographic areas, including countries,
provinces/states, and cities. In addition to reasonable performance and scalability,
a key advantage to this pattern dictionary approach is that it is translated relatively
easily to other languages: A different dictionary can be plugged in easily to the
existing architecture. A language expert is needed to perform the initial translation, refine the pattern library, help with capitalization and punctuation subtleties,
and provide other adaptations, but the basic approach can be re-applied without
major changes to the system. Furthermore, the language expert needs to have
minimal technical knowledge with respect to natural language syntax or software
development to contribute to the library.
Although effective for rapid matching, a number of hurdles need to be overcome. First, in the case where a word may have multiple spellings, for example,
diarrhea (common in the United States) and diarrhoea (common in the United
Kingdom), we stock the dictionary with multiple patterns for a single pathogen.
While look-up time does not increase substantially with the addition of patterns
to the dictionary, the disadvantage of the dictionary approach is that it requires a
priori knowledge management and allows identification only of locations and diseases already present in the database. Similar challenges exist for identifying the
precise geographic location of an outbreak, as geographic names and borders are
subject to change. The expansion and editing of the database requires extensive
and careful manual data entry. Another limitation of the look-up engine is that
it ignores pattern context. A good illustration is the use of “plague” in reports—
often news articles use it metaphorically, such as “Problems continue to plague
New Orleans cleanup effort.” If the look-up engine matches the word “plague”
alone, it will mark this alert as an outbreak of Yersinia pestis in Louisiana. We
mitigate this problem by including “to plague,” “a plague,” and other similar
strings as null patterns in the library so that the classifier will mask them.
Rating Information
Clearly, the article text contains the best indicators about the locations and
diseases of the event in question. However, blindly searching the text, while
increasing sensitivity, leads to excessive false positives. To mitigate this problem,
we process the input in stages: If the classifier cannot identify location and disease from the initial input provided by the feed, namely the modified headline, it
can request more text from the feed. For example, in the case of the Google News
aggregator, the system examines the headline, then the description, which usually
consists of the first one or two sentences of the article, and finally the publication name. Frequently, a publication in one area refers to events in another area,
making the publication name and location an unreliable source for the location
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global infectious disease surveillance and detection
of the alert. However, articles that do not refer to a well-known location, such
as “Suburban school closed after flu outbreak,” generally refer to a location near
the publication headquarters. By processing the input in stages, we reduce the
false positives of the first case while including more of the true positives of the
second case.
Future Directions in Data Characterization
Future work must focus on improving natural language processing capability to clearly identify the pathogen, filter nonpertinent reports and duplicates,
and enhance the spatial resolution of location. Ideally improvements in how
the source information is reported would vastly enhance characterization. For
example, structured annotation on the attributes of an outbreak by the article
author or source publication would remove the problems inherent with natural
language processing. However, given that data standards for news reporting are
not likely to be implemented in the short term, advanced text processing methodologies such as fuzzy matching and neural networks could have an important role
in enhancing current systems. Furthermore, reliance on an external geocoder with
consistently updated databases of geographic locations may be a better solution
(Croner, 2003). Although machine learning techniques are undoubtedly important, human analysis still has tremendous value, as exemplified by the Global
Public Health Intelligence Network (GPHIN) (Mawudeku and Blench, 2006)
and ProMED (Madoff and Woodall, 2005). The success of Wikipedia has shown
that leveraging collaborative human networks of trained public health professionals (such as ProMED subscribers and international groups of experts) could
be an ideal mechanism for classification, severity assignment, conflict resolution,
geocoding, and confirmation of reports on outbreaks of rare or even infectious
diseases of unknown identity (Giles, 2005).
Interpretation
While issues of acquisition and characterization have been addressed by many
systems, methods for interpreting these data are for the most part underdeveloped.
Current systems aggregate Internet-based news resources, but are limited in terms
of analytical tools available to the user. Development has been geared toward
knowledge management, where news on infectious disease is aggregated and
reorganized. Because of the magnitude of information collected, users could, over
time, become overwhelmed with an increasing number of false alarms. Thus, there
is a need to move from simple knowledge reorganization to an analytic approach
for disseminating timely yet specific signals. A number of strategies are available
to reduce the false alarm rates in these inherently noisy data sources.
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Multistream Interpretation
False alarms often can be reduced by thorough aggregation and crossv alidation of reported information on a particular disease outbreak. The motivation for such a meta-alert is based on the idea that multiple sources of information
on an incident can provide greater confidence in the validity or reliability of the
report than any one source alone. In HealthMap, the severity of a meta-alert is
calculated as a composite score based on: (1) the reliability of the data source
(e.g., increased weight to WHO reports and less weight to local media reports);
and (2) the number of data sources, with increased weight to multiple types of
information (e.g., discussion sites and media reports on the same outbreak).
For evaluation of multistream surveillance to be effective, basic characteristics such as sensitivity, specificity, and timeliness of different news source types
need to be quantified (Wagner et al., 2001; CDC, 2001; Reis and Mandl, 2003a;
Brownstein et al., 2005b; Bloom et al., 2007). In our evaluation, we used officially confirmed outbreaks obtained from WHO Outbreak News, available in the
public domain, as a “gold standard” indicator of an infectious disease outbreak
(WHO, 2007). We measured key detection characteristics of Google News reports
for 12 focused outbreaks over the 20-week period. Mean timeliness for Google
News, defined as the time between detection by the surveillance source and report
by WHO, was 12 days. However, actual timeliness varied widely from 102 days
earlier to 59 days after the WHO report. For example, a diarrheal outbreak in
Ethiopia was detected by the media nearly three weeks before the WHO report.
In contrast, a plague outbreak in the Democratic Republic of the Congo and a
Chikungunya outbreak in India were only reported in the media once the official
WHO report was released. Sensitivity, defined as the proportion of WHO alerts
detected by news data, was moderate, with 58 percent of the alerts reported in the
news. In contrast, we identified 267 unique alerts (country–disease pairs) from
Google News, revealing a high volume of reporting. Given that only a subset of
outbreaks is posted to WHO Outbreak News, the specificity of news data could
not be calculated given the current data sources. Without a better gold standard
of validated outbreaks, assessing false positives is difficult.
Statistical Interpretation
The value of news reports can be measured similarly to traditional surveillance data sources used for outbreak detection, where the goal is to distinguish
an abnormal pattern from a normal or expected one. Statistical methods for
outbreak detection include temporal pattern models such as statistical process
control (SPC) (Hutwagner et al., 1997) and autoregressive moving average models (ARIMA) (Reis et al., 2003), spatial models for geographic cluster detection
(Kulldorff and Nagarwalla, 1995; Brownstein et al., 2002; Olson et al., 2005),
and spatiotemporal patterns for detecting space-time interactions (Kulldorf et
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al., 2005). To apply these to monitoring Internet news sources, we must define
the baseline patterns and thresholds of reporting for which no action is required.
In this case, we expect a baseline level of random noise in news media reports
generated by case definitional issues, surveillance bias, and overreporting. The
generation of statistical signals therefore can be based on a set threshold of report
volume defined by modeling this baseline. Models can include factors such as
cyclical patterns (day of week, month, seasonal effects) and autocorrelation (Reis
and Mandl, 2003b; Brownstein et al., 2005a), as well as geographic and temporal biases of news reporting. Thresholds would be set by evaluating the tradeoff
between signal quality and timeliness.
Future Directions in Data Interpretation
Future work in modeling and data integration should also be directed at
improving risk assessment. For example, signals from unstructured online information sources can be integrated with other health indicator data to provide a
broader context for the alert. Pertinent datasets include mortality and morbidity
estimates, population density and mobility, and pathogen seasonality and transmissibility (Wilson, 1995; Altizer et al., 2006; Dowell and Ho, 2004; Grassly and
Fraser, 2006; Fraser et al., 2004). With the increasing importance of vectorborne
and zoonotic diseases (Gratz, 1999; Dobson and Foufopoulos, 2001; Brownstein
et al., 2004), consideration also should be given to inclusion of ecological data
such as distribution of arthropod vectors and animal host reservoirs, as well as
environmental predictors including climate and vegetation (Brownstein et al.,
2003; Colwell et al., 1998; Kitron, 1998). Combining these informal sources with
clinical and laboratory surveillance data should also be an important next step.
Such integration could yield a relevancy score for the report, define populations
at risk, and predict disease spread.
Dissemination
An important final consideration is how information from Internet-based systems should be disseminated. Clearly a critical audience is public health officials
interested in real-time updates of infectious disease status in their geographic
region. However, whether these systems should be freely available and open to
the public is an area of active debate. Travelers, for example, may have a keen
interest in up-to-the-minute knowledge about infectious disease activity at their
destination. For the general population, obtaining integrated real-time coverage
of a disease emergency is particularly challenging given disparate news and alert
sources. An unrestricted sentinel system dedicated to the aggregation and geographic display of current outbreaks could fill this information gap.
On the other hand, unrestricted access to this information could have severe
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economic impacts on the countries affected by the disease alerts. The risk is
especially elevated with fully automated systems that may not have the benefit of
informed human judgment. However, even with careful controls, any system can
generate spurious alerts. User restrictions may be the only way to guard against
unwarranted damage (Cash and Narasimhan, 2000). Furthermore, an open access
model might not be economically sustainable. GPHIN depends on subscription
fees to make any necessary improvements to the system. In contrast, HealthMap is
based on freely available data and is open to the public. However, a tiered approach
such as the one used by MedISys (Medical Intelligence System) where general
information is provided to the public based on free resources and more detailed
information pertinent to public health officials (including geographic detail) is
provided by paid subscription may represent a reasonable compromise. Information
access is a key consideration for the future development of these systems.
Another critical question is who ultimately should oversee these systems and
manage the information collected, especially given that issues of trust and reliability are paramount. At the moment, systems are being developed by international organizations, governments, and academic institutions. The current linkage
between surveillance by GPHIN and public health response by WHO’s GOARN
presents a very appealing approach. An initiative at Google.org, called the International System for Total Early Disease Detection (INSTEDD) project, aims to
develop a system that increases the number of languages and data sources available through GPHIN (Delamothe, 2006). INSTEDD could become a transparent
and publicly available resource independent of any government agency. How such
a system would be linked with existing public health infrastructure should be an
area of active consideration.
Conclusions
The growing use of informal electronic information sources highlights an
important paradigm shift in disease surveillance, expanding beyond traditional
public health systems. Although Internet-based informal sources on outbreaks
are becoming a critical tool for global infectious disease surveillance, important
challenges still need to be addressed. In particular, an unavoidable pitfall of a
system-of-systems approach is that it is inherently subject to the limitations of
the primary data collected by the individual component systems. Our preliminary
evidence-based evaluation of HealthMap suggests that aggregation of multiple
sources may counter this limitation by increasing sensitivity and timeliness while
reducing false alarms, in that assessments are not based on any single news outlet
alone. Because many of the places with the least technological adoption also carry
the greatest infectious disease burden, future system development should also
specifically address the digital divide to achieve more uniform and comprehensive
global coverage. A robust research agenda, continued organic evolution of existing and new technologies, and scrutiny through a rigorous evaluation framework
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global infectious disease surveillance and detection
will help ensure that the global public health enterprise maximally leverages
new electronic sources for surveillance, communication, decision making, and
intervention.
Acknowledgments
This work was supported by R21LM009263-01 and R01LM007970-01 from
the National Library of Medicine, the National Institutes of Health, and grant
number 200510MFE-154492 from the Canadian Institutes of Health Research.
USING CELL PHONE TECHNOLOGY FOR INFECTIOUS DISEASE
SURVEILLANCE IN LOW-RESOURCE ENVIRONMENTS:
A CASE STUDY FROM PERU
Pamela R. Johnson, Ph.D.15
Voxiva
David L. Blazes, M.D., M.P.H.16
Naval Medical Research Center Detachment
Summary
Basic routine health surveillance has been largely unachievable in most of
the developing world because of inadequate funding and public health training,
especially in resource-limited parts of Africa, Asia, and Latin America. Considering that many emerging diseases with pandemic potential first occur in the
developing setting (e.g., severe acute respiratory syndrome, or SARS and H5N1
avian influenza), enhanced surveillance systems in these countries must become
high priorities for safeguarding global public health. This presentation reports
on an innovative model using a cell phone- and Internet-based reporting system
that has been developed and tested to extend disease surveillance by the Peruvian
Navy along the coast and remote rivers of Peru. Alerta DISAMAR—the name
given to the system refers to the Health Department of the Peruvian navy—has
been fully operational in Peru since 2003. More than 600 individuals have been
trained and have used an Internet- and cell phone-based electronic system developed by Voxiva to report routinely from 42 land-based sites and 19 ships. More
than 80,000 cases and 31 outbreaks have been reported. Alerta DISAMAR represents a sustained, large-scale effort that leverages cell phones and related tech15 Co-founder
16 Director,
and Executive Vice President.
Emerging Infections Program, Lima, Peru.
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nological innovations to strengthen disease surveillance. Because mobile phone
networks are expanding so rapidly across the developing world, this model has
important lessons for strengthening disease surveillance in other low-resource
environments.
Background
The low-resource environments of most developing countries pose a particular challenge to global efforts to establish effective infectious disease surveillance
and detection. There is little question that these countries are important to global
surveillance. “Out of every 100 persons added to the population in the coming
decade,” Zlotnik wrote, “97 will live in developing countries” (Zlotnik, 2005).
Figure 2-6 shows countries sized in proportion to their populations. It shows how
significant the share of the world’s population is in China, Brazil, Nigeria, subSaharan Africa, and other countries in the developing world.
Infectious disease is disproportionately represented in these countries. Many
new and emerging infectious diseases—including SARS, H5N1, HIV/AIDS—
trace their origins to these often densely populated environments. However,
despite their demographic and epidemiologic significance, most developing countries, where microbial threats to global health are most likely to emerge, also
possess the weakest surveillance systems. The Government Accountability Office
(GAO), in a global review of surveillance systems, noted that:
Developing country systems are a weak link in the global surveillance framework. Surveillance systems in industrialized and developing countries suffer
from a number of common constraints, including a lack of human and material resources, weak infrastructure, poor coordination, and uncertain linkages
between surveillance and response. However, these constraints are more pronounced in developing countries, which bear the greatest burden of disease and
are where new pathogens are more likely to emerge, old ones to reemerge, and
drug-resistant strains to propagate. Weaknesses in these countries thus substantially impair global capacity to understand, detect, and respond to infectious
disease threats (GAO, 2001).
Over the past decade, a number of important efforts have been made to use
information technology to strengthen surveillance systems. Most have taken place
in developed countries where computers and Internet connectivity are readily
available. In addition, e-mail and the Internet have had a major impact in facilitating the growth of global networks such as the World Health Organization’s
(WHO’s) Global Outbreak Alert and Response Network (GOARN), ProMEDmail, and a number of global disease-specific surveillance networks (Heymann
and Rodier, 2004).
Despite the evident importance of information technology (IT) in these
Copyright © National Academy of Sciences. All rights reserved.
broadside
FIGURE 2-6 Distribution of the earth’s population.
SOURCE: Worldmapper (2007). See http://www.worldmapper.org.
Reprinted with permission. © Copyright 2006 SASI Group (University of
2-6
Sheffield) and Mark Newman (University of Michigan).
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139
examples, IT has yet to realize its full potential for strengthening the surveillance systems of countries in the developing world. Even where computers exist,
inadequate power and lack of Internet coverage outside major towns and cities
has meant that in most developing countries routine surveillance systems are still
largely paper based, and transmission is slow. Health officials in capital cities and
towns may be easily linked to global networks and colleagues in other major cities, but communicate less easily with health facility staff in their own countries.
Until recently, there was no practical, measurable way to bridge the digital
divide between the cities and the poor and rural areas in these countries, where
most of the population lives. Nonetheless, a major recent review of disease
priorities led by The World Bank holds out a vision of the future of disease
surveillance:
Public health agencies, ministries of finance, and international donors and organizations need to transform surveillance from dusty archives of laboriously collected after-the-fact statistics to meaningful measures that provide accountability
for local health status or that deliver real-time early warnings for devastating
outbreaks. . . . Information technology and informatics can help in attaining
this vision . . . technology can facilitate the collection, analysis, and use of
surveillance data, if data standards are developed and compatible systems are
established. . . . technology such as cell phone-based systems could accelerate
collection of key data (for example, occurrence of a viral hemorrhagic fever
outbreak) (Nsubuga et al., 2006).
The explosive growth of mobile telephone networks in the developing world
is already a dramatic success story. According to the International Telecommunications Union (ITU), Internet connectivity is growing at a good pace, but the
reality is that cell coverage is growing much faster. In the developing world there
are 1.2 billion phones and a million new mobile phone subscribers every day.
Approximately 80 percent of people who live today are within reach of a mobile
phone signal, according to the ITU. Half of all households will have phone access
in the next decade, and 90 percent of the world will be covered by 2010. In Latin
America, there are more than 270 million mobile phone users today. The industry
estimates that within the next 3 years, 75 percent of people in Latin America will
own a cell phone. Africa shows the most dramatic growth. Over the past 5 years,
growth has averaged nearly 60 percent a year, with nearly 76 million subscribers
at the end of 2004.
Voxiva was founded in 2001 to find practical ways of using information technology for health and development in low-resource environments. We reviewed
a variety of pilot projects that were seeking to extend the benefits of the Internet
using a variety of individual devices, including personal digital assistants (PDAs)
and satellite dishes. However, we did not find any practical, measurable, and
sustainable strategy to support data collection and communication with points
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global infectious disease surveillance and detection
of service. It was and in many countries remains a paper-based world, with few
benefits of IT reaching large scale.
Voxiva’s founders recognized the potential of the growth of cellular networks
to develop a measurable, sustainable approach that could support public health
and development. Working with a variety of public health agencies, including
health officials in the U.S. and Peruvian navies, Voxiva developed innovative software that allows health professionals to enter and access data using the Internet,
a cell phone, or other devices. The software makes it possible to write a survey
and to make that survey available in multiple formats so users can use the tools
they have and the most convenient, cost-effective means to respond.
Figure 2-7 illustrates the approach that Voxiva has taken to optimize the
use of the existing infrastructure of personal computers (PCs), Internet, cell
phones, fixed phones, pay phones, PDAs, smart phones, and paper to create networked data collection and communications surveillance systems in low-resource
environments.
Over the past six years, we have learned a number of lessons for building IT
systems for use in low-resource environments, leveraging cell phones and other
forms of information technology.
Building on Available Infrastructure
The global mobile phone network is increasingly the most important globally
deployed communications infrastructure that covers the developing world. As fast
growing and highly successful local businesses, telecommunications companies
provide global infrastructure for data transmission and communication that is
inherently sustainable. As a result, the health sector no longer needs to build and
maintain its own infrastructure to transmit data and support communication with
its network of health facilities.
Hardware is also increasingly available. Health ministries, states or provinces, and increasingly districts have computers and at least intermittent Internet
access. In addition, the dramatic expansion of mobile phone usage has put a
simple “terminal” within the reach of many if not most health workers—one that
can be used to enter data, respond to surveys sent by text messages, and send and
receive alerts. Providing a toll-free number that people can call with their own
mobile phones is a quicker and cheaper approach to expanding a surveillance
network than buying, equipping, maintaining computers, and paying for power
and Internet access for all health facilities.
By building on this global telecommunications infrastructure and available
hardware, it is possible to rapidly create large-scale integrated networks that can
do basic reporting without large-scale new investments in acquiring, installing,
and maintaining technology. Over time, the infrastructure will grow—but most
countries already have enough hardware to begin.
As one example, Voxiva was able to support the national scale-up of
Copyright © National Academy of Sciences. All rights reserved.
Cell
phone
PDA/
smartphone
Phone
Pay
phone
Paper
Local
applications
Copyright © National Academy of Sciences. All rights reserved.
FIGURE 2-7 Being able to enter and access data from any available communications channels can optimize the use of existing infrastructure.
SOURCE: Voxiva. Reprinted with permission of Voxiva.
PCs/
Internet
SAMPLE DATA
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Rwanda’s national HIV/AIDS program with a monitoring system that allows
health facilities to report program indicators and register new patients. Without
any new investment in hardware, Rwanda was able to rapidly increase its electronic reporting system from 12 facilities to 146 sites. Ninety percent of the sites
report program indicators and register patients using the phone. They use their
own cell phones, call a toll-free number—the first in Rwanda—log in using their
password, and enter basic data digitally using the keypad. Over time, more and
more sites will get computers and Internet connectivity, but the program was able
to reach national coverage rapidly without waiting.
Multiple, Redundant Technologies
We have found that no single solution or hardware works in all environments, for a variety of reasons. Power is a major constraint, especially in the most
remote environments and poorest countries. The cost of connectivity remains
high in many countries. Maintenance and support for computer hardware and
software are costly and in short supply. Actual needs for bandwidth and analytic
power vary depending on how users are using the data collected. For many needs,
paper records will be the base system. Having the choice of different electronic
devices means that one can optimize the use of available hardware and allows
health professionals to enter and access data using the access means they have.
This also creates redundancy: If the Internet is not available, it is still possible to
do basic reporting via the phone.
Electronic Data Capture at the Source
Paper systems rely on copying information at the source, relaying it, then
entering and aggregating information at higher levels; this system of data transmission is error prone and makes it difficult to trace data and cases back to their
source. If data can be entered and confirmed at the source, this in itself can
enhance quality. If data can be transmitted to a central database, reviewed and
approved at higher levels (e.g., at the district level), and also be made rapidly
available to others who need it, the burden and risks associated with entering data
multiple times are reduced.
Rapid Transmission of Data
Most surveillance systems rely on physical transmission of data via mail
or “sneaker net” with people bringing the forms to a monthly meeting or on a
periodic visit. More urgent information is transmitted via individual phone or
radio calls and recorded centrally. Electronic transmission data can cut the time
and cost required for transmission dramatically. Although this is important for
routine surveillance, it is even more vital for an event, such as a serious outbreak
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or pandemic, when the situation on the ground could change rapidly. Electronic
submission of data in near real-time information could help decision makers
make much better decisions about allocation of resources in a situation of rapid
change.
Shared Database, Role-Based Access
If data are collected at the source and transmitted to a core database, organizations can make that data available to authorized users according to the specific
roles they play. For example, the same set of data could be viewed in a variety
of ways:
• Health staff can get confirmation that their report has been received,
notification of cases of interest from neighboring locations, and results of a case
investigation;
• A district health official could see reports from health clinics and posts
immediately—then edit or approve them;
• Senior health officials could review aggregate data;
• Surveillance officers could get lists of nonreporting sites; and
• Outbreak investigation teams or vaccination teams could get short message service (SMS) or e-mail alerts about suspected cases of measles or potential
outbreaks.
Data, collected once and transmitted to a central database, can be used many
times. Furthermore, data can be presented in standard templates, basic reports,
and maps or exported for additional analysis.
Communication Plus Feedback
An extended electronic network can also facilitate communication and feedback that is vital to the supervision and motivation of a distributed network.
Automated messages can be sent by multiple means—e-mails, text messages,
voice mails, alerts—and accessed through the available technology.
Build Human Capacity
Information technology alone is no silver bullet. Building a surveillance
system in any environment requires an investment in the training staff at all levels. Well designed information systems can help, with tools such as validation
rules, reminders, and online access to guidelines and training materials. Such
tools could be even more helpful in situations where health staff are not well
trained. However, the best designed system cannot detect disease or respond to
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an outbreak without the right processes and people; at its core, a surveillance
system will always be about the people who use it. The role of technology should
be to empower networks of clinicians, nurses, and other health workers to fully
participate in this important enterprise of global disease surveillance.
The same technological approach leveraging cell phone technology is being
used for a variety of purposes. It has been used for syndromic surveillance in
schools in San Diego and Washington, DC. It has been tested in the Canete
Valley in Peru and in Baghdad and Basra, Iraq, and is being developed with
the Ministry of Agriculture in Indonesia to create a system to strengthen animal
surveillance. In Latin America, it is being used to monitor national HIV/AIDS
programs, track adverse events, and support public safety (Olmsted et al., 2005;
Curioso et al., 2005).
Alerta DISAMAR: A Case Study in Infectious Disease Surveillance
Background
In fall 2001, at a time when other events in the world raised awareness of
microbial and other threats, there was an outbreak of P. falciparum malaria at a
remote naval base in the Amazon jungle basin of Peru that led to several deaths.
As in some other countries, the existing surveillance system was underdeveloped
and primarily paper based; it was not unusual for reports to take a month to get
to authorities in Lima.
Primed by these events, the Peruvian navy, the U.S. Naval Medical Research
Center Detachment in Lima, and the Peru-based office of Voxiva developed a
joint project. In January 2003, they initiated Alerta DISAMAR, a novel electronic
disease surveillance system. This experience in implementation has been exciting
to observe from the ground up, and this case study describes some of the lessons
learned during deployment of this surveillance system in Peru.
Pandemics by definition involve the global dissemination of disease. Military
populations historically have been involved in the dissemination of a number of
infectious diseases, including their well-documented role in the spread of H1N1
influenza in 1918–1919 (Oxford et al., 2005). There are also examples from
antiquity of troop movement roles in the spread of smallpox, cholera, measles,
syphilis, and plague (McNiel, 1977). More recently, high rates of HIV infection
have been seen in sub-Saharan African militaries, and this population certainly
contributes to ongoing transmission (Whiteside and Winsbury, 1996). Despite the
known risks of disease transmission among highly mobile armed forces, these
groups remain among the most poorly tracked populations in many developing
nations. The combination of undersurveilled military populations and dangerous
transmissible diseases seems the perfect recipe for a pandemic.
Military personnel are a very good population to place under surveillance for
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emerging infectious diseases (Chrétien et al., 2007). They serve as ideal sentinel
populations due to their expeditionary mission, their frequent travel to remote
locations, and their interactions with local populations.
A number of challenges exist in implementing an electronic disease surveillance system, some cosmopolitan and some unique to resource-limited settings.
The dubious observer may even ask if conducting surveillance in a resourcelimited setting is even feasible when the potential pitfalls and challenges often
seem insurmountable. The first challenge is to create a system that is complementary and not duplicative of existing surveillance systems. Creation of parallel
surveillance systems can paradoxically lead to the failure of both the established
and the new systems because limited funds and effort can be diluted between the
two systems with neither functioning effectively (Nsubuga et al., 2006). Second,
one must convince the stakeholders in the population under surveillance that their
efforts are useful and their valuable time is not wasted. To accomplish this, one
must make sure that meaningful data are returned to the end users of the system,
and in a timely fashion so that consequential action may be taken to limit the
effect of a disease or condition. An example might be the timely detection of
an influenza outbreak in a closed facility where case isolation, enforcement of
hand/cough hygiene, and antiviral chemoprophylaxis may limit the spread of this
contagious illness.
Additionally, a disease surveillance system in the developing setting must
be cost-effective, with few recurring expenses in order to assure sustainability.
Many countries in the developing world have limited funds to spend on public
health, and these are often exhausted in responding to crises rather than invested
in preventive strategies. Finally, a disease surveillance system in the developing
setting must be able to function in remote locations and austere conditions.
With regard to the situation in the Peruvian navy, we focused our attention
on a population that was not under surveillance, and applied novel technology in
the attempt to create a model that could be disseminated to other resource-limited
settings worldwide. Furthermore, in establishing this surveillance system, we
have attempted to change the culture within this population to approach disease
characterization and transmission from a broader perspective, that of epidemiology and public health.
The System
The Alerta electronic disease surveillance system uses a countrywide network of health-care facilities that encompasses more than 95 percent of the
population of the Peruvian navy and its civilian dependents in most regions of
Peru (over 120,000 people). Some of these sites are tertiary care facilities in the
capitol city of Lima, but the majority are smaller, more remote, and less capable
clinics that exist throughout the country. Figure 2-8 shows a typical clinic site in
one of the austere areas where this system functions.
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FIGURE 2-8 Health-care personnel collect data.
SOURCE: Jose Quispe, Peruvian Navy. �������������������������������������
Reprinted with permission from NMRCD.
2-8
The network consists of 43 fixed sites throughout Peru and 19 ships both on
the coast and on rivers in the jungle (Figure 2-9). The sites use a diverse range
of reporting techniques, with 12 sites routinely reporting by radio relay, 27 by
telephone, 15 by Internet, and 8 by telephone or Internet.
Data flow from individual clinics to the central operations hub in Lima. The
actual data flow from the field is described in Figure 2-10. Data are collected on
standard clinical forms during patient encounters, then entered into the system by
nurses or physicians via cell phones, toll-free public telephones, or by Internet if
accessible. Several extremely remote sites are beyond the cellular footprint, and
in these, the Peruvian navy personnel use a radio phone to relay data to the next
nearest site that has either a cell phone or access to public phones or the Internet.
Occasionally, satellite phones are used if they are available to enter data through
the toll-free telephone system.
The data collected through this system are often the only systematic representation of the epidemiology of diseases within the Peruvian navy. This has
allowed baseline levels of disease to be set, and allocation of scarce resources to
be assigned based on rational data rather than assumptions. The system collects
rates of the 29 reportable illnesses for the Peruvian Ministry of Health (MoH) as
well as some militarily relevant cases such as training-related injuries. The data
generated by this system are invaluable to both the Peruvian navy and the MoH
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147
FIGURE 2-9 Alerta network.
SOURCE: Dr. Carmen Mundaca, Naval Medical Research Center Detachment (NMRCD).
Reprinted with permission from NMRCD.
because they report disease rates from areas2-9
of the country where the MoH does
not have a significant presence.
The data are captured and displayed in real time on a web-based platform.
Several automated outputs are generated so that feedback is given almost immediately to the stakeholders in this process, either by electronic mail or short message service (SMS) messaging to cellular phones. Features include automated
outbreak detection via algorithms, graphical representation to assist clinicians,
and baseline trends.
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Copyright © National Academy of Sciences. All rights reserved.
Mobile cell phone alerts
Data available in real time
2-10 broadside
Outbreak detection
Evaluation of the system
Enter data by phone, Internet, or radio daily and
biweekly according to the disease
FIGURE 2-10 Data flow from the field.
SOURCE: Dr. Carmen Mundaca, NMRCD. Reprinted with permission from NMRCD.
Baseline trends
Automated reports
generated
Health-care personnel collect data
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Discussion
A complete evaluation of the ALERTA surveillance system was performed
for the period from January 2003 to November 2006, and is the subject of a separate publication (Mundaca et al., 2005). This evaluation focused on three phases:
implementation (first year), consolidation (second year), and expansion (third and
fourth years). The methods for this evaluation are based on the Centers for Disease Control and Prevention’s (CDC’s) Updated Guidelines for evaluating public
health surveillance systems (CDC, 2001). The tasks involved in evaluating this
system are adapted from the steps in program evaluation in the Framework for
Program Evaluation in Public Health (CDC, 1999), as well as from the elements
in the original guidelines for evaluating surveillance systems (CDC, 1988). This
assessment was based on information from several data sources, including the
main database generated by the system platform, quarterly morbidity reports from
the Peruvian navy, outbreak reports, information from Voxiva personnel, focus
groups, training evaluations, and surveys applied to stakeholders. Highlights of
this evaluation are included below, and include usefulness, sustainability, stability, and flexibility.
The Alerta system has been invaluable to the Peruvian navy. Since its implementation through November 2006, 80,747 events have been reported, including
3,789 in 2003; 9,454 in 2004; 25,246 in 2005; and 42,258 through November
2006. The Peruvian navy has embraced Alerta DISAMAR and the culture of
epidemiology surrounding it. As one example, the Peruvian military leadership
asked all the services for the number of cases of dengue fever in the past year.
The navy was the only group that could provide a number and distribution within
the week. They searched Alerta DISAMAR’s database and were able to provide
the information rapidly. Since this incident, the other branches of the Peruvian
military have decided to implement Alerta. Reports such as these have allowed
baseline levels of disease to be determined, and for the first time have identified outbreaks of disease in a timely fashion so that diagnoses can be made and
interventions enacted.
One of the most important questions to ask in evaluating a system is whether
that system is doing what it was intended to do. Over the past four years, we
have detected more than 31 outbreaks, including diarrhea, dengue, influenza,
and tuberculosis. The outbreak of diarrhea depicted below is an example of an
outbreak reported using the system (Figure 2-11), and there have been several
outbreaks of acute respiratory infections that have initiated outbreak responses at
recruit training camps. One of these identified outbreaks (mumps) led the Ministry of Health (MoH) to conduct active community surveillance that uncovered
an ongoing outbreak in the civilian population that mirrored that found in the
Peruvian navy.
Timely detection of outbreaks of disease allow accurate laboratory diagnoses to be made, and with a firm diagnosis, a viable response can be fashioned
Copyright © National Academy of Sciences. All rights reserved.
Copyright © National Academy of Sciences. All rights reserved.
21
26
31
36
41
Oct
46
Nov
51
Dec
Jan
4
Feb
9
Mar
14
Apr
19
May
24
Jun
Epidemiological week
0.0
16
Sep
0
11
Aug
40.0
6
Jul
40
1
Jun
80.0
49
May
80
44
Apr
120.0
39
Mar
120
34
Feb
160.0
Jan
160
Nov Dec
200.0
Oct
Monthly incidence
200
Sep
Weekly number of cases
2-11 broadside
FIGURE 2-11 Outbreak of diarrhea as reported by the system.
SOURCE: Dr. Roger Araujo, NMRCD. �������������������������������������
Reprinted with permission from NMRCD.
Number of cases
ADD Ancon Base
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Incidence x 1,000 inh x month
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151
that hopefully will attenuate the outbreak. The Naval Medical Research Center
Detachment (NMRCD) has been able to marry Alerta to molecular and microbiologic diagnostics in a number of these outbreaks, including the use of rapid
antigen detection testing for influenza.
In addition to outbreak response, we have also provided training in basic
epidemiology and more advanced field epidemiology. We have trained more than
600 public health personnel in the Peruvian navy in basic epidemiology and the
use of this electronic disease surveillance system. Throughout South America, we
have also trained more than 1,300 epidemiologists in the basics of outbreak detection and management. The objectives for these courses and the entire curriculae in
Spanish and English are available at no cost on the Web (Lescano et al., 2007).
The following attributes of the Alerta system were included in the evaluation process:
• Simplicity: Description of the data flow; estimated time for the reporter
to collect information and analyze the data; staff training requirements; and time
spent on the maintenance of the electronic platform.
• Flexibility: Number of reporting sites added per year; cost and time
required to add new sites; ability to add new diseases to the reporting template.
• Data quality: Reporting rate (percentage of sites that report per total
number of sites); percentage of complete reports; error rate (number of errors/
number of reports); error rate per site (number of errors/total number of sites per
week).
• Acceptability: Personnel surveys after training courses; number of personnel who report per site; mean time after training to achieve a timely report.
• Representativeness: Coverage (percentage of Naval population covered
by the system); characteristics of the population.
• Timeliness: Percentage of sites that report on time and percentage of
outbreaks detected on time; average of days to report.
• Stability: Number of system failures; percentage of time that the system
is fully operational; actions involved with repairs in the system.
• Sustainability: Joint responsibilities; relationship with the Peruvian navy;
incentives; costs assumed by each part; problems and requirements to sustain the
system.
Overall, the Alerta electronic disease surveillance system has been embraced
by the Peruvian navy and has transformed public health preparation and response
in this population. Both the Peruvian navy and the NMRCD laboratory have
contributed personnel, resources, and significant time to ensure optimal performance. The implementation of this system has not been without pitfalls, and
many challenges persist. However, the significant progress illustrates how horizontal partnerships and small projects can generate measurable improvements in
epidemiologic capability.
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global infectious disease surveillance and detection
This quote from a U.S. navy physician sums up the experience in Peru:
The introduction of Alerta has led to early outbreak identification/response, timely
case management, and increased review of clinical procedures within reporting
units. . . [It is a] working model for similar larger scale international programs
Alerta is a simple, near real-time disease surveillance model for countries in all
stages of communications technology development (Lescano et al., 2003).
Clearly, to respond to and control a potential pandemic, all regions of the
world need fully functional public health systems. These systems require careful
networking of many components, including reliable disease surveillance, accurate
local diagnostics, rapid medical response capability, and fluid cooperation and
communication among local and international partners.
Some components of successful public health strategies are present in
the U.S. Department of Defense Global Emerging Infections Surveillance and
Response System (DoD-GEIS). This system is a decade-old DoD program initiated in response to President Clinton’s directive in 1996 that mandated the development of a global system to track, control, and respond to potential pandemic
infections. It generated, among other things, the electronic disease surveillance
system described above (White House, 1996). GEIS serves as just one component
of a growing network of public health assets that are increasingly being used to
control infectious diseases with pandemic potential, complementing many global
public health community efforts (Chrétien et al., 2006).
The Alerta model implemented in Peru has a number of dimensions that
have contributed to its success:
• Committed leadership in all parties;
• A regulatory regime that specified reporting requirements;
• A practical use of information technology that maximized the use of available telecommunications and computing infrastructure;
• Real-time data collection from points of service and automated reports
and notification;
• Live database for continuous analysis and investigation;
• Links to laboratory and investigation capacity;
• Training and support of a distributed network of clinicians and other
health workers; and
• Mobile technology accessible to virtually everybody in Peru—if not individually then through a Navy command with cell phones and Internet access.
The approach that was developed and tested in Peru is now being expanded
with support from the U.S. DoD Southern Command to five neighboring countries: Bolivia, Colombia, Ecuador, Paraguay, and Uruguay. In addition, Voxiva is
part of a public–private partnership with the GSM Association, the largest asso-
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ciation of mobile phone operators (more than 650 mobile phone operators and
2 billion subscribers worldwide) to extend the benefits of this network in service
to public health. Hopefully this can provide not only a model of working in the
field, but also a model of cooperation between public and private entities.
Acknowledgments
The results reported derive from the common vision and hard work of a
number of individuals in the Peruvian and U.S. navies and Voxiva as well as
the support of the DoD-GEIS program. Key individuals include Drs. Carmen
Mundaca, Roger Araujo, Tanis Batsel, Rafael Elgegren, Ernesto Gozzer, Patrick
Kelley, Andres Lescano, Monica Negrete, and Mario Ortiz.
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Detection and Diagnostics
OVERVIEW
Workshop presentations on infectious disease detection and diagnostics surveyed current capacity, needs, and challenges; anticipated forthcoming developments; and imagined a future in which diseases can be diagnosed prior to the
appearance of symptoms (see Summary and Assessment).
Diagnostics for Developing Countries
The session began with a reminder from Mark Perkins of the Foundation for
Innovative New Diagnostics (FIND) that while emerging diseases and bioterrorism threaten public health, infectious diseases such as tuberculosis and malaria
have long imposed a severe burden on the developing world. In their contribution
to this chapter, Perkins and Peter Small of the Gates Foundation discuss the need
for rapid, accurate, inexpensive, robust diagnostics in developing countries—a
need that could be met by recent advances in genomics, proteomics, and materials
science if there was a profitable market. To fill this gap, FIND guides the development and adoption of novel diagnostic products for diseases of the developing
world in much the same way as public–private partnerships have been established
to produce drugs and vaccines for low-resource settings. With FIND’s support,
companies that produce low-cost diagnostics for use in developing countries
realize sufficient cost savings (in manufacturing, approval procedures, and marketing) to sustain profits.
158
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Rapid Diagnostics
Soldiers at risk of contracting infectious disease—either from the natural environment or from bioweapons—need diagnostics that are rugged, rapid,
and easy to use, according to speaker Mark Wolcott of the Diagnostic Systems
Division at the U.S. Army Medical Research Institute of Infectious Diseases
(USAMRIID). In their contribution to this chapter, Wolcott and co-authors discuss the rationale, design, and development of rapid diagnostic assays for infectious diseases. They offer brief, comparative descriptions of a variety of platform
technologies that in the future may be combined to produce comprehensive, integrated diagnostic systems—perhaps in the guise of miniaturized “labs on chips”
that process samples, perform assays, and automatically report their results. “As
technologies mature and new technologies are developed, rapid infectious disease
diagnostics will become available and practical,” the authors predict.
Rapid diagnostic tools are also improving infectious disease surveillance
in animals. Workshop presenter Alex Ardans, who directs the California Animal Health and Food Safety Laboratory System, described the development of
polymerase chain reaction-based (PCR-based) assays to screen for diseases that
have caused devastating outbreaks in livestock, such as exotic Newcastle disease
(END) in poultry and foot-and-mouth disease (FMD) in cattle. California also
developed a highly efficient tuberculosis testing program after the disease was
detected in several of the state’s large dairies.
Based on such experiences, Ardans argued that the state’s laboratory system
plays its most crucial role when recognizing and responding to unusual disease
events. For example, following a recent END outbreak among fighting cocks,
whose handlers worked in and spread the disease to commercial poultry operations, the laboratory optimized an existing real-time PCR assay for END that
was used to perform more than 85,000 tests (Crossley, 2005). Such emergencies
present unique opportunities to improve disease diagnosis, Ardans said, although
not necessarily with the latest technology. He noted that laboratory researchers, in
pursuit of the source of E. coli O157:H7 following a recent outbreak in spinach,
discovered that a gauze swab used to sample irrigation waters for contaminants
performed better than newer concentration devices.
Emerging Diagnostics
Although Koch’s postulates remain diagnostic standards, adapting them to a
vastly expanded understanding of disease states has become increasingly problematic, observed presenter Ian Lipkin and co-author Thomas Briese of Columbia
University’s Jerome L. and Dawn Greene Infectious Disease Laboratory. Their
paper discusses contemporary problems in proving causality, and illustrative case
studies that reveal how these challenges are shaping pathogen surveillance and
discovery. The authors also provide a taxonomy and comparative guide to proven
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and proposed methods for characterizing infectious agents without recourse to
cultivation, including two platforms of their own creation: MassTag PCR and the
GreeneChip. In the future, Lipkin and Briese predict, substantial advances against
chronic disease will occur “not from technical improvements but from investments in prospective serial sample collections and an appreciation that many
diseases reflect intersections of genes and environment in a temporal context.”
Pre-Symptomatic Diagnosis
Imagining a future in which bioterrorism agents are continually reengineered
to elude standard detection and diagnostic methods as well as therapeutics,
speaker and Forum member Stephen Johnston offers a model of diagnosis for
exposure to a pathogen before symptoms appear: a host-based detection system,
capable of analyzing hundreds to thousands of components in samples of blood,
sputum, or urine, and thereby capable of detecting any type of engineered or
natural threat agent. In the final paper of this chapter, Johnston discusses the
feasibility of developing such a system and its potential not merely to detect
biothreats, but to “convert standard health practice from one that treats symptoms
to one that detects disease very early—even presymptomatically.”
PARTNERING FOR BETTER MICROBIAL DIAGNOSTICS
Mark D. Perkins, M.D.
Foundation for Innovative New Diagnostics
Peter M. Small, M.D.
Bill and Melinda Gates Foundation
Timely and accurate diagnosis is critical to the global efforts to prevent and
treat infectious diseases. And yet, those on the front lines of this battle struggle
to make do with inadequate and antiquated testing technology. For example, a
100-year old test is used to diagnose tuberculosis, a disease that kills someone
every 16 seconds, and precious new antimalarial drugs are being rolled out with
the same diagnostic imprecision that currently mistreats several hundred million
cases every year. The tragic reality is that diagnostic uncertainty exacts a huge toll
in morbidity and mortality. Reliance on underperforming diagnostic technologies
limits the control of the world’s greatest killers, especially in settings with high
Reprinted with permission from Nature Biotechnology. Copyright 2006 Nature Publishing Group.
Perkins MD, Small PM. 2006. Partnering for better microbial diagnostics. Nature Biotechnology
24(8):919-921.
Chief Scientific Officer.
Global Health Program.
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human immunodeficiency virus (HIV) prevalence. We contend that innovative
mechanisms are needed to produce, develop and deploy new and better diagnostic
tools for infectious diseases in developing countries.
Global Public Health Goals at Risk
Acknowledging the impact of the global tuberculosis epidemic in the early
1990s, the World Health Assembly of the World Health Organization (WHO;
Geneva) declared tuberculosis a global emergency and ratified goals for case
detection and cure under the DOTS (directly observed therapy shortcourse)
strategy by the year 2005. Although important successes in fighting tuberculosis
have been achieved in recent years, reliance on weak diagnostic tools has slowed
progress. Case detection targets for smear-positive tuberculosis have not been
met, and fewer than 25 percent of all cases are now detected and reported as
smear positive (WHO, 2004). The data available suggest that the Millennium
Development Goal of halving tuberculosis prevalence by 2015 also cannot be
achieved universally without improved methods for diagnosing tuberculosis (Dye
et al., 2005).
The weaknesses of standard diagnostic tests for tuberculosis are well documented. Even in controlled research settings, the average sensitivity of sputum
microscopy for pulmonary tuberculosis is only 60 percent in immunocompetent
populations, and it is substantially lower among people infected with HIV. Conventional culture methods are so slow that testing often loses clinical relevance,
and the poor predictive value of the tuberculin skin test renders it essentially
worthless in disease-endemic areas. The weaknesses of the available diagnostic
technologies are only amplified in high-burden countries, which typically have
insufficient infrastructure and inadequate staffing.
Reliance on inadequate diagnostic tools cripple TB control efforts. Because
of limited access to diagnostic services and the low sensitivity of conventional
testing, patients in many high-burden countries remain undiagnosed for three to
six months (Madebo and Lindtjørn, 1999; Liam and Tang, 1997). These delays
result in increased morbidity and mortality, mounting costs combined with loss of
work, and continuing tuberculosis transmission to families and communities.
Unlike tuberculosis, which requires months of treatment to cure, malaria
can be treated with a few doses of unsupervised treatment. This dramatically
reduces the motivation to confirm the diagnosis. Microscopy for malaria is
notoriously difficult, and experienced microscopists give substantially different
results on up to a third of all slides. In most settings where malaria is endemic,
quality microscopy is poorly available and malaria treatment is given by default
to almost all patients with fever. Fever is an exceedingly common symptom in
the tropics, and an estimated 800 million malaria treatments are given each year
for fevers, the great majority of which are not caused by malaria (Amexo et al.,
2004). This massive mistreatment of hundreds of millions of people results in
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the fatal under-treatment of other diseases, such as pneumonia and sepsis, which
present with similar symptoms.
Having watched at least two generations of malaria medicines fall to mounting drug resistance, the international malaria community has called for greater
diagnostic accuracy before treatment, especially as expensive artemisinin-based
therapies are introduced. In 2004, the WHO recommended that malaria should be
confirmed by parasitologic examination before treatment in all patients older than
five years of age. In this setting, the development of simple and rapid diagnostic
tests (RDTs) that can detect circulating Plasmodium antigens in a drop of fingerprick blood is a key recent development.
The success of RDTs in improving the targeting of drug therapy, and their
acceptance in malaria management by remote health workers and patients, will
depend on the reliability and accuracy of the tests. There are now more than three
dozen manufacturers of such tests, many of which show inadequate sensitivity,
thermostability and geographic applicability. Though RDTs are now in wide use
in some areas, the lack of true performance data on most of these tests, the variability in published performance of others and the lack of a global quality assurance mechanism has generated chaos and confusion with regard to test selection
and has resulted in many end-users rejecting test results in favor of presumptive
treatment.
The lethal convergence of these diseases and HIV exacerbates the negative
impact of weak diagnostic tools. The rise of HIV in tuberculosis-endemic settings dramatically increases tuberculosis incidence, the number of symptomatic
individuals and the pressures on already overburdened health systems. HIV
coinfection decreases the sensitivity of microscopy for TB at the same time that
it increases the urgency for rapid diagnosis and treatment. From South Africa
to Brazil (Pronyk et al., 2004; Gutierrez et al., 2002), 30 to 50 percent of HIVinfected people die with undiagnosed tuberculosis, and Mycobacterium tuberculosis is now a leading cause of bacteremia in febrile patients visiting emergency
rooms in sub-Saharan Africa (Archibald et al., 1998). Fever in HIV endemic
areas cannot be assumed to be benign if nonmalarial. Thus, for many countries
burdened by HIV, the need for improved diagnostic tests is increasingly urgent.
New Opportunities
Recent trends in science and technology, and in the diagnostics industry,
indicate that there may be important new opportunities to improve diagnostic
tests suitable for developing countries. Availability of the complete genomic
sequence of M. tuberculosis allows a comprehensive assessment of potential
diagnostic targets. Massive investment in biodefense has generated a range of
diagnostic technologies intended for front-line use. The growing diagnostics
industry can develop new diagnostic tests at a fraction of the cost and time needed
to bring drugs and vaccines to licensure.
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Motivated primarily by the small but significant market in industrialized
countries, the tuberculosis diagnostics industry has produced several new tests
in recent years. For example, shortcuts around the slow growth of M. tuberculosis using phage-based or molecular methods allow tuberculosis detection and
screening for rifampin resistance within 48 hours (Albert et al., 2002; Johansen
et al., 2003). Other new tests exploit tuberculosis-specific proteins to detect latent
infection with much improved specificity, especially in BCG (BacilleCalmette
Guérin)-vaccinated populations (Lalvani et al., 2001; Mori et al., 2004). Likewise, for malaria diagnosis, several rapid immunochromatographic tests detecting
Plasmodium antigens in blood have been developed over the past 15 years, and
they now reach a market of some 25 million people.
Forging a Public–Private Initiative
Market forces alone, however, will not yield the diagnostic tools needed to
improve global health. Private companies often avoid developing products that
will primarily be used in developing countries out of skepticism about the return
on their investment. Developing countries have little capacity to pay the higher
prices typically attached to new products, even when these costs result in overall
savings to health care systems. The processes by which these countries license,
purchase, and distribute products are often inadequately developed and poorly
understood by industry.
The drive to develop new diagnostics for the developing world is unlikely
to succeed without the private sector, with its expertise in product development,
manufacturing capacity, product distribution and quality control. Unless measures
are put in place to address current market dynamics, the number of companies
engaged in diagnostics development will likely remain limited, and most will
continue to tailor their products to markets in industrialized countries. The resulting products, such as the molecular amplification systems and automated systems
for early detection of mycobacterial growth—which have markedly improved
the diagnosis of tuberculosis in industrialized countries—may be little used in
developing countries and thus have no impact on the global tuberculosis problem.
Most of the companies manufacturing rapid malaria tests are small and do not
have the resources to redevelop their assays to address important deficiencies in
sensitivity and shelf life, especially at tropical temperatures.
Goal-driven public sector action is needed across the development pathway
to forge a strong and sustainable partnership with industry to generate new
diagnostics (Figure 3-1). Public sector actors must be prepared to sponsor basic
research, partner equitably with industry on product development, evaluate products in a regulatory-quality fashion (Small and Perkins, 2000), demonstrate the
efficacy of implementation, change technical and financial policies to foster new
diagnostics, and actively facilitate the latter’s distribution and use. In pursuit of
these goals, the public sector should explore such innovative approaches as the
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3-1 Broadside
FIGURE 3-1 Product development path for microbial diagnostics.
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165
creation of novel financing mechanisms and distribution strategies to increase
industry confidence that a viable market will exist in resource-limited settings.
There are many examples of innovative public–private partnership for the
development of drugs and vaccines. Few are, however, focused on diagnostics.
The Foundation for Innovative New Diagnostics (FIND; Geneva, Switzerland; of
which Mark D. Perkins is Chief Scientific Officer), is one such entity. Launched
in 2003, FIND aims to develop a model for public sector action to drive the
development of diagnostic products for diseases of the developing world, using
the search for new diagnostics as the test case for the model’s development.
FIND seeks to identify the most promising product candidates and accelerate
the process of development, testing, approval, distribution and incorporation
into routine public health policy. Although motivated by the desire to create new
public goods, FIND has many of the attributes of a private company, pursuing
a clear business plan and using rigorous scientific criteria to identify priority
product candidates.
RAPID INFECTIOUS DISEASE DIAGNOSTIC ASSAYS
Mark J. Wolcott, Ph.D.
U.S. Army Medical Research Institute of Infectious Diseases
Randal J. Schoepp, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
David A. Norwood, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
David R. Shoemaker, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
Rapid disease diagnostics (“serving to identify a particular disease or pathogen”) for many infectious agents are not as well developed as other laboratory
technologies. Laboratory tests for many infectious agents still rely on decadesold technologies and techniques. Culture remains the gold standard for identifying organisms, but not all pathogens can be cultured, making alternative tests
necessary.
When culture is difficult or not available (virus cultures in field laboratories),
serological diagnosis of the antibody response to the organism is typically used.
Opinions,
interpretations, conclusions, and recommendations are those of the authors and are not
necessarily endorsed by the U.S. Army. Funding was provided in part by the Defense Threat Reduction
Agency, Joint Science and Technology Office for Chemical and Biological Defense (JSTO-CBD).
Diagnostic Systems Division.
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global infectious disease surveillance and detection
However, a problem with both traditional culture and immunodiagnostics is the
time required to obtain results. Culture may take several days and immunodiagnosis is limited by the time required to mount an antibody response, often a week
or more (Figure 3-2). Current efforts in rapid diagnostics are shifting the window
of detection closer to the point at which clinical disease symptoms become evident. Ultimately, future rapid diagnostics will shift the window to a point soon
after exposure, giving the clinician the greatest opportunity to intervene in the
disease process.
Orthogonal diagnostic testing is the key to improving the reliability of rapid
diagnostic technologies. Orthogonal testing refers to tests that are statistically
independent or non-overlapping but, in combination, provide a higher degree
of certainty of the final result. Although orthogonal testing is not a standard
perspective in the clinical diagnostic industry, the concept and its application
are paramount when investigating some infectious agents. Any single detection
technology has a set of limits with regard to sensitivity and, most importantly,
specificity. Orthogonal testing seeks to overcome the inherent limitations of individual test results with the strength of data combinations (Henchal et al., 2001).
The application of orthogonal diagnostic testing uses an integrated testing strat-
Infection/response time course
Detect exposure
Acquired immunity (Late response)
Clinical disease
Detect agent
IgG serodiagnostics
IgM serodiagnostics
Antigen/nucleic acid methods
Culture methods
Innate immunity
0
5
10
Time
15………120 days
FIGURE 3-2 Infection and response time course. Various detection methodologies have
highly different entry points in their use on human disease. As the time points extend out,
the ability of medical interventions have less success. The earlier the time of medical
intervention, the more successful the prognosis is for most diseases.
SOURCE: Wolcott (2006).
3-2
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DETECTION AND DIAGNOSTICS
egy where more than one technology, technique, or biomarker is used to produce
diagnostic results, which are then interpreted collectively (Figure 3-3).
The Department of Defense has an acquisition program to acquire quality
diagnostic products that satisfy the needs of commanders with missions to support the warfighter. This acquisition program is designed to be timely with fair
and reasonable associated costs. The acquisition program includes design, engineering, test and evaluation, production, and operations and support of defense
systems (Table 3-1). To simplify and expedite the acquisition timeline for the
fielding of a rapid diagnostic system, commercial off-the-shelf technology is
evaluated and a formal selection process is used to select a system for further
development and fielding. The Joint Biological Agent Identification and Diagnostic System (JBAIDS) acquisition program was formally launched in September
2003 with the award of the first phase, a molecular diagnostic system, in fall
2005 (Figure 3-4).
Classical
microbiology
Nucleic
acid
detection
(agent/host)
Clinical
diagnosis
or
medical
intelligence
Antigen
detection
(agent/host)
ANSWER
Animal
testing or
other
advanced
technologies
(EM/Mass
Spec/etc.)
FIGURE 3-3 Orthogonal diagnostic testing. Although each method provides an independent assessment, together the power of the diagnostic becomes large. The failure of any
one independent assessment does not fail the system.
3-3
SOURCE: Wolcott (2006).
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global infectious disease surveillance and detection
TABLE 3-1 Department of Defense (DoD) Acquisition Program for
Diagnostic Devices
Predevelopment
Advanced Development
Basic
research
Technology
evaluation
Demonstration
and validation
New
technologies
Technology
demonstrations
Prototypes
Engineering
and
manufacturing
development
PMA/510K
approval
Initial
operational
testing
Procurement Operations
and Support
Procurement
and
deployment
Operations
and
support
Final
production
Follow-up
evaluation
NOTE: The acquisition process moves from left to right through defined operational activities. Each
activity is designed to provide a value-added service and ensure that DoD obtains the product needed
at a reasonable cost investment for the country.
SOURCE: Wolcott (2006).
FIGURE 3-4 Acquisition program—evolutionary strategy. The acquisition process for
developing and fielding a rapid infectious disease diagnostic assays system is designed
around an evolutionary strategy. By leveraging commercial technologies that currently
exist in the commercial market, and furthering development on those platforms, the final
field-deployable system will be quicker and cheaper than trying to obtain the final product
up front.
3-4
SOURCE: Wolcott (2006).
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Current molecular diagnostic technologies are based on the amplification of
specific DNA sequences from extracted nucleic acids, DNA or RNA. Amplification techniques take tiny amounts of nucleic acid material and replicate them
many times through enzymatic reactions, some that occur through cycles of
heating and cooling. These include methods that involve target amplification
(e.g., polymerase chain reaction [PCR], reverse transcriptase–PCR [RT-PCR],
strand displacement amplification, transcription amplification), signal amplification (e.g., branched DNA assays, hybrid capture), probe amplification (e.g., ligase
chain reaction, cleavase-invader, cycling probes), or postamplification analysis
(e.g., sequencing the amplified product or melting curve analysis as is done in
real-time PCR).
Nucleic acid-based methods are generally specific and highly sensitive and
can be used for all categories of microbes (Christensen et al., 2006; Emanuel
et al., 2003a). Amplification methods can identify minute traces of the genetic
material of an organism in a specimen, avoiding the need for culture. These
techniques are particularly useful for organisms that are difficult to culture or
identify using other methods (e.g., viruses, obligate intracellular pathogens),
or are present in very low numbers. Results can be provided more rapidly than
through most conventional methods, especially culture. However, because amplification methods are so sensitive, false positives from trace contamination of the
specimen or equipment can easily occur. In addition, because these techniques
depend on enzymatic activity, false-negatives also occur when a sample contains
contaminants that inhibit enzyme activity (Hartman et al., 2005). Nucleic acidbased tests are also limited in that they do not provide information on the viability
of the detected organism.
Immunodiagnostics is the standard against which many agent detection,
identification, and diagnostic technologies are compared. Antibody-based assays
continue to serve as preliminary and confirmatory diagnostic formats for many
infectious and noninfectious diseases. These assays are typically rapid, sensitive, specific, reliable, and robust. Immunodiagnostic technologies are relatively
unsophisticated, making them available to nearly any laboratory.
Hand-held assays (HHAs) are immunoassays that are based on immunochromatography or lateral flow assay format. Generally, a sample is applied to
the testing unit and by flowing along a membrane, an indicator line forms where
antibodies to the analyte of interest are bound. The presence of a line indicates
the presence of the analyte, while the absence of a line denotes a negative result.
Applying a sample solubilizes the tagged antibodies and initiates the first binding
of the target by the tagged antibodies. As the sample continues migrating down
the filter paper, the analyte of interest encounters a set of antibodies bound to the
membrane and an antibody-analyte-antibody sandwich is formed. While early
HHAs incorporated enzymes as labels to yield a visible signal, advances have
done away with the multistep enzyme immunoassay format and have incorporated reporter molecules such as colloidal gold or colored latex spheres that yield
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a direct signal. These physical signal generators rely on the aggregation of a large
number of tags to enhance signal visualization by the naked eye. HHAs, like all
analytic systems, have inherent limitations in their use and interpretation; they
require a relatively large amount of sample, their sensitivity is limited, and they
have a potential for false positives as a result of “dirty” environmental samples
that form a confounding “dirt” line in the antibody capture zone. Although HHAs
have limitations, their overall ease of use and quickness make them useful in
certain situations.
Time-resolved fluorescence (TRF) is an immunoassay application that
employs the basic immunoassay analyte sandwich capture format, but with
detector antibodies that are directly labeled with a lanthanide chelate, such as
europium, samarium, terbium, and dysprosium. The strengths of TRF are its
increased sensitivity and the potential for multiplexing. TRF uses the differential fluorescence life span of lanthanide chelate labels compared to background
fluorescence. The long-lived fluorescence signal and the difference in wavelength
between absorbed and emitted light results in a very high signal-to-noise ratio and
excellent sensitivity (Hemmila et al., 1984; Soini and Kojola, 1983). The long
fluorescence decay time allows the measurement of immunoassay fluorescence
after any background fluorescence has decayed. By pulsing the excitation light
repeatedly, in 1 second the fluorescent material can be excited more than 100
times with an accumulation of the generated signal that improves both the overall
signal and the reduction of background signals. TRF assays are particularly useful
in clinical immunoassays, but have limitations with environmental samples where
europium or other lanthanides naturally occur. The contaminating compounds
behave much like labeled lanthanides, prolonging the background fluorescence
and lowering TRF sensitivity.
Electrochemiluminescence (ECL) is immunoassay technology in which a
detector antibody is tagged with a chemical that emits light (luminescence) when
it is excited by an electrical stimulus. There are several electrochemiluminescent
chemical moieties, but ruthenium is the most common. Ruthenium, in the form
tris (2,2’ - bipyridine) ruthenium (Ru), is relatively small, allowing easy conju
gation to antibodies. The technology relies on two components: the ECL-label
(Ru) coupled to an antibody and tripropylamine (TPA) present in the reaction
buffer. When an electrical current is applied to an electrode, both components
are activated by oxidation. The oxidized TPA is transferred into a highly reducing
agent, which reacts with activated Ru to create an excited-state form of Ru. This
form returns to its ground state with emission of a photon at 620 nm wavelength.
An advantage of the Ru-TPA methodology is that the measurement of a single
sample can be repeated multiple times because the electron-transfer photonrelease reaction regenerates the Ru resulting in signal amplification. Although
ECL assays are simple, rapid, and sensitive (Kijek et al., 2000; Smith et al.,
2001), the sample matrix can affect the assay sensitivity. The sample matrix will
influence the sensitivity by varying positive cut-off values; therefore, matrix-
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s pecific positive and negative control samples are used to establish standard
curves and cutoff values.
Several diagnostic systems are using a technology to analyze microspherebased multiplex protein assays. The advantage of multiplex assays is that multiple results are available from one sample without individual testing. Up to 100
different biomolecules (proteins, peptides, or nucleic acids) can be analyzed in
a single test. A microplate platform allows the automated analysis of a 96-well
plate in 30 minutes yielding a throughput of 1,920 assays in a 20-plex system.
Currently kits for simultaneous quantitative measurement of up to 25 to 30 proteins are available, including cytokines, phosphoproteins, growth factors, kinases,
and transcription factors. Several investigators are using these systems to develop
multiplexed assays for biological warfare agents. One system was evaluated by
the U.S. Army with extremely good results, but the equipment is currently not
rugged enough for use by the warfighters.
The key to future rapid diagnostic systems is the development of a completely and fully integrated system. Previous diagnostic research efforts were
only concerned with the development of an assay technique and failed to address
the full spectrum of an integrated system. To fully address an integrated system,
protocols, sample processing, reagents, assays, platforms, and evaluations need
to be completely explored. Protocols are equivalent to an intended-use statement.
Without addressing how and why the assay or system is to be used, misapplication will result in incorrect and potentially serious testing reliability issues.
The single most important aspect of rapid testing is sample processing.
The sample is the most important component in a system, and an inappropriate or improperly handled sample will jeopardize an otherwise robust assay.
For example, detection of Bacillus anthracis is highly problematic. The spores
of Bacillus anthracis are very refractile to easy and rapid sample preparation.
Alternate methods are required to produce the highest quality sample, which
include concentrating the sample (if possible) and methods to release either the
nucleic acids or specific proteins from the spore. These include techniques such
as germination, sonication, or mechanical disruption (“bead-beating”). Another
consideration of sample preparation, especially for many molecular methods, is
the removal or neutralization of inhibitors of amplification.
Systems consist of more than just assays (Figure 3-5). Developers need
to be cognizant of all the details. While most commercial manufacturers have
appropriate production systems and quality manufacturing practices in place for
producing consistent, reliable, and appropriate reagents that are compliant with
Food and Drug Administration (FDA) requirements, research-derived systems
often fall short. In addition, integration of assays with various platforms is often
overlooked in initial system development. While some assays perform well on
multiple platforms, many assays suffer optimization issues when moved from
one platform to another. Unless provisions are made for multi-platform development, and shown to be equally effective through validation, platform equivalency
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global infectious disease surveillance and detection
Diagnostic System Architecture
Validation/field testing
Protocols
Platforms
Reagents
Sample processing
Assays
FIGURE 3-5 Diagnostic system architecture. Systems-based architecture needs to include
the full gamut of functions from protocols through validation.
SOURCE: Wolcott (2006).
3-5
should not be assumed. Another consideration in system development for systems
developed by professional scientists working in modern laboratory facilities is
the inherent expectation that assays and systems will work in the hands of less
trained personnel outside of the pristine laboratory facilities. Often, this is not the
case. Field evaluation, under conditions of actual employment, is critical before
assays and systems can be confidently deployed and used.
Validation of the appropriateness and effectiveness of assays and systems is
paramount in the development process (Emanuel et al., 2003b). Development of
assays and systems needs to include assay validation parameters such as linearity,
limits of detection, inclusivity and exclusivity testing, ruggedness, robustness,
and repeatability. Validation parameters are detailed in Box 3-1.
A critical and often overlooked issue is that diagnostic systems and tests
intended to be used to test clinical samples must be approved by the U.S. Food
and Drug Administration in order to legally be distributed and used in the United
States. Many of the technologies discussed in this article are mature enough to
produce clinically useful diagnostic products. However, companies that may have
the capability to manufacture these diagnostic tests, and to gain FDA approval
for them, typically are not interested in doing so for tests to diagnose tropical
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BOX 3-1 Example of Diagnostic Systems
Validation Parameters
1. L
inearity (establish standard curve with single “type” strain). The concentrations will range from 100 pg to 1 fg of the target nucleic acid. When cloned
material is required (i.e., Variola), the concentrations will range from 1 pg to
10 ag.
a. There will be two replicates for each 10-fold dilution.
b. Data will be used to estimate limit of detection (LOD).
c. Slopes will be used to calculate amplification efficacy and efficiency using
the formulas.
d. All supporting data will be submitted in the data package.
e. Real-time polymerase chain reaction (PCR) curves.
f. Standard curve indicating slope and R2 values.
g. PCR efficacy and efficiency calculations.
2. Limit of detection.
a. LOD testing will be performed with the type strain.
b. A minimum of 58 positive results is required to establish the LOD.
c. 60 total replicates will be performed at the LOD of the assay consisting
of:
i. Three separate runs—two instruments—two operators—2 days.
ii. A minimum of two positive and two negative controls.
d. All supporting data will be submitted in the data package.
e. Operators, instruments, and dates of performance should be documented.
3. Inclusivity/exclusivity.
a. Inclusivity (testing the ability of the assay to pick up multiple strains of the
same agent).
i. Multiple strains of the target organism.
ii. Duplicate samples.
b. Exclusivity (test of whether assay cross-reacts with nucleic acids from other
organisms).
i. Panel will include near neighbor testing (genetic neighbors).
ii. Panel will include broad cross-reactivity panel.
iii. Duplicate on purified nucleic acids at a concentration at least 1,000x
the established LOD of the assay.
c. Environmental/matrix panel to include human DNA and cell culture extracts
used to produce viral agents.
SOURCE: Wolcott (2006).
diseases or biological threat agents because the commercial demand is low. This
is a chronic problem with no easy solution.
To help support the deployment of rapid agent identification systems, especially those that do not have enough commercial value to be fully supported by
commercial manufacturers, the Department of Defense relies on the Joint Program Executive Office–Critical Reagents Program (CRP). The CRP is a national
resource for the biological defense community, whose mission is production of
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global infectious disease surveillance and detection
detection reagents, standardization of procedures and training, and optimization
and transition of detection technologies. Their commodity areas include the
production of antigenic and genomic materials for test and evaluation purposes,
antibodies, to include the manufacturing of hand-held devices, molecular detection reagents, and sampling kits. Because of the confined nature of these materials
and the lack of commercialization due to the limited customer base, CRP provides
a vital link to the defense community to ensure harmonization of tests and evaluations and as an avenue for advanced development.
In the course of development of newer, faster, better, and cheaper rapid
diagnostic devices, the Department of Defense program is looking at potential
future platforms. Many characteristics of those future systems are discussed
above, but one that is showing some promise is DNA microarrays. Microarrays or
DNA chips are one of the latest methods for rapid infectious disease diagnostics.
Microarrays are a recent adaptation of Northern blot technology (Grunstein and
Hogness, 1975; Schena et al., 1995). The ability to label nucleotide sequences
with fluorescent tags, much like fluorescent antibody technology, has increased
their use in diagnostics. Microarrays are small, solid supports (typically glass
slides) on which DNA sequences are attached, or spotted, at fixed, orderly,
addressable locations. The DNA is composed of short, single-stranded fragments,
typically 5 to 50 nucleotides long. Microarrays can have up to tens of thousands
of spots, allowing for a large amount of data collected for each sample tested.
Microarrays depend on the annealing of two nucleic acid strands to function.
When sample DNA is prepared, usually through polymerase-based amplification,
fluorescent dyes are incorporated into the amplicon so that hybridization can
be detected. The kind of information required from microarrays drive how the
arrays are developed and used. Microarrays can be spotted with known sequences
of a variety of oligonucleotides for basic genomic investigation. Gaining wider
acceptance is the use of microarrays to “resequence” organisms. Utilizing known
sequences from already sequenced organisms and hybridizing genomic material
from organisms not previously sequenced, sequence differences can be determined. With more than 10,000 sequences (and growing as automated systems
improve) to interrogate on a single chip, variation in genomic sequences can
provide accurate species and subspecies determination. Finally, one of the earliest
applications of microarrays is their use in “transcriptomics” or gene expression
studies. Gene expression-based measurements of mRNA levels, and the differences between these levels in various states of organism growth (i.e., aerobic
versus anaerobic growth), has provided significant insights in gene regulation of
various organism functions.
Although microarrays have the demonstrated potential for diagnostics, routine use is hampered by several considerations. The first hurdle for microarrays is
the availability of high-quality, validated, and standardized arrays and processes.
A key limitation to implementation of routine diagnostic microarrays is identification of appropriate targets. Although ribosomal RNA gene targets are widely
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used, they are limited in their ability to resolve bacteria below the species level
(Saliba et al., 1966). Other bacterial target genes, including housekeeping genes,
are potentially useful, but data across the full breath of organisms are limited or
nonexistent. Even with good targets, optimal hybridization conditions for all the
probes on a single array are still challenging. Redundant variations in probes
help compensate to a degree. Another challenge to microarray routine use is
the sensitivity of most systems. To obtain appropriate sensitivity, polymerase
amplification is necessary. In most systems, this requires a multitude of specific
primers for the genes of interest. Because multiplexed PCR is limited to a dozen
or so reactions, several hundred iterations of PCR could be required to completely
cover all the potential probes on an array, which is not practical in routine use.
Until a good on-chip amplification or signal detection method is developed, the
use of diagnostic microarrays will be limited.
Ultimately, to meet the needs of users, rapid infectious disease diagnostic
assays need a comprehensive integrated system. This includes automated sample
processing and the use of multiple technologies to obtain results that can be interpreted against the clinical picture or medical intelligence. Currently, immunoassays and molecular assays are the most mature technologies. Immunoassays are a
maturing technology that has improving sensitivity and specificity. With improvements in signal amplification and the use of monoclonal antibodies, immunoassays are fast, robust, and approaching the sensitivity of some molecular methods.
Molecular methods are rapidly developing but are not at the full maturity level
yet. Amplification methods achieve exquisite sensitivity, but at the risk of potential contamination events. Together, immunoassays and molecular techniques are
very complementary and a powerful set of techniques for an integrated system
(Henchal et al., 2001) (Figure 3-6).
The future for rapid infectious disease diagnostics is the lab-on-a-chip
approach, where all sample processing, assay technologies, detection, and reporting are fully integrated into one unit. Miniaturized, disposable, and cost-effective
units will evolve from our current systems. As technologies mature and new
technologies are developed, rapid infectious disease diagnostics will become
available and practical.
Ramping Up to Success
Although we believe that the products of strategic, adequately supported
public–private partnerships to develop diagnostics could transform approaches
to control infectious diseases in poor countries, progress inevitably will be incremental, especially in the near term. Because new tests are likely to be imperfect,
we will need flexibility and creativity to ensure that these tools are used to
maximum effect. For example, rather than discard a rapid tuberculosis test with
high sensitivity but low specificity, we should consider incorporating it into a
diagnostic algorithm to quickly rule out tuberculosis in most patients present-
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D
Microfluidic backbone
B
Analyte AnalyteSpecific
specific
Binding
binding
C
C
Detection
Detection
3-6A
Power
Power
Subsystem
subsystem
Micro
Micro
Controller
controller
Anthrax
positive
BW
Module
Immunodiagnostics
Operator
Interface
interface
FIGURE 3-6 Comprehensive integrated diagnostic system. Integrated systems that employ more than one technology along with the sample
handling component are being investigated for the next-generation diagnostic systems.
Crude
Sample
sample
A
Sample
Preprocess
preprocess
Disposable cassette
Nucleic acid detection
Automated sample processing
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DETECTION AND DIAGNOSTICS
ing with chronic cough—a step that could dramatically decrease the workload
of tuberculosis clinics. Rather than develop a single test to replace the sputum
microscopy, we should embrace the concept of market segmentation and develop
a range of new tools suitable for different diagnostic environments.
We must also accept that new technology may require changes to longstanding public health practices. For example, tuberculosis epidemiology has long
been tracked by monitoring the number of smear-positive patients. If microscopy is replaced with a more sensitive test, tracking of tuberculosis trends could
be disrupted. But this is a small price to pay for better serving patients and
strengthening the world’s ability to bring tuberculosis under control. Similarly,
microscopy offers quantitative estimates of parasite burden, which is often used
by clinicians to estimate the severity of illness or to monitor the effectiveness of
treatment. Replacement with qualitative testing will force a change of practice,
even as it brings the power of confirmatory diagnosis out of referral laboratories
and into the community.
Finally, we emphasize that the impact of a new diagnostic test ultimately will
be determined by the extent to which it is used. Expanding use of a new technology, as with any global health intervention, ultimately will depend on political
will. Integration of improved diagnostics into national programs in the same
structured fashion that has been used for standard and second-line tuberculosis
drugs is possible, but only if leaders confront a range of issues that will make
implementation possible—from lifting import taxes to improving laboratory
capacity to modifying disease control guidelines. Is this too much to ask to give
our health-care practitioners the tools they need to do their jobs?
EMERGING TOOLS FOR MICROBIAL DIAGNOSIS,
SURVEILLANCE, AND DISCOVERY
W. Ian Lipkin, M.D.
Columbia University
Thomas Briese, Ph.D.6
Columbia University
Introduction
Here we describe methods and perspectives for pathogen surveillance and
discovery, and discuss challenges associated with proving causality. We provide
examples from our own experience to illustrate the complexity of pursuing
Jerome
L. and Dawn Greene Infectious Disease Laboratory, Mailman School of Public Health.
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global infectious disease surveillance and detection
research in this arena and to provide the reader with insights into the process that
led to the implementation of particular strategies.
Proof of Causation
Discovery of an organism in association with disease is only the first step in
understanding its role in pathogenesis. Many have wrestled with the challenge
of codifying the process of proving causation. Based on the germ theory of
disease formulated by Pasteur, Koch, and Loeffler proposed precise criteria that
define a causative relationship between agent and disease: The agent should be
present in every case of a disease, it should be specific for a disease (i.e., present in none other), and it should be propagated in culture and proven capable of
causing the same disease upon inoculation into a naïve host. Known as Koch’s
postulates (Koch, 1891), these criteria were subsequently modified by Rivers for
specific application to viruses (Rivers, 1937), and by Fredricks and Relman to
reflect the advent of molecular methods (Fredricks and Relman, 1996) (Table
3-2). Nonetheless, Koch’s postulates remain the ideal standard by which causality is considered to be proven. There are problems with holding to this standard.
Some agents cannot be propagated in culture. Additionally, for many human
viral pathogens, there may be no animal model. In many acute viral diseases, the
responsible agent can be readily implicated because it replicates at high levels
in the affected tissue at the time the disease is manifest, morphological changes
consistent with infection are evident, the agent is readily identified with classical
or molecular methods, and there is evidence of an adaptive immune response.
However, implication of viruses in chronic diseases may be confounded because
persistence requires restricted gene expression, classical hallmarks of infection
are absent, and/or mechanisms of pathogenesis are indirect or subtle. In the final
analysis, investigators are occasionally left with what amounts to an assessment
of strength of epidemiological association based on the presence of the agent,
its footprints (nucleic acid, and preferably, an immune response), and biological
plausibility based on analogy to diseases with related organisms where linkage
is persuasive.
Many Routes to Microbial Pathogenesis
Implication of an infectious agent is most straightforward in instances where
it is present at the site of disease at the time the disease is manifest. Two classic
examples where effects are readily appreciated at the infection site are poliomyelitis, where virus replicates in motor neurons of the brain and spinal cord,
causing cell loss and paralysis, and cholera, where Vibrio cholerae replication
and local elaboration of toxin in the intestine alters ion transport, resulting in
diarrhea. A more complex example of intoxication is botulism where replication
of Clostridium botulinum in the skin or the gastrointestinal tract leads to local
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DETECTION AND DIAGNOSTICS
TABLE 3-2 Criteria for Proof of Causation
Robert Koch (1890)a
Thomas R. Rivers (1937)
Fredricks and Relman (1996)
A microbe must be:
• P
resent in every case of a
disease.
• A
specific virus must be
found associated with a
disease with a degree of
regularity.
• C
andidate sequences should
be present in most cases of
disease and at sites of disease.
• Specific for that disease.
• I solated, propagated,
in culture, and shown
to induce disease upon
inoculation into the
experimental host.
• R
eisolated from the
experimental host wherein
the original syndrome is
replicated.
NOTE: This fourth postulate
though not required by Koch,
logically follows his other
conditions and so has been
added by some reviewers.
NOTE: The possibility of
a viral carrier state was
recognized and Koch’s
requirements of propagation
in media or cell culture was
abandoned.
• T
he virus must be shown
to be the causative agent
of disease in the sick
individual.
• F
ew or no sequences should
be present in host or tissue
without disease.
• S
equences should diminish
in frequency with resolution
of disease and increase with
relapse.
• S
equences should be present
prior to the onset of disease.
NOTE: The pathogen should
be present at the proper time
in specific regions and the
disease should be produced
with some regularity by
serious inoculation of
infected material into a
susceptible host.
aAlthough
Koch included basic points already in earlier papers, especially his 1884 paper on the
etiology of tuberculosis, his most explicit presentation was given at the 1890 International Congress
of Medicine; the proceedings of which were published in 1891.
SOURCE: Koch (1891); Rivers (1937); Fredricks and Relman (1996).
expression of a toxin that traffics to the neuromuscular junction to interfere with
motor function. Host responses to infection may contribute to pathogenesis.
Acute infection with influenza virus or severe acute respiratory syndrome (SARS)
coronavirus elicits cytokines and chemokines that cause pulmonary dysfunction. Chronic inflammation in hepatitis B and hepatitis C infections can result in
hepatic failure and hepatocellular carcinoma. Infection can also lead to inhibition of immune function. The capacity of viruses to enhance susceptibility to
opportunistic agents is now best known in the context of HIV/AIDS; however, the
observation of virus-induced immunosuppression dates back to the early 1900s
when von Pirquet noted the loss of skin reactivity to tuberculin in association with
measles infection. The effects of infection may depend on the age and maturation status of the host. Individuals at either extreme of life are at increased risk
for acute morbidity and mortality with a wide variety of infections. Encephalitis
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global infectious disease surveillance and detection
is far more common in individuals infected with West Nile virus after the age
of 50 years than in other adults or children. Infection during organogenesis may
have different consequences than at other times. Congenital rubella infection, for
example, can be associated with characteristic cardiac and central nervous system
defects. Persistent viral infections are described in animal models where subtle
effects on cellular physiology result in alterations in the expression of neurotransmitters or hormones that have profound effects including cognitive impairment,
hypothyroidism, or diabetes mellitus. Whether similar mechanisms can be implicated in human disease remains to be determined; nonetheless, these preclinical
studies indicate biological plausibility. Infection can break tolerance for “self,”
resulting in autoimmune disease. A classical example is molecular mimicry in
group A beta-hemolytic streptococcus infection where cross-reactivity to heart
and brain results in valvular disease and chorea, respectively. The capacity for
infections to cause disease via myriad mechanisms, direct and indirect, short and
long term, pose challenges for pathogen discovery.
Molecular Strategies for Pathogen Discovery
Methods for cloning nucleic acids of microbial pathogens directly from
clinical specimens offer new opportunities to investigate microbial associations
in chronic diseases (Relman, 1999). The power of these methods is that they can
succeed where methods for pathogen identification through serology or cultivation may fail due to absence of specific reagents or fastidious requirements for
agent replication. Over the past decade, the application of molecular pathogen
discovery methods resulted in identification of novel agents associated with both
acute and chronic diseases, including Borna disease virus, hepatitis C virus, Sin
Nombre virus, HHV-6, HHV-8, Bartonella henselae, Tropheryma whippelii, West
Nile virus, and SARS coronavirus (Challoner
���������������������������������������������
et al., 1995; Chang et al., 1994;
Choo et al., 1989; Lipkin et al., 1990; Nichol et al., 1993; Relman et al., 1990,
1992; VandeWoude et al., 1990).
Various methods are employed or proposed for cultivation-independent characterization of infectious agents. These can be broadly segregated into methods
based on direct analysis of microbial nucleic acid sequences (e.g., complementary DNA [cDNA] microarrays, consensus polymerase chain reaction [cPCR],
representational difference analysis [RDA], differential display [DD]), direct
analysis of microbial protein sequences (e.g., mass spectrometry), immunological systems for microbe detection (e.g., expression libraries, phage display), and
host response profiling.
The decision to employ a specific method is guided by the clinical features,
epidemiology, and spectrum of potential pathogens to be implicated. Expression libraries, composed of cDNAs or synthetic peptides, may be useful tools
in the event that large quantities of acute and convalescent sera are available for
screening purposes; however, the approach is cumbersome and labor-intensive,
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and success depends on the presence of a specific, high-affinity humoral immune
response. Mass spectrometry is an intriguing approach to pathogen discovery
(Dalluge, 2000; van Baar, 2000); however, potential confounds include mutations in flora that alter spectra without clinical correlation; the requirement for
establishment of large libraries of spectra representing flora of thousands of orga
nisms propagated in vitro and isolated in vivo; and the difficulties associated with
extending this technology to viruses, where disease may occur without robust
protein expression, and pathogenicity may be correlated with single base substitutions. The utility of host response messenger RNA (mRNA) profile analysis has
been demonstrated in several in vitro paradigms and some inbred animal models
(Diehn and Relman, 2001; Taylor et al., 2000; Zhu et al., 1998); nonetheless, a
variety of organisms may activate similar cascades of chemokines, cytokines,
and other soluble factors that influence host gene expression to produce what
are likely to be convergent gene expression profiles. RDA is an important tool
for pathogen identification and discovery. However, RDA is a subtractive cloning method for binary comparisons of nucleic acid populations (Hubank and
Schatz, 1994; Lisitsyn et al., 1993). Thus, although ideal for analysis of cloned
cells or tissue samples that differ only in a single variable of interest, RDA is
less well suited to investigation of syndromes wherein infection with any of several different pathogens results in similar clinical manifestations, or infection is
not invariably associated with disease. An additional caveat is that because the
method depends on the presence of a limited number of restriction sites, RDA is
most likely to succeed for agents with large genomes. Indeed, in this context, it is
noteworthy that the two viruses detected by RDA were herpesviruses (Challoner
et al., 1995; Chang et al., 1994).
Consensus PCR also has been a remarkably productive tool for biology. In
addition to identifying pathogens, this method has facilitated identification of a
wide variety of host molecules, including cytokines, ion channels, and receptors.
One difficulty in applying cPCR to pathogen discovery in virology has been that
it is difficult to identify conserved viral sequences of sufficient length to allow
cross-hybridization, amplification, and discrimination in a traditional PCR format. Although this may not be problematic when one is targeting only a single
virus family, the number of assays required becomes infeasible when preliminary
data are insufficient to permit a more directed, efficient analysis. To address
this problem, we adapted cPCR to differential display, a PCR-based method for
simultaneously displaying the genetic composition of multiple sample populations in acrylamide gels (Liang and Pardee, 1992). This hybrid method, known
as domain-specific differential display (DSDD), employs short, degenerate primer
sets designed to hybridize to viral genes that represent larger taxonomic categories than can be resolved in cPCR. Although this modification allowed us to identify West Nile virus as the causative agent of the 1999 New York City encephalitis
outbreak (Briese et al., 1999), it did not resolve issues of low throughput with
cPCR due to limitations in multiplexing.
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global infectious disease surveillance and detection
To address the need for sensitive, facile, highly multiplexed pathogen surveillance, we established two new platforms for viral detection, MassTag PCR
and the GreeneChip. MassTag PCR is a multiplex PCR method that can accommodate in excess of 20 genetic targets with sensitivity in the range of 10 to 1,000
RNA copies (variability is a function of primer degeneracy). The GreeneChip
is a comprehensive viral microarray that addresses all vertebrate viruses in the
International Committee on Taxonomy of Viruses (ICTV) database. Both methods rely on the presence of an agent related to one already known. In instances
where agents are novel or sufficiently distant in sequence to related agents to
confound hybridization it may be necessary to resort to subtractive cloning
or high-throughput unbiased sequencing. Our algorithm for characterization of
clinical materials is illustrated in Figure 3-7. Where the list of candidates to be
considered can be addressed using MassTag PCR this is our method of choice
due to low cost, speed, and sensitivity. Where MassTag PCR fails or the list of
candidates exceeds 30 targets, we move to GreeneChips (viral or panmicrobial).
In the event that GreeneChips fail we shift to unbiased high-throughput sequencing or subtractive cloning.
MassTag PCR
Although singleplex PCR assays are well established in clinical microbiology and have proved indispensable in management of HIV and hepatitis C virus
(HCV), and in control of outbreaks where an agent is identified, multiplex assay
applications have lagged behind. Fluorescence reporter systems in real-time PCR
achieve quantitative detection with sensitivity similar to nested amplification;
however, their capacity to simultaneously query multiple targets is limited to
the number of fluorescent emission peaks that can be unequivocally separated.
At present up to four fluorescent reporter dyes are detected simultaneously. To
address the need for highly multiplexed assays, we created MassTag PCR, a
platform wherein digital mass tags rather than fluorescent dyes serve as reporters
(Figure 3-8). The first description of this method was published in the context of
a panel that distinguishes 22 different viral and bacterial respiratory pathogens
(Briese et al., 2005). It allowed us to identify viral and bacterial sequences in
respiratory samples as well as cultured materials, and to recognize instances of
coinfection not appreciated in reference laboratories using established diagnostics
assays. We later expanded the repertoire to include causative agents of hemorrhagic fever, and to subtype influenza viruses. Between October and December
2004, an increased incidence of influenza-like illness (ILI) was recorded by the
New York State Department of Health that tested negative for influenza virus by
molecular testing, and negative for other respiratory viruses by culture. Concern
that a novel agent might be implicated led us to investigate clinical materials
(Lamson et al., 2006). MassTag PCR resolved 26 of 79 previously negative
samples, revealing the presence of rhinoviruses in a large proportion of samples,
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DETECTION AND DIAGNOSTICS
Clinical specimen
Short candidate list
<30 agents
Refine:
MassTag primers
GreeneChip probes
Long candidate list
>30 agents
MassTag PCR
6 hours
GreeneChip
14 hours
(-)
(-)
(+)
High-throughput
sequencing
1 week
(+)
Sequencing
Surveillance/Causation
Quantitative real-time PCR
serology
FIGURE 3-7 A staged strategy for pathogen detection and discovery.
SOURCE: Lipkin (2006).
3-7
1. PCR Amplification with mass tag primers
4. Automated sample injection, photocleavage
A
Cleavage of mass tags from amplicon
Ultraviolet Light
B
A
A
B
B
Purified samples
1 1/2 min per sample
2 1/2 hrs for 96 analyses
96 well thermocycler plate
Ionization and detection
MS
A
A B
A
B
A
A B
B
A B
B
2. Product purification on filter plate
5. Detection and pathogen identification
B
Abundance
A
3. Elution into 96 well loading plate
for mass spectrometer analysis
Mass Size
FIGURE 3-8 Schematic representation of MassTag PCR procedure.
SOURCE: Briese et al. (2005).
3-8
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global infectious disease surveillance and detection
about half of which belonged to a previously uncharacterized genetic clade. The
2004 New York ILI study confirmed the utility of MassTag PCR for surveillance,
outbreak detection, and epidemiology by demonstrating its potential to rapidly
query samples for the presence of a wide range of candidate viral and bacterial
pathogens that may act alone or in concert.
MassTag PCR may not suffice in instances where either larger numbers of
known pathogens must be considered or sequence divergence may impair binding of PCR primers. The limitations of MassTag PCR (and other PCR platforms)
were poignantly demonstrated during analysis of samples from Marburg hemorrhagic fever outbreaks in the Democratic Republic of Congo during 1998–1999
wherein two of five subjects were negative. The explanation for failure became
clear after cPCR amplification and sequencing revealed three mismatches in
the forward and one in the reverse primer (Palacios et al., 2006). If we had
enjoyed our current access to unpublished, proprietary filovirus sequences at the
time primers were designed, we would have averted difficulty in this instance.
Nonetheless, despite access to sequences in World Health Organization (WHO)
network laboratories, this experience reinforced the need for a complementary
tool with higher tolerance for sequence divergence, and led us to develop the
GreeneChip, a DNA microarray system.
Establishment of the Greene Microbial Database
A critical early step in the development of the MassTag PCR and microarray tools was the establishment of a viral sequence database. This effort was
facilitated in 2002 by the move of the ICTVdB (International Committee on
Taxonomy of Viruses Database) and its director, Cornelia Büchen-Osmond, from
Biosphere 2 (Earth Institute) in Oracle, Arizona, to the Greene Laboratory; and
the establishment of a Northeast Biodefense Center Biomedical Informatics Core.
Because vertebrate viruses are highest priority for human disease, we focused on
them first, with a plan to extend the database to viruses of invertebrates, plants,
and prokaryotes as resources permitted. To ensure comprehensive coverage, we
included every vertebrate virus listed in the ICTVdB, a taxonomic database that
describes viruses at the levels of order, family, genus, and species. Efforts to
identify cognate sequences for members of each of these taxa in the National
Center for Biotechnology Information (NCBI) sequence database proved to be
more difficult than anticipated. The NCBI database is not exhaustively curated;
thus, it contains many entries where annotation is missing, outdated, or inaccurate. An additional confound is that only incomplete sequence is available for
many viruses, bacteria, and parasites, particularly some relevant to this project,
where genomic sequencing efforts are less advanced. To circumvent limitations
in curation and nomenclature in the NCBI database, and to minimize computa See
http://phene.cpmc.columbia.edu.
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DETECTION AND DIAGNOSTICS
tional costs in establishment of multiple alignments at the nucleotide (nt) level,
we began construction of the Greene Viral Database (GreeneVrdB) by using the
Protein Families database of alignments (Pfam) and Hidden Markov Models
(HMM). Sequences for the design of oligonucleotide probes and MassTag PCR
primers were selected based on biological parameters, including the degree of
conservation of proteins or domains, their expression level during infection, and
the amount of data available for the respective region.
The GreeneVrdB was established by integrating the taxonomy database
of ICTV and the sequence database of NCBI (Figure 3-9). The majority of
viral protein coding sequences in the NCBI database (84 percent) were represented in the Pfam database; the remainder were mapped using pair-wise Basic
Local Alignment Search Tool (BLAST) alignments. A panmicrobial database
(GreenePmdB) was established by supplementing the GreeneVrdB with ribosomal RNA (rRNA) sequences of fungi, bacteria, and parasites obtained from
the Ribosomal Database Project (RDP)10 or the NCBI database. At the time
of this writing the GreenePmdB comprises the 382,512 viral sequences of the
GreeneVrdB, representing both complete and partial viral genomes; 41,790 bacterial 16S rRNAs; 4,109 fungal 18S rRNAs; and 2,626 18S parasitic rRNAs.
These sequences represent all 2,011 vertebrate virus species and 135 bacterial,
73 fungal, and 63 parasite genera.
GreeneChips
DNA microarrays have potential to provide a platform for highly multiplexed
differential diagnosis of infectious diseases. The number of potential features far
exceeds that with any other known technology. Furthermore, probes of up to 70
nt are not uncommon. Thus, unlike PCR where short primer sequences demand
precise complementarity between probe and target, DNA arrays are less likely
to be confounded by minor sequence mismatches. Lastly, one can incorporate
both microbial and host gene targets. This affords an opportunity to both detect
microbes and assess host responses for signatures consistent with various classes
of infectious agents. Despite these advantages, DNA arrays have not been widely
employed because of limited sensitivity. Although a viral array was helpful in
identifying the causative agent of SARS in 2003, critical to its success was the
discovery that the agent could be propagated to high titer and had cytopathic
effect in Vero cells (Ksiazek et al., 2003). Once this advance was shared, several
investigators rapidly and independently identified the agent by electron microscopy, differential display, cDNA cloning, microarray, and cPCR. The challenge
of array sensitivity has now been addressed with improved methods for sample
See
http://pfam.wustl.edu.
http://www.ncbi.nih.gov.
10 See http://rdp.cme.msu.edu.
See
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global infectious disease surveillance and detection
ICTVdB
NCBI sequence data
(International Committee on
Taxonomy of Viruses)
(National Center for
Biotechnology Information)
Panmicrobial sequence database
Viral sequence
database
382,512 viruses
382,512
41,790
bacteria
4,109 fungus
2,626 parasites
Pfam database
(Protein FamiIies)
RDP
(Ribosomal Database Project)
+
NCBI
FIGURE 3-9 Greene pathogen database.
SOURCE: Lipkin (2006).
preparation, amplification, labeling, and printing. Together with Agilent Technologies, we created a DNA array platform suited to analysis of clinical materials
without amplification in culture. Investigation
by MassTag PCR and viral DNA
3-9
microarray of blood collected during the 2005 Angola Marburg virus outbreak
from an individual who died of hemorrhagic fever failed to yield a pathogen;
however, implementation of a panmicrobial DNA array, GreeneChipPm, implicated Plasmodium falciparum infection (Palacios et al., 2007).
Microbial Probes
Viral probes were designed to represent a minimum of three distinct genomic
target regions for every family or genus of vertebrate virus in the ICTVdB.
Where possible, we chose highly conserved regions within coding sequence
for an enzyme such as a polymerase, and two other regions corresponding to
more variable structural proteins. Our reasoning was that RNAs encoding structural proteins may be present at higher levels than those encoding proteins
needed only in catalytic amounts, and that use of probes representing noncontiguous sites along the genome might allow detection of naturally occurring or
intentionally created chimeric viruses. The viral array has been through several
iterations as the database evolved and technology allowed increases in probe
density. The first release, GreeneChipVr1.0, comprised a total of 9,477 viral
probes. The second release, GreeneChipVr1.1, added 6,271 more typing probes
for influenza virus A hemagglutinin and neuraminidase genes. Recent releases,
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GreeneChipVr1.5 (15,700 probes) and GreeneChipVr2.0 (86,300 probes), are the
result of higher printing density on the Agilent array platform and a new generation of probe design algorithms. The process for identifying bacterial, fungal, and
parasitic probes was similar, although restricted to 16S and 18S rRNA sequences.
GreeneChipPm1.0 contained a total of 29,495 probes, including the probes comprising GreeneChipVr1.1 as well as 11,479 16S rRNA bacterial, 1,120 18S rRNA
fungal, and 848 18S rRNA parasite probes.
Host Gene Markers
Identification of signal(s) representing a microbe in samples from affected
subjects is a primary objective in pathogen discovery. Nonetheless, evidence of
infection is bolstered by coterminous evidence of gene expression consistent with
an activated host immune response. Furthermore, gene expression profiles may be
helpful in implicating specific strains or serotypes (e.g., Th1 cytokine responses
are more robust with H5N1 than H1N1 influenza infection) (Cheung et al., 2002).
Finally, in cases where we fail to find clear evidence of a known pathogen, a
profile consistent with immune activation may be helpful in determining whether
to pursue additional studies focused on pathogen discovery. Thus, GreeneChips
include probes for genes associated with cytokines, chemokines, and their receptors; components of the interferon-inducible signaling pathways; immunoglobulins (Igs) and Ig receptors; toll-like receptors and their downstream signaling
pathways; complement components; major histocompatibility complex (MHC)
molecules; and heat shock proteins from a set of validated oligonucleotides
(Wright and Church, 2002).
GreeneLAMP Analysis Software and GreeneChip Validation
GreeneLAMP (Log-transformed Analysis of Microarrays using P-values)
version 1.0 software was created to assess results of GreeneChip hybridizations.
Common analysis software focuses on the differential two-color analysis used in
gene expression arrays, which is not applicable to the GreeneChip. GreeneLAMP
has a robust and generalized framework for microarray data analysis, including:
flexible data loading, filtering, and control experiment subtraction. Probe intensities are background corrected, log2-transformed, and converted to Z-scores (and
their corresponding p-values). Where available, control matched experiments
from uninfected samples are used and spots >2 standard deviations (SD) from
the mean are subtracted. In instances where matched control samples are not
available, the background distribution of signal fluorescence is calculated using
fluorescence associated with 1,000 random 60-mers (Null probes). In both scenarios, positive events are selected by applying a false-positive rate of 0.01 (the
rate at which Null probes are scored as significant) and a minimum p-value per
probe of 0.1 (in cases with a matching control) and 0.023 (2 SD; in cases without
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a matching control). A map, built from a Basic Local Alignment Search Tool for
nucleotides (BLASTN) alignment of probes to the Greene Pathogen Database,
is used to connect probe sequences to the respective entries in the Greene Pathogen Database. Each of those sequences corresponds to an NCBI Taxonomy ID
(TaxID). The individual TaxIDs are mapped to nodes in a taxonomic tree built
based on ICTV virus taxonomy or NCBI taxonomic classification for other organisms. The program output is a ranked list of candidate TaxIDs. Candidate TaxIDs
are ranked by combining the p-values for the positive targets for that TaxID using
the QFAST method of Bailey and Gribskov (Bailey and Gribskov, 1998).
The specificity of the viral GreeneChip was assessed using extracts of cultured cells infected with adeno-, alpha-, arena-, corona-, entero-, filo-, flavi-,
herpes-, orthomyxo-, paramyxo-, pox-, reo-, and rhabdoviruses (a total of 49
viruses). All were accurately identified by GreeneLAMP analysis. To assess
sensitivity, viral RNA extracted from infected cell supernatants (adeno-, West
Nile, St. Louis encephalitis, respiratory syncytial, entero-, SARS corona-, and
influenza viruses) was quantitated by real-time PCR, serially diluted, and subjected to GreeneChip analyses. The threshold of detection for adenovirus was
10,000 RNA copies; the threshold of detection for the other reference viruses
was 1,000 RNA copies per reverse transcription (RT)-reaction. The respiratory
GreeneChip was tested for detection and typing with 31 influenza virus A and B
reference strains of human and animal origin and, because reference strains represent only a limited fraction of the genetic variability, with numerous circulating
human influenza virus strains isolated worldwide since 1999. In summary, a total
of 69 viruses comprising 54 influenza virus A and B isolates of human, avian,
and porcine origin and 15 non-influenza human respiratory viruses were tested,
identified, and subtyped.
GreeneChips were also validated with clinical samples from patients with
respiratory disease, hemorrhagic fever, tuberculosis, and urinary tract infections,
and were demonstrated to identify human enterovirus A, human respiratory syncytial virus A, influenza A virus, Lake Victoria marburgvirus, SARS coronavirus,
lactobacillus, mycobacteria, and gammaproteobacteria in various specimen types,
including cerebrospinal fluid, nasopharyngeal swabs, sera/plasma, stools, and
urine.
Recovery of Hybridized Sequences from GreeneChips
Arrays can facilitate cloning and sequence analysis as well as pathogen identification. Hybridized products typically range from 200 nt to >1,000 nt. Because
GreeneChips display three or more probes representing different genomic regions
for each virus, one can rapidly recover sequence not only for hybridized products
but also for sequences between those products through use of PCR.
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Unbiased High-Throughput Sequencing
The advent of high-throughput sequencing technology affords unique
opportunities for pathogen discovery. Unlike consensus PCR or array methods
where investigators are limited by known sequence information and must make
choices regarding the range of pathogens to consider in a given experiment,
high-throughput sequencing is unbiased. Several systems are in development. We
have experience with the pyrosequencing system of 454 Life Sciences; however,
the principles for sample preparation and data analysis are broadly applicable
across platforms. Because all nucleic acid in a sample (whether host or pathogen) is amplified and sequenced, elimination of host nucleic acid can be critical
to boosting pathogen signal toward the threshold for detection. Our approach is
to apply a similar sample preparation and random PCR amplification protocol
as developed for the GreeneChip including extensive DNase I treatment of the
RNA template to remove host chromosomal DNA. This process obviates the
potential for detecting DNA genomes of pathogens; however, our reasoning is
that an active infection should be associated with transcription. After amplification and sequencing reads typically range in size from 40 to 400 base pairs. Raw
sequence reads are trimmed to remove sequences derived from the amplification
primer and filtered to eliminate highly repetitive sequences. After trimming and
eliminating repeats, sequences are clustered into nonredundant sequence sets.
Unique sequence reads are assembled into contiguous sequences, which are then
compared to the nonredundant sequence databases using programs that examine
homology at the nucleotide and amino acid levels (using all six potential reading
frames with adjustments for sequence gaps). Specific PCR tests are then designed
to examine association with disease, measuring burden, and obtaining additional
sequence for phylogenetic characterization.
Vignettes in Pathogen Discovery
Borna Disease Virus and Neuropsychiatric Disease
In 1985, Rott and Koprowski reported that serum from patients with bipolar
disorder reacted with cells infected with Borna disease virus (BDV), an unclassified infectious agent named after a town in Saxony (eastern Germany) that had
large outbreaks of equine encephalitis in the late 1800s. Intrigued both by the
concept that infection might be implicated in a neuropsychiatric disease, and
that established methods for virus isolation had failed, we and others began to
pursue characterization of this elusive neurotropic virus using molecular tools.
BDV nucleic acids were isolated by subtractive hybridization in 1989, the first
successful application of subtractive cloning in pathogen discovery (Lipkin et al.,
1990). This effort relied on cDNA cloning with home brew kits as it preceded the
advent of polymerase chain reaction and ready access to sequencing technologies.
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global infectious disease surveillance and detection
The correlation between cloned materials and disease was achieved by demonstrating that (1) candidate cDNAs competed with RNA template from brains of
infected rats for transcription and translation of a protein biomarker present in
brain (hybrid arrest experiments), (2) the distribution of candidate nucleic acid
correlated with pathology in brains of experimentally infected rats and naturally
infected horses (in situ hybridization), and (3) no signal was obtained in Southern hybridization experiments, wherein normal brain was probed with candidate
clones. Based on northern hybridization experiments the genome was variously
reported as a 8.5 kb negative polarity RNA or an 11 kb positive polarity RNA.
Over the next 5 years, the genome was cloned, and the virus was visualized and
classified as the prototype of a new family of nonsegmented negative-strand
(NNS) RNA virus with unusual properties: nuclear replication/transcription,
posttranscriptional modification of selected mRNA species by splicing, low-level
productivity, broad host range, neurotropism, and capacity for persistence (Briese
��������
et al., 1992, 1994; Cubitt et al., 1994; de la Torre, 1994; Schneemann et al.,
1995; Schneider et al., 1994). It
�����������������������������������������������������
was widely held that the introduction of specific
reagents such as recombinant proteins and nucleic acid probes would allow rapid
assessment of the role of BDV in human disease. However, in a classic example
of the pitfalls of PCR diagnostics, particularly using nesting methods, BDV
was implicated in a wide variety of disorders that included unipolar depression,
bipolar disorder, schizophrenia, chronic fatigue syndrome, AIDS encephalopathy,
multiple sclerosis, motor neuron disease, and brain tumors (glioblastoma multiforme) (Lipkin et al., 2001; Schwemmle et al., 1999). At the time of this writing,
there is no conclusive evidence that BDV infects humans. BDV is nonetheless a
fascinating virus, and its discovery has yielded intriguing models of viral pathogenesis, and provided guidance regarding methods for rigorously investigating
the role of infection in chronic disease with sensitive molecular tools. It is worth
noting that the two years of molecular gymnastics required to identify BDV could
be collapsed into a few weeks with current art. However, even with the explosion
in viral sequence data over the past decade, BDV is sufficiently different that it
could not be identified by consensus PCR or microarrays based on sequences
other than those representing Bornaviridae. To our knowledge it is unique in
this respect.
West Nile Virus Encephalitis
In late August 1999, health officials reported an outbreak of encephalitis
accompanied by profound weakness in Queens, New York. There was neither an
apparent increase in the frequency of encephalitis in New York, nor an automatic
reporting event that resulted in detection of the outbreak. Thus, the recognition of
the syndrome was due to the clinical acumen of Deborah Asnis, an infectious diseases physician at Flushing Hospital Medical Center, and Marcelle Layton, Assis-
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191
tant commissioner, Communicable Disease Program, New York City Department
of Health, and their associates.
On September 3, serology for the presence of antibodies to North American
arboviruses yielded results consistent with infection with St. Louis encephalitis virus (SLEV) (Asnis et al., 2000). St. Louis encephalitis (SLE) had not
been reported previously in New York although mosquito vectors competent
for transmission of SLE were present. Investigation of the outbreak epicenter
revealed sites of active mosquito breeding and early victims of the outbreak had
histories consistent with mosquito exposure. Thus, on September 3, a mosquito
eradication program was adopted by the state and by the city of New York. Concurrently, wildlife observers independently noted increased mortality of avian
species, including free-ranging crows and exotic birds housed in the Bronx Zoo.
Tracy McNamara, a veterinary pathologist at the Wildlife Conservation Society,
performed histologic analysis of birds and found meningoencephalitis, gross
hemorrhage of the brain, splenomegaly, and myocarditis (Steele et al., 2000).
Although 70 percent of emerging infectious diseases are zoonoses and the coincidence between the human and nonhuman outbreaks was striking, McNamara
was unable to persuade her colleagues in human infectious disease surveillance
to review materials. She forwarded tissue samples from diseased birds to the U.S.
Department of Agriculture (USDA) National Veterinary Service Laboratory in
Ames, Iowa, where virus was cultured and electron micrographs reported to be
consistent with the presence of either a togavirus or a flavivirus. Thereafter the
avian virus was forwarded from USDA to the Centers for Disease Control and
Prevention (CDC) in Fort Collins, Colorado, for molecular analysis (Lanciotti et
al., 1999).
On September 13–15, the CDC Encephalitis Project (composed of centers
in California, New York, and Tennessee) held its annual meeting in Albany, New
York. Data emerging from both California and New York over an 18-month survey period indicated that an etiological agent was never identified in 70 percent
of cases of encephalitis despite culture, serology, and molecular analyses. In this
context, our group was invited to discuss methods for identification of unknown
pathogens and to consider application to project samples of a new method for
amplifying viral nucleic acids, domain-specific differential display (DSDD).
Sherif Zaki at CDC Atlanta had demonstrated the presence of flavivirus protein
in brains of human victims of the New York City outbreak; however, efforts to
amplify SLEV or other flaviviral sequences by conventional reverse transcription
PCR (RT-PCR) had been unsuccessful. Employing several degenerate primer
sets designed to target in DSDD highly conserved domains in the NS3, NS5, and
3’-untranslated regions of flaviviruses, we obtained positive results for four of
the five New York patients in only a few hours. Sequence analysis confirmed the
presence of a lineage one West Nile virus (Briese et al., 1999; Jia et al., 1999).
Concurrently, our colleagues at CDC in Fort Collins reported West Nile-like
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global infectious disease surveillance and detection
sequences in cell lines infected with homogenates from New York birds. In concert these findings confirmed that the outbreak in New York City was a zoonosis
due to West Nile virus (WNV).
Subsequently, we established quantitative real-time PCR assays for sensitive high-throughput detection of virus in clinical materials and mosquito pools.
Analysis of blood samples from infected humans revealed the presence of WNV
sequences in late 1999 (Briese et al., 2000); however, the significance of humanhuman transmission was not appreciated until 2002, when transmission through
organ transplants and blood transfusion led to implementation of blood screening
by nucleic acid amplification tests (CDC, 2003, 2004). This outbreak illustrates
the power of molecular methods for addressing the challenges of emerging
infectious diseases. As an example of an emerging zoonosis it also underscores
the significance of enhancing communication between the human and veterinary
medicine communities.
Enteroviruses and Amyotrophic Lateral Sclerosis
Amyotrophic lateral sclerosis (ALS) is a disorder characterized by progressive loss of motor neurons and muscle atrophy. An inherited form caused by
mutations in the superoxide dismutase gene has been described; however, the
majority of cases are idiopathic. In 2000 Berger and colleagues, using nested
PCR, sequencing, and in situ hybridization methods, reported the striking finding that 15 of 17 French subjects with ALS, and only 1 of 29 subjects with
other neurologic diseases had sequences of a novel echovirus in the spinal
cord (Berger et al., 2000). Although other enteroviruses such as poliovirus and
human enterovirus 71 have been unequivocally implicated in acute motor neuron disease, this publication was the first to provide compelling evidence that
enteroviruses could cause slowly progressive chronic neurologic disease. Given
the potential utility of antiviral treatment of this devastating neurodegenerative
disorder we were encouraged by the National Institute of Neurological Disorders and Stroke (NINDS) to try to independently replicate the echovirus data.
Our experience in the BDV field, where problems with PCR hygiene had led
to spurious links to disease, was invaluable in directing experimental design.
Whereas the Berger group had used RNA template extracted from sections cut
on cryostats and analyzed by nested PCR in the same laboratory, we collected
frozen tissues from two tissue banks, extracted RNA in a laboratory with no
history of virus research, and performed blinded real-time PCR analyses in yet
another laboratory. Real-time PCR is similar in sensitivity to nested PCR but is
less sensitive to false-positive results because assays are performed in a closed
system wherein signal is read as fluorescent signal. Analysis of spinal cord and
motor cortex from 20 subjects with ALS and 14 controls revealed no echovirus
sequences (Walker et al., 2001). These results were well received by colleagues
but elicited less positive correspondence from some individuals who noted that
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DETECTION AND DIAGNOSTICS
our publication was foreclosing a promising research lead and clinical trials
with antiviral drugs.
Future Perspectives
Technologies will continue to evolve, allowing faster, more sensitive, and
less expensive methods for pathogen surveillance and discovery. Although multiplex PCR is relatively mature, microarray technology is still in its infancy;
near-term modifications already in development include microfluidic sample
processing and direct measurement of conductance changes associated with
hybridization. We have only touched the surface of proteomics and host response
profiling. It is conceivable that biomarkers will be found that are specific for
classes of infectious agents and/or provide insights that can guide clinical management. In chronic diseases the most substantive advances are likely to come not
from technical improvements, but from investments in prospective serial sample
collections and an appreciation that many diseases reflect intersections of genes
and environment in a temporal context.
Acknowledgments
We thank our colleagues at the Scripps Research Institute, the University of
California–Irvine, and Columbia University who have enabled our work in pathogen discovery over a period of more than 20 years. Current efforts are supported
by National Institutes of Health awards AI062705, AI070411, HL083850-01,
AI51292, AI056118, AI55466, AI57158 (Northeast Biodefense Center-Lipkin),
NS047537, and EY017404.
THE POTENTIAL IMPORTANCE OF PRESYMPTOMATIC,
HOST-BASED DIAGNOSIS IN BIODEFENSE AND
STANDARD HEALTH CARE
Stephen Albert Johnston, Ph.D.11
Arizona State University
Abstract
Through programs such as BioShield, BioWatch, and BioSense we have
created a first line of defense against traditional biothreats—our Bio-Maginot
Line. However, the biotechnology revolution is driving the potential to create
engineered pathogens that could circumvent these barriers. The increased risk
inherent in this revolution is unstoppable, and efforts to control the risk through
11 Professor,
Life Sciences; director, Center for Innovations in Medicine, The Biodesign Institute.
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global infectious disease surveillance and detection
regulation are probably unwise. Fortunately, for historical and technical reasons
we may have a window of opportunity to get ahead of this threat curve. Key to
this opportunity is the development of a diagnostic capability that could detect
infections before symptoms appeared. This host-based detection system would
be capable of detecting any type of threat agent—engineered or natural. Key
aspects of this diagnostic system are that it would be capable of reading hundreds
to thousands of blood, sputum, or urine components; rely on self-normalization
by regular testing of individuals; and be widely distributed in homes. Evidence
to date indicates that it may be possible to develop such a system. Obviously, its
cost could not be justified by the unpredictable probability of a biothreat attack.
Fortunately, the need for such a capability for biodefense is exactly in line with
the need for the same capability to transform traditional medicine, most obviously
for detecting natural outbreaks. The current health-care system is economically
unsustainable. One solution to this crisis is to convert standard health practice
from one that treats symptoms to one that detects disease very early—even
presymptomatically. The convergence of the need for presymptomatic diagnosis
capability, both for biodefense and standard medical practice, justifies an Apollolike effort to create this technology.
Particularly since 9/11 there has been increasing concern about biological
attacks. In the area of detection of attacks, we are relying on two basic strategies.
One strategy, BioWatch, would have enough detectors distributed throughout the
country to pick up airborne releases of pathogens. The hope is that a biothreat
release would be detected before people develop symptoms. The problems with
this strategy have been widely debated, but largely come down to the cost–benefit
ratio of sustaining a system that would be effective. There is also the concern
that engineered organisms would not be detected. The second major strategy is
based on sufficient, organized surveillance of health-related data to detect early
evidence of symptomatic people. The BioSense program is one example of this
effort. Unlike BioWatch, this type of approach has a clear crossover advantage
to standard medical practice. However, in the specific application to biothreat
detection, it is dependent on detecting sick people.
Programs such as BioWatch (defined on page 4), BioShield,12 and BioSense13
have created a certain level of defense, largely against pathogens and scenarios
based on analysis from the past century. This Bio-Maginot Line would provide
a measure of defense against the obvious attack. As with the real Maginot Line,
the concern is that the attack would go around the fortifications (Figure 3-10).
Although no one can predict the risk of a future attack, let alone one that would
12 On
July 21, 2004, President Bush signed into law Project BioShield, which provides new tools to
improve medical countermeasures protecting Americans against a chemical, biological, radiological,
or nuclear (CBRN) attack (White House, 2004).
13 BioSense is a national program intended to improve the nation’s capabilities for conducting near
real-time biosurveillance, enabling health situational awareness through access to existing data from
health-care organizations across the country (CDC, 2007).
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195
FIGURE 3-10 The Bio-Maginot Line.
SOURCE: Johnston (2006).
3-10
involve an engineered organism, there is little doubt that the threat will increase
over time. As cartooned in Figure 3-11, this increase is largely due to the biotechnology revolution. The ability to both understand and manipulate life is increasing exponentially. Most measures of technological capability in biotechnology,
like microchips, are obeying Moore’s Law.14 Whether it be growth in sequence
deposits to GenBank (Figure 3-12), ability to sequence DNA, or facility at synthesizing genes, the revolution is amazing.
This revolution will drive remarkable change, but with it will come new
opportunities for ill application. For example, the science of interfering RNAs
started with some strange observations in plants in the 1990s. It progressed
quickly to study in animal systems and now is standard technique for manipulating gene expression. The technology is offered as kits, and several biotechnology
companies are pursuing its medical applications. A Nobel Prize was given for its
discovery in 2006, a record time from discovery to prize. Yet it takes relatively
little imagination to see how the incorporation of RNA interference (RNAi)
constructs into viruses might augment their virulence. Almost every new technology in biotechnology and almost every new understanding of immunology and
host–pathogen interactions could be configured to ill ends.
The same revolution that will drive dramatic new opportunities for contributions from biotechnology will increase the prospects for bad applications,
14 Moore’s
Law states that computing power will double every 1.5 years. This prediction has largely
held.
Copyright © National Academy of Sciences. All rights reserved.
1965
1970
1975
1985
1990
1995
DNA shuffling
1980
Copyright © National Academy of Sciences. All rights reserved.
Risk
FIGURE 3-11 Changing spectrum of biothreat risk.
SOURCE: Johnston (2006).
Genome
sequencing
Recombinant
DNA
1960
Natural pathogens
2000
2005
2010
2015
2020
2025
3-11 broadside
RNA i
Chemical gene
synthesis
Reverse viral genetics
Time
Antibiotic
resistance
Valley of the
shadow of
death
2030
2035
Biorevolution
2040
Decision
driven ∆
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Sequences (millions)
Base pairs of DNA (billions)
DETECTION AND DIAGNOSTICS
Base pairs
Sequences
FIGURE 3-12 Growth of GenBank, 1982–2005.
SOURCE: NCBI (2007).
or even accidental events. The opportunities are dynamic. The sequence of any
pathogen can be determined in one3-12
day. We are rapidly increasing our knowledge
of host–pathogen interactions and the human immune response to infection. As
stated above new technologies are being developed at a rapid pace. In addition,
the ability to set up high-throughput screens is becoming more common. The
combination of these trends will create the potential to create new pathogens
(Figure 3-13).
The impact of these trends is clear. We are moving from a relatively simple
threat space involving a list of potential pathogens and likely scenarios to one
that has much higher dimensionality (Figure 3-14). The implications are that
in the future, lists of relative importance of pathogens (e.g., Select Agent lists)
and likely scenarios of attack are going to become, if they are not already, less
useful.
That is the bad news. There is good news. For all the foreboding, a bioattack
has not occurred since October 11, 2001. Why not if the risk is increasing? There
are probably many explanations. One is that the Soviet biothreat program was
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global infectious disease surveillance and detection
Sequence
of all
microbes
Anything
you
want
New
technologies
Knowledge
of host, bugs,
and disease
mechanisms
HTP
screening
FIGURE 3-13 The combination of rapid knowledge and technological growth will create
the potential to make new pathogens.
SOURCE: Johnston (2006).
3-13
Number of variables
is increasing
NN df
N df
Anthrax
plague
smallpox
glanders
etc.
Any
combination
of microbe
and knowledge
Select Agent lists
scenario-based
strategies
FIGURE 3-14 The threat space is becoming increasingly complex.
SOURCE: Johnston (2006).
3-14
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DETECTION AND DIAGNOSTICS
decommissioned before the real revolution in biotechnology had penetrated their
operation. Second, Islam has placed biology as a low science. This was reflected
in the number of graduate students in biology versus engineering, though this
trend may be changing. Finally, making biothreat agents is still not easy. It would
involve multiple steps and specific reagents. Anything of this nature can easily
have one step go wrong. Of course if enough attempts are made, one will likely
succeed—but the odds are now in our favor.
We may now be in a grace period relative to preparing for a biological
attack—the valley of the shadow of death (Figure 3-11). If we continue to base
our preparedness on protection against specific pathogens or scenarios, we may
be in trouble. An alternative is to invest in developing platform technologies and
strategies that offer broad-based defense. Examples include developing systems
to generate and validate vaccines rapidly, and creating strategies to quickly produce new therapeutics to new pathogens from preexisting modules. However, I
think the most important shift in emphasis would be to host-based diagnosis to
allow presymptomatic detection of infections. The ability to detect infections
before they are symptomatic has obvious value to strategies from quarantine
to antibiotic treatment. It also addresses the problem of detecting the release of
a new pathogen as the sensing is the host itself. Detection is not dependent on
knowing what pathogens might be used.
The premise for this concept is presented in Figure 3-15. All of the factors
that determine a person’s health status could be monitored in near-real time by
Genes
Environment
Age
Serum/cell
components
Sex
State of
health
FIGURE 3-15 Biosignature pattern recognition in human diseases. Host-based presymptomatic detection of events.
SOURCE: Johnston (2006).
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global infectious disease surveillance and detection
profiling all the components of blood. Blood chemistry, or that of sputum or
urine, reflects changes in health, specifically early effects of infection. Continuous monitoring of blood components of healthy individuals would create their
own biosignatures of health and disease (Figure 3-16), the ultimate in personalized diagnostics. Devices capable of generating such biosignatures are already
in development. These units are aimed at a clinical setting largely for application to early detection or characterization of a specific illness, such as cancer. A
DocInBox diagnostic device relevant to biodefense would have to be capable of
detecting the early events of infection against the background of all other causes
of change in health status.
This type of biosignature diagnosis has two distinctive features. Approximately 45 biomarkers are FDA approved. In contrast, biosignatures would involve
measuring hundreds or possibly thousands of blood components. If the basis of
disease could be anything, one has to sample broadly. Second, real-time and
frequent monitoring of individuals would allow normalizing each person’s bio-
State of health
baseline
State of health
Continuous monitoring of the healthy
State of health
FIGURE 3-16 Personalized medicine based on biosignatures.
SOURCE: Johnston (2006).
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Sciences. All rights reserved.
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DETECTION AND DIAGNOSTICS
signature to himself or herself. This is in contrast to traditional biomarkers where
diagnosis is made based on values established in the population (Figure 3-17).
To meet these expectations the basic specifications for such a DocInBox are
clear. To detect a pathogen release, the unit must work in near-real time. Most
respiratory infections have a presymptomatic period of a few days at most (Figure
3-18). An assay system that takes a week to process has little value relative to
infections, but would for other chronic ailments. If the goal is presymptomatic
diagnosis obviously well people need to be monitored. Particularly for infectious
disease, it follows that the diagnostic devices should be in the homes or places
of work. Having these units in the physician’s office or emergency room will
do little good in detecting a biothreat release. If the units are to be dispersed in
homes, their operation must be rugged and inexpensive.
There are two issues relative to the possibility of attaining this goal. First,
is presymptomatic diagnosis of infections biologically feasible? The evidence is
scant in this regard. This topic will be the focus of a more extensive review, but
there are some positive indications. In vitro studies have shown that the transcription pattern of dendritic cells changes on exposure to pathogens and that different pathogens elicit different patterns (Huang et al., 2001). This is important as
dendritic cells are in the first line of exposure to pathogens. Microarray analysis
of human blood cells has shown that individual patterns can be monitored over
time (Whitney et al., 2003). Finally, it appears that microarrays of gene expres-
} Normal
Measure
Individual
T=0
Measure
T=1
Biosignature elements
FIGURE 3-17 Biosignatures versus biomarkers.
SOURCE: Johnston (2006).
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global infectious disease surveillance and detection
5 Days
Rhinoviruses
1-4 Days
Influenza
Parainfluenza
4 Days
Respiratory Syncytial
Virus (RSV)
7 Days
7-10 Days
Pertussis
5-8 Days
Adenovirus
Epstein-Barr Virus (EBV)
4-6 Weeks
I I I I I I I I I I I I I I I I I I I I I I I I I I I
1
5
10
15
20
Days
FIGURE 3-18 Upper respiratory disease incubation periods.
SOURCES: Adapted from Meneghetti (2006); Basu (1998); Smith et al. (2006).
sion can also detect presymptomatic responses in primates (Rubins et al., 2004).
3-18
We have preliminary evidence (Johnston and Magee, unpublished) from a model
of cowpox infection in mice that the infected mice can be distinguished from
mock-infected mice three hours after infection, also by microarray analysis of
blood cells. Clearly, more definitive studies of the limitations of presymptomatic
diagnosis are needed.
The other issue is the technological challenge of creating the diagnostic
system. This will be a formidable challenge. It will involve a coordinated, highly
interdisciplinary effort that will include new instrumentation, modeling/algorithm
development, data handling and transmission as well as judicious use of animal models and clinical testing (Figure 3-19). One challenge we have been
addressing is how to develop the binding agents to measure thousands of blood
components.
Though the technological challenges are great, such a diagnostic system is
probably feasible. If developed it would be a major factor in preventing largescale loss from a biothreat attack and may serve as a serious deterrent. However,
the effort and cost to put such a system in place could not be justified based
solely on the probability of a biothreat attack. Though its application to detection of natural outbreaks could be more easily supported, even this use would
probably not drive an economic imperative to initiate this development program.
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DETECTION AND DIAGNOSTICS
Human
studies
Data
management
Animal
models
Instrumentation
DocInBox
Computation
modeling
Biological
detection
Systems
biology
FIGURE 3-19 Program to create DocInBox diagnosis.
SOURCE: Johnston (2006).
Fortunately, a presymptomatic diagnostic system is also needed for another more
easily justifiable application—the impending crisis in standard health care.
The cost of U.S. health care was approximately $2.2 trillion in 2006. This
3-19
cost is estimated to be approximately $4
trillion by 2015 (Figure 3-20). Currently
this cost accounts for approximately 19 percent of our Gross Domestic Product
(GDP), rising to 25 percent or more by 2015 (Figure 3-21). By comparison,
health-care costs have outpaced energy costs since the 1980s (Figure 3-22).
Because most health costs are in the later years of life, with an aging population
these trends are expected to continue (Figure 3-23). Clearly, we spend an enormous amount of our wealth on health care. If this investment contributes substantially to the productivity and creative output of the population it is money well
spent. However, approximately 85 percent of this expenditure is on taking care of
sick people and only about 15 percent on drugs and diagnostics. Our health-care
system costs so much because it is largely postsymptomatic focused, and therefore centered on taking care of sick people. This system is clearly unsustainable
economically. It will require either reducing care or revolutionizing medicine. If
we opt for the latter, the key aspect will be converting medicine to a focus on
presymptomatic diagnosis. A corollary of this transition will be improvement in
quality of life. This will afford a “squaring” of the life curve (Figure 3-24) such
that we not only live longer, but better.
We are fortunate that a key technology required for being prepared for the
biothreats of the future is also the exact capability we have basically no choice
but to develop for standard health care of the future, as well as for more prob-
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Copyright © National Academy of Sciences. All rights reserved.
FIGURE 3-20 Health-care spending projections.
SOURCE: Adapted from HHS (2007).
3-20 broadside
$2.2T 2007
Total U.S. health-care expenditures ($)
$4T 2016
204
Copyright © National Academy of Sciences. All rights reserved.
3-21 Broadside to match 3-20?
18%
FIGURE 3-21 In 2005, 18 percent of GDP was spent on health care. By 2015, it is projected to be 25 to 30 percent.
SOURCE: Adapted from HHS (2007).
Total U.S. health-care expenditure
Gross Domestic Product
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global infectious disease surveillance and detection
Total U.S. energy spending
Total U.S. health-care spending
FIGURE 3-22 Comparison of U.S. spending on energy and health care, 1970–2004.
NOTE: The 2001 to 2004 numbers were projected based on oil prices. Total energy costs
2002–2004: Numbers are estimates based on extrapolation of energy price increase based
on increases in petroleum prices, applied to Department of Defense known energy use
figures. OPEC basket price averaged $50.71
per barrel in 2005, $36.05 per barrel in 2004,
3-22
$28.10 per barrel in 2003, $24.36 per barrel in 2002, $23.12 per barrel in 2001, and $27.60
per barrel in 2000 (DoE, 2006).
SOURCES: EIA (2005); HHS (2007).
$4, 500
$4, 000
$3, 500
$3, 000
$2, 500
$2, 000
$1, 500
$1, 000
$500
$0
All ages Under
25
25–34
35–44
45–54
55–64
65+
65–74
Age
FIGURE 3-23 Average annual health-care expenditures by age, 2005.
SOURCE: DoL (2007).
3-23
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75+
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Survival (quality)
DETECTION AND DIAGNOSTICS
0
0.2
0.4
0.6
0.8
1
1.2
Age
FIGURE 3-24 Human species needs to square life’s curve: Higher quality = less cost.
SOURCE: Johnston (2007).
able threats from natural infections. From the perspective of being prepared for
engineered biothreats, we should take advantage of the valley of the shadow of
death (Figure 3-11) to get ahead of the threat
curve. Presymptomatic diagnosis
3.24
should be a key element in this preparedness. From the perspective of standard of
care, this same technology could be key to revolutionizing us as a species. Such
potential merits an Apollo-like effort to complete.
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Resource Needs and Opportunities
OVERVIEW
Following workshop sessions that emphasized technical considerations for
infectious disease surveillance, detection, diagnosis, and reporting, the final session focused on relevant issues in public health policy, many of which had been
raised in prior discussions.
Global Coordination
The opening presentation, by Will Hueston, of the School of Public Health
and College of Veterinary Medicine of the University of Minnesota, describes
challenges in coordinating these vital public health activities. In his contribution
to this chapter, Hueston adopts a business perspective to analyze key technical
and social impediments to coordination. He explores how surveillance might
be repurposed as part of a system of disease detection, reporting, and outbreak
investigation; then he outlines political, technical, and educational measures that
would support such reform. By way of conclusion, Hueston employs business
strategic planning analysis to identify strengths, weaknesses, opportunities, and
threats inherent in current approaches to addressing infectious diseases.
Following Hueston’s presentation, a panel discussion explored diverse perspectives on resource needs and opportunities for infectious disease surveillance,
detection, diagnosis, and reporting. William Karesh, who spoke in a previous session about infectious disease surveillance in animals (see Summary and Assessment and Chapter 1), concurred with Hueston’s position that surveillance should
be designed to answer questions of long-term importance, rather than of present213
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global infectious disease surveillance and detection
day urgency. Noting that “society is healthier because more people understand
health,” Karesh advocated greater information sharing by public health officials
as a way to reduce, rather than increase, panic in response to disease threats, and
also to increase popular support for funding public health. He envisioned a twoway exchange of surveillance information, with the global public both supplying
essential data and receiving the benefits of its meaningful interpretation.
Panelist James LeDuc, Director for Global Health in the Institute of Human
Infections and Immunity at University of Texas Medical Branch, offered a concrete example of the potential for such “grassroots” surveillance: In Cambodia,
a network of “semitrained” villagers with cell phones and Mopeds swab sick
chickens and ducks to check for avian influenza and alert the health community to
suspected human cases. Multinational companies represent another newly tapped
source of global surveillance information; LeDuc noted that the Centers for Disease Control and Prevention (CDC) has established collaborations with a number of major companies operating in China, encouraging them to share signs of
unusual disease activity. He also identified two recent developments at the World
Health Organization (WHO) as significant opportunities for global coordination
in addressing infectious disease: the appointment to Director-General of Margaret
Chan, who has extensive experience in this area, and the ratification of the revised
International Health Regulations (IHRs; see Summary and Assessment).
On Location and in the Lab
In contrast to the global perspective taken by LeDuc, panelists Marci Layton,
Fernando Guerra, and Frances Downes offered local viewpoints on infectious
disease surveillance and detection. Layton, who had previously discussed local
public health surveillance as conducted by the New York City Department of
Health and Mental Hygiene (DOHMH; see Summary and Assessment and Chapter 1 overview), reemphasized that public health is an essentially local pursuit,
and that its most important asset is its infrastructure, particularly its workforce.
While acknowledging advantages in disease detection conferred by the increasing
volume of surveillance information available at the local level, she stressed the
importance of passing this inevitably noisy data through a “public health filter,”
embodied in “an epidemiologist looking at the data, a physician interviewing
other physicians to find out more deeply about a case, or field staff going out and
investigating the case.” This process converts raw surveillance data into “trustable” intelligence that avoids being premature or panic inducing, Layton said.
Guerra, Director of Health for San Antonio and Bexar County, Texas, works
with a population much smaller than that of New York City, but one that is similarly diverse and changeable. His experiences in building and using surveillance
systems, such as an immunization registry and tracking program, reveal the
profound influence of social circumstances on public health and their potential
contribution to “situational awareness” of disease threats, as discussed in prior
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sessions (see Summary and Assessment). The terms of reference for syndromic
surveillance need to be broadened, Guerra argued, and in particular should
encompass psychosocial and environmental circumstances.
Downes, Laboratory Director for the Michigan Department of Community
Health, discussed opportunities for improving infectious disease surveillance
from the perspective of the public health laboratory. Her contribution to this chapter, which summarizes her presentation, describes the creation and strengthening
of laboratory networks, the removal of barriers to disease reporting by laboratories, the role of information technologies, and the incorporation of syndromic
surveillance and disease diagnosis in the field. Given its unique position as “the
point at which laboratory science and public health surveillance intersect,” the
public health laboratory should lead the integration of nontraditional laboratory
surveillance sources into public health surveillance, Downes observed.
Funding
Nearly every panel member discussed some aspect of funding, beginning
with LeDuc’s blunt assessment that support for government and academic
research on public health is severely constrained, and will remain so for the
foreseeable future. As a result, he said, investments in disease surveillance and
detection must deliver the greatest value for money, and existing systems must
be subject to ongoing evaluation. LeDuc advocated a “transparent independent
investigation” of the federal BioSense (syndromic surveillance) and BioWatch
(aerosol detection) programs to determine whether they are truly answering
important questions. This would include considering the potential value of other
questions and/or systems and their applicability to standard clinical practice, as
well as for the detection of extraordinary disease threats. A similar argument was
taken up by panelist and speaker Ian Lipkin, director of Columbia University’s
Greene Infectious Disease Laboratory (see Summary and Assessment and Chapter 3), who noted that thoughtful investments in the surveillance and detection of
acute infectious disease may ultimately pay off in addressing chronic disease, in
which infections and immunity appear to play a role. Recognizing that funding
for surveillance tends to be tied to specific disease threats, LeDuc encouraged the
development of systems that can be adapted to a broad range of conditions (e.g.,
from avian influenza to any infectious respiratory disease).
Layton identified investment in infrastructure as key to improved disease surveillance by DOHMH. “That means people,” she explained. “It means field surveillance staff. It means public health nurses. It is physicians, laboratory support,
environmental health scientists, veterinarians, and . . . information technology
experts to allow us to process information and respond to it. Syndromic surveillance allows me to know what is going on in the city,” she continued, “but the
ability to do that [results from a] tremendous investment in staff infrastructure.”
Similarly, Downes noted that “the collection and analysis of surveillance data
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global infectious disease surveillance and detection
is only one part of the challenge of responding to emerging infectious diseases.
Epidemiologic and laboratory resources are needed to investigate early warning
signals and take actions to interrupt continued disease transmission.”
Workforce Issues
Several panelists identified a shrinking public health workforce as a challenge to infectious disease surveillance and detection, due in part to the relatively
low salaries of public health professionals. To encourage the kind of interest and
commitment necessary to produce the next generation of public health practitioners, Lipkin suggested engaging the media. “The number of kids who are
interested in forensics as a result of CSI has gone up dramatically,” he noted.
“Why not do something similar in public health?” Karesh argued for rewarding researchers who pursue the public good as their primary goal; for example,
those who release key information prior to publication, and those whose negative
results are difficult to publish, despite their epidemiological value.
COORDINATION OF DISEASE SURVEILLANCE,
DETECTION, DIAGNOSTICS, AND REPORTING
William D. Hueston, D.V.M., Ph.D.
University of Minnesota
Most of the presentations at this forum have focused on the technical aspects
of surveillance, diagnostics, and detection. My presentation will focus primarily
on the challenges of coordination as a leadership responsibility and management
imperative, with coordination defined from a business perspective: “Synchronization and integration of activities, responsibilities, and command and control
structures to ensure that the resources are used most efficiently in pursuit of the
specified objectives” (BusinessDictionary, 2007). Before I address these broad
issues, however, I would like to introduce five technical impediments to the coordination of infectious disease surveillance across animal and public health.
Technical Impediments to Coordination
First, there is the challenge of incorporating surveillance into the information
architecture of medical and veterinary medical business systems. Medical and
veterinary facilities decide to implement information systems when the benefits
outweigh the cost of installation and support. Most medical records systems are
designed to collect and compile records to enhance business efficiency, an obvious benefit that reduces the volume of paper records and the personnel needed to
College
of Veterinary Medicine and School of Public Health.
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compile the records. Generating bills and tracking cost center performance present different information management challenges than analyzing agent, host, and
environment data to support surveillance systems and epidemiological analyses.
Although the benefits of having a national or global surveillance system may
be readily apparent on a societal level, there may not be a visible return on the
investment required for an individual business to participate. Surveillance and
epidemiology generally are viewed as public goods, that is, the benefits accrue to
the whole society. Hence individual institutions and businesses often are reluctant
to participate in national surveillance programs without some inducement such
as government grants or preferred insurance rates, or some penalty, like a legal
requirement for involvement. Understanding the “value proposition” is critical
to forming productive collaborations.
A second challenge involves the lack of a common lexicon, so that certain
terms have different meanings in different disciplines. Various ontologies exist
to annotate biological terms such as the International Classification of Diseases
(ICD) and Standardized Nomenclature for Medicine (SNOMED) for human
medicine, and the Standardized Nomenclature for Veterinary Diagnoses and
Operations (SNVDO) and Standardized Nomenclature for Veterinary Medicine
(SNOVET) for veterinary medicine. The challenges of defining an integrated
human/veterinary system are myriad, such as rectifying hand versus paw versus
hoof naming conventions and adding population data—a cow is a member of a
herd and a chicken a member of a flock, where the population data represent one
element of the diagnosis. Although substantial progress has been made, no global
standard has emerged for an ideal medical vocabulary for use in both human and
veterinary medicine.
A third issue is the need for standardized communication protocols that
enable surveillance, detection, and response systems to share data and results in
real time. In this age of high-tech communications and increasing international
travel, a classic example of the lack of standardization exists with the differences in cell phone or videotaping protocols between the United States and
Europe. Agreeing on a standardized approach can be a monumental undertaking,
such as establishing an animal identification system in the United States. The
U.S. Department of Agriculture’s Animal and Plant Health Inspection Service
(APHIS) worked for years with a variety of stakeholders to reach a decision to
move ahead with a 15-character animal identification number, a 13-character
group/lot identification number, and a 7-character premises identification number
(USDA, 2006).
A fourth concern is how to secure the resources to support surveillance, particularly global surveillance. Despite widespread recognition of the importance
of global surveillance for the public good, health-care systems are nationally
based and, in a number of countries, funded largely by third-party payers and
user fees. The development of the Global Early Warning Systems (GLEWS)
in 2006 represents the first joint early warning and response system combining
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global infectious disease surveillance and detection
and coordinating the separate surveillance activities of the World Organization
for Animal Health (OIE), the Food and Agricultural Organization of the United
Nations (FAO), and the World Health Organization (WHO) (WHO, 2006). However, the GLEWS coverage is variable, reflecting huge differences in the capacity
of individual countries in terms of their laboratory resources, trained personnel,
internal surveillance systems, and reporting capabilities.
Confidentiality provides a final example of the technical challenges for
coordination. Even when secure communications can be guaranteed, protecting
individual privacy, proprietary business information, and sensitive national security data are topics of intense debate. Strategies like summarizing individual data
to produce group statistics may obscure the very trends that are of public health
interest. Differing objectives may bring those who provide the data and those who
compile and report the data into conflict. Examples include “shunning” of individuals who test positive for a disease despite a low risk of transmission during
casual social contact; regulatory action on voluntarily participating farms after
detection of an agent of concern; changes in consumer purchasing patterns of
finished products based on comparison of contamination rates on raw ingredients
before processing; and imposition of trade restrictions following the voluntary
reporting of an animal disease agent detection considered to pose only a limited
risk to production agriculture, such as detection of a low-pathology strain of avian
influenza in wild birds.
Paradigm Impediments to Coordination
Our collective approach to surveillance is framed by the prevailing paradigms of our society. Currently, coordination of disease surveillance, detection,
diagnostics, and reporting is stymied by an overriding philosophical framework
comprising our public health focus, our definition of health, our perspective on
risk, our fascination with disease agents, our propensity to glorify emergency
response, and our preoccupation with technology. A series of examples will help
to illustrate these challenges:
• Despite the fact that public health surveillance is all about populations,
we tend to think in terms of the individual. Individual stories galvanize public
action as they personalize stories of illness, pain, and death. Betty Ford’s breast
cancer and Rock Hudson’s AIDS diagnosis are often cited as turning points for
U.S. public health policy for these diseases. Furthermore, our focus tends to be
parochial, evaluating public health priorities from our personal and local perspectives rather than considering the world at large.
• We tend to define health as absence of disease; success as complete cure
or eradication of an infectious disease scourge; the primary public health function
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as rapid response to crises; and our compelling public health vision as zero risk.
In stark contrast, physicians explain that we can achieve a high quality of life
despite a number of illnesses and afflictions; economists argue that the focus on
eradication of disease is not optimal use of our health-care dollars; decreasing
prevention budgets contribute to the occurrence of crises needing rapid response;
and scientists point out that zero risk is unachievable.
• All too often we focus our infectious disease resources on the agent,
ignoring the web of causation, including genetics, host immunity, and social
and environmental factors. By focusing disproportionately on the agent, we fail
to adequately track host and environmental risk factors that contribute to the
emergence and reemergence of infectious diseases and we are lulled into the
erroneous conclusion that successful risk management depends on identification
of the specific agent. However, agent identification was not a prerequisite for the
public health heroes who made important contributions prior to the formulation of
the germ theory of disease, such as Ignaz Semmelweis (whose advocacy of hand
washing drastically reduced mortality due to puerperal fever) and John Snow (a
father of epidemiology, who gathered evidence that linked the spread of cholera
with water contaminated by waste from infected people).
• We are strongly influenced by what I call the “John Wayne mentality,”
which dictates that when something goes wrong, someone is to blame and that
party must be hunted down and punished and thereby, the problem is solved
(often this mindset results in a case of shooting the messenger). We wholeheartedly embrace the war metaphor, wherein public health wages battles against
infectious diseases. Such conflicts have winners and losers, and it is our job to
win; indeed, victory over infectious disease was prematurely declared by U.S.
Surgeon General William H. Stewart in 1967 (IOM, 2006, particularly pp. 1-2).
• We are fascinated by technology. Even though few of us use even a
fraction of the power of our computers or cell phones, we rush to upgrade to
the latest and greatest improvement of speed, graphics, communications, and
games software. While partially inured to the exaggerated claims of biotechnology, genomes, and pharmaceuticals, we still cling to the hope that technology
will provide the silver bullet. When we complete careful reviews of our public
health program failures, technology is rarely the culprit. The lack of people
skills—including leadership and teamwork—is far more commonly cited as a
major contributor to public health program underperformance than a shortage
of technology. Disciplinary silos and professional egos are more damaging than
absence of the latest “techno-solution” or “miracle-mycin.”
Coordination as a Leadership and Management Imperative
The overall high health status of people and animals in the United States
contributes to the prevailing attitude of “if it ain’t broke, don’t fix it.” Our comparative good health also leads us to focus on the “disease du jour” or the crisis
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global infectious disease surveillance and detection
of the moment rather than prioritizing our investments by the potential impact
they can make on measures of population health such as infant mortality, risk
factor avoidance, or adolescent pregnancy. In the absence of a headline-grabbing
outbreak or the untimely demise of a celebrity, we are loath to fund surveillance
systems that could anticipate such threats and trigger proactive prevention campaigns. Success in a disease control program often is met with reduced funding
or elimination of the surveillance and disease detection programs on which the
success was based. As an example, the successful U.S. campaigns against the
zoonoses bovine brucellosis (undulant fever in humans) and bovine tuberculosis
(one form of tuberculosis in humans) depended on a traceability system that
allowed affected cattle detected at slaughter to be traced back to their herd of
origin. Given the eradication successes, however, funding was dropped for the
identification systems and the United States has slipped backward in its ability to
trace cattle back to the farm of origin. While the most highly trained fire-fighting
unit in most communities—that of its local airport—is rarely used, our tendency
is to decommission surveillance, detection, diagnostic, and reporting infrastructures when the disease of concern becomes rare.
An Alternative World View
Coordinating surveillance requires that we “begin with the end in mind,” as
Stephen Covey memorialized (Covey, 1989). What is the surveillance intended
to accomplish? Why is coordination important? How will the surveillance results
be used? What benefits will the surveillance yield for those who are expected
to participate? Presumably the overarching goal of coordinated surveillance is
improvement of public health, that is, the health of the community. Public health
involves identifying problems, setting priorities, formulating policies to address
these priorities, promoting health and preventing illness, and providing access
to health care.
Achieving these lofty public health goals requires a very different paradigm
characterized by a global perspective, a focus on health, an ecosystem approach
(agent, host, environment), a risk management goal, prioritization based on
importance rather than urgency, and a commitment to working with people to
manage the dilemmas rather than seeking a technology quick fix (Table 4-1).
We increasingly recognize that we live in a complex world of microbial
ecology, a world in which microbes are ubiquitous and adaptive and in which
disease and emergent disease is the norm rather than the exception. If we think
of surveillance only in terms of agent detection, we will not be able to effectively
manage these new risks. For example, initial responses to recent foodborne disease outbreaks in leafy greens demonstrated a lack of understanding of complex
food production and distribution systems. These complex systems must incorporate multiple critical control points including the application of best practices and
targeted monitoring and feedback loops.
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RESOURCE NEEDS AND OPPORTUNITIES
TABLE 4-1 Current Public Health Paradigm and Alternative World View
Current Paradigm
Alternative World View
Health is absence of disease
Health is well-being (in mind, body, spirit)
Infectious disease is all about the agent
Infectious disease emerges at the convergence
of agent, host, environment
Zero risk is achievable
Zero risk is unachievable; risk management is
the goal
Success is eradication/cure
Success is homeostasis with microbes that are
ubiquitous, constantly evolving and adapting
Public health function is to react
Public health function is health promotion
Reaction requires agent detection
Risk management can be successful whether or
not microbe is identified
Urgency dictates priority
Surveillance informs policy and guides action
on basis of importance
Answers lie solely in technology
Answers involve people, politics, partners
SOURCE: Hueston (2006).
Real-time surveillance of food products and their raw materials must be
combined with quality control and food safety systems in processing and distribution, sensitive public health disease detection, prompt reporting, and rapid
outbreak investigation. The entire food system must retain the flexibility to adjust
its risk management strategies to changing risk factors (hosts, agents, and the
environment) without waiting for outbreaks to occur. Without a dynamic and
adaptive food safety system, significant resources will be squandered on useless
activities such as large recalls announced after most of the product has already
been consumed.
The Politics of Coordination
Coordination is all about politics, which I define as the interpersonal dynamics that occur whenever two or more people are gathered together. Politics of
societies are influenced by culture, and the organizational culture of the various
public health agencies and the regulated industries is as germane to the practice of
public health as is ethnicity, gender, religion, and other factors. To coordinate—to
harmonize in common action and effort—requires effective political processes
over the long term. “People skills” are needed to build coordination and collaboration, yet the social sciences are rarely emphasized—or even mentioned—in the
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global infectious disease surveillance and detection
programs that train doctors, public health professionals, veterinarians, and plant
pathologists. Interpersonal and teamwork skills are described as “non-technical”
or “soft skills” and omitted from the curriculum. As has been demonstrated time
and time again, university faculties assume that students “ought to know all that
stuff before they get into graduate school or professional school.”
Toward Optimal Surveillance
The optimal surveillance system is integrated and dynamic, with ongoing
data collection. Real-time analysis would generate information relevant to risk
management that would in turn drive policy and action. This ideal surveillance
system incorporates feedback processes, permitting continuous, evolutionary
change. It would integrate information on infectious disease in humans, domestic
animals, wildlife, and plants collected and maintained through cross-disciplinary
collaboration such as plant pathologists working in public health or psychiatrists
working in veterinary medicine.
What is the way forward toward such a “system of systems?” Beginning with
the end in mind, we need to prioritize public health goals. We need to complement agent surveillance with host and environmental monitoring. We need to
recognize that societal stability and economic security are critical for maintaining
a functional public health infrastructure, and find ways to make “doing the right
thing” both beneficial to society and profitable for the private sector. We need
multiple functional models that will work in the developing world as well as
in industrialized countries. The information systems we need to develop would
support global public health. Finally, because we can anticipate many future challenges, we must incorporate capacity for adaptation into the design of integrated
surveillance systems.
Changing the Prevailing Paradigms
There is no magic formula for changing paradigms. However, change can
occur incrementally, by rewarding progress no matter how slow, and then identifying, documenting, and celebrating successes, large and small. Fostering paradigm
change is difficult, requiring a number of simultaneous activities, including:
• We must nurture a new generation of public health professionals who
adopt a holistic, global perspective of health, and who look for creative ways
to manage risks. We need to imbue these emerging public health professionals
with a commitment to transdisciplinary approaches. We also need to encourage
them to embrace change and be adaptable in a world that will never be risk
free.
• Combining experiential learning opportunities with more didactic educational approaches will enable our new public health professionals to be more
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effective, to be more adaptive, to understand complex challenges and opportunities, and to manage the complex dilemmas of the future.
• We must establish a robust, global public health infrastructure that incorporates interoperable high- and low-tech solutions, such as the cell phone surveillance system described in this report (see Johnson and Blazes in Chapter 2). Like
Voxiva, we need to bring cultural anthropologists into health delivery teams to
examine motivators for promoting public health in different cultures.
• We must examine the ethics of surveillance, and in particular the question as to whether effectively contained disease outbreaks need be reported to the
public. I found the HealthMap presentation (see Brownstein in Chapter 2) both
exciting and frightening, because it labels countries as to whether or not they
have a given infectious disease within their borders. Although that knowledge
may help us to detect global disease patterns and target intervention resources,
it also has the potential to set back international development, given that reports
of infectious disease can lead to trade embargoes and reductions in tourism and
investment. This, in turn, will decrease infectious disease reporting. Futhermore,
labeling an entire country in terms of disease presence or absence acts against
the recognizing potential to safely establish free zones or even agricultural enterprises within a country where a specific disease is widespread.
• Finally, we must build public–private partnerships for global health. While
public funding will always be constrained by other societal demands, we can
identify potential benefits of improving public health in ways that make sense to
corporations. The private sector can move much faster and contribute a wider array
of resources toward those shared public health goals than the public sector can.
Strengths, Weaknesses, Opportunities, and Threats
SWOT analysis emerged in the 1960s and 1970s as a strategic planning
tool used to evaluate the Strengths, Weaknesses, Opportunities, and Threats of
a project or initiative. Looking at current disease surveillance, detection, diagnostics, and reporting systems, we can draw several conclusions from a brief
SWOT analysis.
The public health dilemmas of infectious diseases are global, not local. While
our local strengths include the vast array of technology and data at our disposal, our
principal weakness is the disparate global environment in which we must operate,
where countries vary greatly in terms of infrastructure capacity, human and fiscal
resources, and commitment to public health. We are also plagued by the disconnect between surveillance and action, which is exacerbated by the misconception
of surveillance as a goal, rather than as a means to an end.
Progress toward integrated, global surveillance is threatened by the potential
for unintended consequences. The potential for surveillance to deepen the firstworld/third-world divide is a huge threat to global coordination and collaboration. Thus we need to discuss the possible consequences—both intended and
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unintended—with our stakeholders and the beneficiaries we serve, both domestically and globally.
A key opportunity lies in the possibility of developing an overarching, integrated, global surveillance plan that will take us out of our disciplinary silos—a
plan that sets priorities based on global considerations of public health impacts
and identifies the resources necessary for coordination. These priorities necessarily must balance the potential impact on and the degree of buy-in from the
community that they are meant to serve. Experience has taught me that ideal
solutions lacking community support will fail, while popular, partial solutions
will succeed. We must be willing to address today’s complex public health dilemmas one small step at a time. After all, as I am frequently reminded by a mentor,
“slow progress is progress.”
Finally, we have a tremendous opportunity to foster a new generation of
global public health leaders who will catalyze coordination through very different paradigms than those held today. Progress toward coordinated surveillance
will be accelerated by active transdisciplinary leadership development programs
in global public health.
Defining Success
How can we measure our progress toward global coordination of infectious disease surveillance, detection, diagnostics, and reporting? A successful
system will allow us to more effectively anticipate new threats and will adapt
fluidly to manage risk under novel conditions. It will encourage the formation
of public–private partnerships to support surveillance. New leaders will step
forward to promote international collaboration toward shared goals. Finally, we
will know we have succeeded when we can document incremental improvement
in global public health.
IMPROVING INFECTIOUS DISEASE SURVEILLANCE AND
DETECTION: A PUBLIC HEALTH LABORATORY PERSPECTIVE
Frances Pouch Downes, Dr.P.H.
Michigan Department of Community Health
The practice of infectious disease surveillance has co-evolved with the public health laboratory to address important health concerns with ever-advancing
technologies. This ongoing partnership is essential to the continued improvement
of surveillance systems. Public health laboratories in the United States are major
contributors of infectious disease reports. In Michigan, for example, 60 percent
of all laboratory results in the Michigan Disease Surveillance System are received
Laboratory
Director.
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from the state’s public health laboratory. Nationally, public health laboratories
perform more than 40 million tests annually and are responsible for generating
35 to 65 percent of all positive laboratory findings for reportable diseases (APHL,
2002).
This essay examines key opportunities for improving infectious disease
surveillance from the perspective of the public health laboratory. These include
the creation and strengthening of laboratory networks; the acknowledgment and
removal of barriers to disease reporting by laboratories; the adoption and adaptation of information technologies by and for laboratory use; and the extension of
the laboratory–surveillance partnership to refine and validate syndromic surveillance and rapid field diagnosis of reportable diseases.
Establishing Laboratory Networks
Surveillance benefits from the collection of comprehensive data from diverse
sources, and public health laboratories can play an instrumental role in facilitating
and garnering support for this process. The public health laboratory community
increasingly has embraced the concept of laboratory networks that enable a wide
variety of laboratories to contribute their testing results to surveillance and disease control databases. Examples of current and potential laboratory networks are
described in the following paragraphs.
The National Laboratory System
In 2001, the Centers for Disease Control and Prevention (CDC) launched
pilot programs in four states (Michigan, Minnesota, Nebraska, and Washington)
to implement a National Laboratory System (NLS) of statewide laboratory networks (CDC, 2004). Since the initiation of the NLS, many public health laboratories have undertaken network development programs within their states that
improve public health response and surveillance through partnerships with traditional and nontraditional partners, including clinical and hospital laboratories,
health advocacy organizations, agriculture and veterinary laboratories, and commercial laboratories.
Integrated Surveillance Networks
The public health laboratory is the juncture at which medical laboratory
science and public health surveillance intersect. Due to this unique position, the
public health laboratory must provide the leadership to forge relationships that
eventually will lead to the integration of nontraditional laboratory surveillance
data sources into public health surveillance.
Recent infectious disease emergence and foodborne disease outbreaks demonstrate the need for public health surveillance to integrate nontraditional sources
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global infectious disease surveillance and detection
of data. Peanut butter, fresh spinach, and tomatoes recently have been identified
as vehicles of enteric bacterial infections. In these examples, improved access to,
and monitoring of, agriculture and food processor laboratory results by public
health practitioners may have enabled earlier identification of disease activity
and outbreaks. Because most emerging infectious diseases are zoonotic, animal
diagnostic testing is clearly another rich source of data to collect for improved
surveillance of emerging, reemerging, or novel infections.
Technical and Professional Networks
Although network-building activities rarely involve increased screening or
testing for public health laboratories themselves, public health laboratories undertaking these efforts frequently provide technical training (e.g., in rapid screening
for bioterrorism agents), consultation (e.g., on antimicrobial resistance testing),
and feedback (e.g., the use of laboratory reports for surveillance and outbreak
response). Network development also encourages the development of best practice guidelines for tests of public health importance (e.g., rapid HIV testing,
estimated glomerular filtration rate, cholesterol screening). Even simple efforts
such as the development of educational materials or tools and presentations to
remind laboratorians about the importance of their role in disease reporting, or
the participation of public health laboratories in state and regional clinical laboratory professional organizations, can ultimately improve the completeness and
timeliness of disease reporting. Equally important, technical and professional
networks develop relationships among organizations that can work together to
refine surveillance systems through the use of mechanisms such as electronic
medical record exchanges and electronic laboratory reporting.
Addressing Barriers to Reporting
To improve the timeliness and completeness of reporting by laboratories,
and thereby the quality of surveillance, the following critical barriers must be
addressed.
Reporting Costs
The cost of preparing and shipping isolates and specimens to public health
laboratories for reference and molecular epidemiology testing are not reimbursed
by third-party insurance providers or public health agencies. Recent changes to
the U.S. Postal Service (USPS) regulations prohibiting the use of the USPS for
shipping infectious agents have only exacerbated this problem. For example,
some states require that clinical laboratories submit their public health laboratory
isolates of Mycobacterium tuberculosis and other microbes. These isolates must
now be shipped to public health laboratories by commercial courier services that
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attach a $50 surcharge to each infectious agent shipment. The burden of this cost
is borne by the clinical or other originating laboratory and is not reimbursable by
public or third-party insurers.
Shrinking Workforce
The medical laboratory is beginning to see the first signs of a looming shortage of trained professionals. Between 1980 and 2003, the number of medical
technology programs declined from nearly 800 to 240, and the annual number of
graduates of accredited programs declined from 6,184 to 1,668 (Personal communication, S. Anderson at the 2004 Clinical Laboratory Education Conference).
The laboratory professional workforce will be exacerbated as the majority of the
workforce reach retirement age in the next two decades. Less than 10 percent
of the laboratory professional workforce is eligible for retirement now, but in
the next 10 years, approximately 40 percent of the current workforce will be
eligible, and in 15 years 62 percent will be eligible (Personal communication, S.
Anderson at the 2004 Clinical Laboratory Education Conference). Vacancies due
to an inadequate pool of qualified candidates translate into less time available to
prepare and ship isolates and specimens to public health laboratories, prepare and
submit reports of reportable diseases to public health agencies, and participate in
training on emerging health issues and disease reporting.
Labor-Intensive Methods
Antigen detection and other simple point-of-care tests, among other emerging testing technologies, may be more rapid and require less equipment and
labor. However, public health reference and molecular testing used to detect and
investigate disease outbreaks often requires a microbial isolate. For example,
isolates of suspect Mycobacterium tuberculosis must be available for public
health testing using currently practiced methods for the public health testing of
reference level identification (Metchock et al., 1999), antimicrobial susceptibility
testing (NCCLS, 2003; Plikaytis, 1992), and genotyping (Cowan et al., 2002).
Public health laboratories may need to perform more preliminary testing to
obtain isolates from rapid test specimens and work with front-line practitioners
to assure quality of point-of-care tests and collection of additional specimens for
confirmatory and molecular epidemiology testing. Eventually, alternative public
health laboratory confirmatory and typing methods that do not require microbial
isolates will need to be developed.
Standardized Reporting
Laboratory testing to identify potential cases of reportable disease is increasingly performed for multiple states by commercial clinical laboratories. Com-
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global infectious disease surveillance and detection
municable disease reporting requirements, however, vary from state to state.
Reporting and isolate submission compliance by multistate laboratories will
only improve when states standardize reporting and isolate submission lists and
formats.
Adoption and Adaptation of Information Technology
Information technology that can improve current surveillance systems is
available, but it has not been universally adopted. CDC’s Public Health Information Network (PHIN) standards make adopting this technology nationally
feasible. As with the establishment of laboratory networks, trust and resources
are needed to achieve data exchange between the clinical laboratory and public
health surveillance systems in the following critical areas.
Electronic Laboratory Information System Reporting
As noted in the contribution by Joseph Lombardo (see Chapter 1), many
hospitals use the Health Level Seven (HL-7) format, which can create a message from the originating laboratory information system and transfer it to a
surveillance information system that captures and stores disease surveillance
data for case investigation and data analysis. Widespread adoption of electronic
laboratory reporting would eliminate the current slow, labor-intensive practice
of transcription of results from a laboratory information system to a paper form
and submission by mail or reentering results to a web-based interface with the
surveillance system. Broader adoption of this faster and more complete method
of laboratory reporting may require additional linkage to hospital information
systems that contain patient-specific information not available in the laboratory
information system. Also, resource commitment is required from both the clinical
laboratory and the surveillance system to initiate and maintain electronic laboratory reporting.
Electronic Health Records
Regional initiatives are underway to develop electronic health record
exchanges throughout the United States. While economics and quality of care
are often the motivating forces in the development of the health information
exchange networks, these networks can and should be designed and used for public health surveillance (and registry) reporting. Public health entities are able to
The
PHIN is CDC’s vision for advancing fully capable and interoperable information systems in
the many organizations that participate in public health. PHIN is a national initiative to implement a
multiorganizational business and technical architecture for public health information systems (CDC,
2007).
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receive patient-specific health information while still complying with the Health
Insurance Portability and Accountability Act (HIPAA).
The Role of the Laboratory in Syndromic Surveillance and Field Diagnosis
Syndromic Surveillance
Novel surveillance systems are being piloted and used in a variety of settings for a variety of uses. Laboratory-based reporting is highly specific but not
sensitive; conversely, syndromic surveillance is very sensitive, but not specific.
Syndromic surveillance systems are designed to detect large-scale events clustered in time and space. They will not detect low-frequency events like the first
cases of disease outbreak.
Syndromic surveillance systems can complement, but cannot replace, traditional case and laboratory-based reporting systems. Syndromic surveillance
system data should be validated periodically with traditional case confirmation
and laboratory testing methods. It is also important to evaluate programmatic
investments in syndromic surveillance early warning systems, such as BioSense
and BioWatch, to determine if they have been used as intended and if the investment is warranted (GAO, 2005).
Field Diagnosis
Global public health surveillance and clinical patient care may benefit from
easily performed microbe-specific rugged tests. The “gold standard” tests are
essentially unavailable in many parts of the world and are often so time consuming that they stymie disease control efforts. Exciting advances in the development
of field-ready diagnostics are resulting from public–private partnerships. However, investment in such technology should not supersede investments or precede
efforts in total quality systems.
A comprehensive laboratory quality system approach is relevant for any test,
whether it is complex or simple to perform, and in any testing setting, whether
it is the traditional laboratory, the clinic, or the field (CLSI, 2004). Inaccurate
results generated from unmonitored testing can lead to misdirected patient care,
inaccurate disease reporting to surveillance systems, and wasted resources. When
rugged, simple field tests are used, traditional microbiology also should be accessible to provide reference-level testing to detect emerging infectious diseases
(i.e., microbes that will not be recognized by disease-specific tests) and to validate field tests on an ongoing basis.
Enacted in 1996, HIPAA required the Department of Health and Human Services to establish
national standards for electronic health-care transactions and national identifiers for providers, health
plans, and employers. It also addressed the security and privacy of health data (HHS, 2005).
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global infectious disease surveillance and detection
Conclusion
As investments are made in surveillance systems, it is also critical to commit
adequate resources to analyzing and responding to the increased volume of surveillance data. For example, PulseNet—a much-heralded early warning system
for foodborne diseases—does not live up to its full potential due to inadequate
resources for laboratory studies and epidemiology. Moreover, the collection and
analysis of surveillance data is only one part of the challenge of responding to
emerging infectious diseases. Epidemiologic and laboratory resources are needed
to investigate early warning signals and to take effective actions to break the
cycle of disease transmission.
REFERENCES
APHL (Association of Public Health Laboratories). 2002. Advancing the national electronic surveillance system: An essential role for public health laboratories, http://www.aphl.org/Documents/
Global_docs/advancing_NEDSS.pdf (accessed May 24, 2007).
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definition/coordination.html (accessed May 5, 2007).
CDC (Centers for Disease Control and Prevention). 2004. National Laboratory System (NLS), http://
www.phppo.cdc.gov/mlp/nls.aspx (accessed May 10, 2007).
CDC. 2006. PulseNet, http://www.cdc.gov/pulsenet/ (accessed May 10, 2007).
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CLSI (Clinical and Laboratory Standards Institute). 2004. GP26—Application of a quality management system model for laboratory services; Approved guidelines—Third edition. Wayne, PA:
Clinical and Laboratory Standards Institute.
Covey, S. 1989. The seven habits of highly effective people. New York: Simon and Schuster.
Cowan, L. S., L. Mosher, L. Diem, J. P. Massey, and J. T. Crawford. 2002. Variable-number tandem
repeat typing of Mycobacterium tuberculosis with low copy number of IS6110 by using mycobacterial interspersed repetitive units. Journal of Clinical Microbiology 40(2):1592-1602.
GAO (General Accounting Office). 2005. Information technology: Federal agencies challenges in
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Hueston, W. 2006. Coordination of disease surveillance, detection, diagnostics, and reporting. Presentation to the Institute of Medicine Forum on Microbial Threats, Washington, DC, December
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federal agencies (CDC, U.S. Department of Agriculture/Food Safety and Inspection Service, Food and
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to distinguish strains at the DNA level. DNA “fingerprints,” or patterns, are submitted electronically
to a dynamic database at CDC, allowing for rapid comparison of the patterns (CDC, 2006).
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IOM (Institute of Medicine). 2006. Ending the war metaphor: The changing agenda for unraveling
the host–microbe relationship—Workshop Summary. Washington, DC: The National Academies
Press.
Metchock, B. G., F. S. Nolte, and R. J. Wallace, Jr. 1999. Mycobacterium. In Manual of clinical
microbiology, 7th ed., edited by P. R. Murray, E. J. Baron, M. A. Pfaller, F. C. Tenover, and R.
H. Yolken. Washington, DC: American Society for Microbiology.
NCCLS (National Committee on Clinical Laboratory Standards). 2003. Susceptibility testing of Mycobacteria, Norcardiae, and other aerobic actinomycetes. Approved Standard M24-A. Wayne,
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Plikaytis, B. B., B. D. Plikaytis, M. A. Yarkus, W. R. Butler, C. L. Woodly, V. A. Silcox, and T. M.
Shinnick. 1992. Differentiation of slowly growing Mycobacterium species, including Mycobacterium tuberculosis complex, by gene amplification and restriction fragment length polymorphism analysis. Journal of Clinical Microbiology 30(7):1815-1822.
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(accessed May 5, 2007).
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Appendix A
Agenda
Global Infectious Disease Surveillance and Detection:
Assessing the Challenges—Finding Solutions
The National Academies
500 Fifth Street, NW – Room 100
Washington, DC
December 12–13, 2006
Tuesday, December 12, 2006
8:00 a.m.
Continental Breakfast
8:30 a.m.
Welcome and Opening Remarks
P. Fred Sparling, M.D., Vice Chair
Forum on Microbial Threats
8:45–9:15 a.m.
Keynote Address: “Syndromic Surveillance: Moving
from Theory to Practice”
Patrick W. Kelley, M.D., Dr.P.H.
The National Academies
9:15–9:45 a.m.
Discussion
233
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global infectious disease surveillance and detection
Session I:
Surveillance for Emerging, Reemerging, and Novel Infectious Diseases
Moderator: Col. Ralph Erickson, M.D., Department of Defense Global Emerging
Infectious Surveillance and Response System
9:45–10:15 a.m.
Public Health Infectious Disease Surveillance
Michael Stoto, Ph.D.
Georgetown University
10:15–10:45 a.m.
Infectious Disease Surveillance: The “Local”
Perspective
Marci Layton, M.D.
New York City Department of Health and Mental
Hygiene
10:45–11:00 a.m.
Break
11:00–11:30 a.m.
Animal Disease Surveillance
William Karesh, D.V.M.
Wildlife Conservation Society
11:30 a.m.–12:00 p.m. Plant Disease Surveillance and Detection
Jacque Fletcher, Ph.D.
Oklahoma State University
Jim Stack, Ph.D.
Kansas State University
12:00–12:30 p.m.
Open Discussion of Session I
12:30–1:15 p.m.
Lunch
Session II:
Infectious Disease Detection and Diagnostics
Moderator: David Relman, M.D., Stanford University
1:15–1:45 p.m.
Mark D. Perkins, M.D.
Foundation for Innovative New Diagnostics (FIND)
1:45–2:15 p.m.
Stephen Johnston, Ph.D.
Arizona State University
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APPENDIX A
2:15–2:45 p.m.
Animal Disease Detection: Diagnostic Laboratory
Perspective
Alex Ardans, D.V.M.
California Animal Health & Food Safety Laboratory
System
2:45–3:00 p.m.
Break
3:00–3:30 p.m.
Rapid Infectious Disease Diagnostic Assays
Mark Wolcott, Ph.D.
U.S. Army Medical Research Institute of Infectious
Diseases
3:30–4:00 p.m.
Discussion of the GreeneChip: A Panmicrobial
Oligonucleotide Array for the Diagnosis of
Infectious Diseases
W. Ian Lipkin, M.D.
Columbia University
4:00–5:00 p.m.
Open Discussion of Session II
5:00–5:45 p.m.
Open Discussion of Day 1
6:00–7:00 p.m.
Open Reception
Wednesday, December 13, 2006
8:00 a.m.
Continental Breakfast
8:30 a.m.
Opening Remarks/Summary of Day 1
Peggy Hamburg, Vice Chair
Forum on Microbial Threats
Session III:
Current and Future Methods for Infectious Disease
Surveillance, Reporting, and Communication
Moderator: Stephen S. Morse, Ph.D., Columbia University
8:40–9:10 a.m.
Discussion of ProMED-mail
Stephen S. Morse, Ph.D.
Columbia University
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global infectious disease surveillance and detection
9:10–9:40 a.m.
Discussion of the Global Public Health Intelligence
Network
Abla Mawudeku, M.P.H.
Global Public Health Intelligence Network
9:40–10:10 a.m.
Implications of “Real Time” and “Batch Reporting” for
Surveillance
Joseph Lombardo, Ph.D.
The Johns Hopkins University Applied Physics
Laboratory
10:10–10:30 a.m.
Break
10:30–11:00 a.m.
Using Cell Phone Technology for Infectious Disease
Surveillance
�������������
Pamela Johnson, Ph.D.
Voxiva
David Blazes, M.D., M.P.H.
Naval Medical Research Unit, Peru
11:00–11:30 a.m.
HealthMap: A Global Disease Alert Mapping System
John Brownstein, Ph.D.
Harvard Medical School
11:30 a.m.–12:15 p.m. Open Discussion of Session III
12:15–1:00 p.m.
Lunch
Session IV:
Infectious Disease Detection, Surveillance, and Reporting—
Resource Needs and Opportunities
Moderator: Fred Sparling, M.D., University of North Carolina
1:00–1:30 p.m.
Coordination of Disease Surveillance, Detection,
Diagnostics, and Reporting
Will Hueston, D.V.M., Ph.D.
University of Minnesota
1:30–3:30 p.m.
Discussion Panel
• Marci Layton, M.D.
New York City Department of Health and Mental
Hygiene
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APPENDIX A
• Fernando Guerra, M.D., M.P.H.
San Antonio Department of Health
• Frances P. Downes, Dr.P.H.
Michigan Public Health Laboratory
• W. Ian Lipkin, M.D.
Columbia University
• James LeDuc, Ph.D.
University of Texas Medical Branch
3:30–4:15 p.m.
Open Discussion of Session IV
4:15–4:30 p.m.
Closing Remarks/Adjourn
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Appendix B
Acronyms
ALS
APHIS
ARIMA
ARS
amyotrophic lateral sclerosis
Animal and Plant Health Inspection Service
autoregressive moving average
Agricultural Research Service
BDV
BLAST
BSN
Borna disease virus
Basic Local Alignment Search Tool
Basic Surveillance Network
CBP
CDC
cDNA
CGIAR
cPCR
CRP
CSREES
Customs and Border Protection
Centers for Disease Control and Prevention
complementary DNA
Consultative Group on International Agriculture Research
consensus polymerase chain reaction
Critical Reagents Program
Cooperative State Research, Education, and Extension
Service
DD
DHS
DoD
DOHMH
DoI
DoS
DOTS
differential display
Department of Homeland Security
Department of Defense
Department of Health and Mental Hygiene (New York City)
Department of the Interior
Department of State
directly observed therapy shortcourse
238
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DSDD
DSN
domain-specific differential display
disease surveillance network
ECDC
ECL
ED
EDR
EFSA
EISS
EMEA
END
ER
ESSENCE
EU
EWGLI
EWRS
European Center for Disease Control
electrochemiluminescence
emergency department
Emerging Disease Reports
European Food and Safety Authority
European Influenza Surveillance Scheme
European Agency for the Evaluation of Medicinal Products
exotic Newcastle disease
emergency room
Electronic Surveillance System for the Early Notification of
Community-Based Epidemics
European Union
European Working Group for Legionella Infections
Early Warning Response System
FAO
FAS
FDA
FIND
FMD
FTP
Food and Agriculture Organization of the United Nations
Federation of American Scientists
Food and Drug Administration
Foundation for Innovative New Diagnostics
foot-and-mouth disease
File Transfer Protocol
GAINS
GAO
GEIS
GIS
GLEWS
GOARN
GPHIN
GreenVrdB
Global Avian Influenza Network for Surveillance
Government Accountability Office
Global Emerging Infections Surveillance and Response
System
Geographic Information System
Global Early Warning and Response System
Global Outbreak Alert and Response Network
Global Public Health Intelligence Network
Greene Viral Database
HCV
HHA
HHS
HIPAA
HIV
HL-7
HMM
HSPD
hepatitis C virus
hand-held assay
Department of Health and Human Services
Health Insurance Portability and Accountability Act
human immunodeficiency virus
Health Level Seven
Hidden Markov Models
Homeland Security Presidential Directive
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global infectious disease surveillance and detection
ICD
ICTV
ICTVdB
ICU
IEEE
IHR
ILI
INSTEDD
IOM
IPM
ISID
IT
ITU
International Classification of Diseases
International Committee on Taxonomy of Viruses
International Committee on Taxonomy of Viruses Database
intensive care unit
Institute of Electrical and Electronics Engineers
International Health Regulation
influenza-like illness
International System for Total Early Disease Detection
Institute of Medicine
Integrated Pest Management
International Society for Infectious Diseases
information technology
International Telecommunications Union
JBAIDS
Joint Biological Agent Identification and Diagnostic System
LEADERS
LOD
Lightweight Epidemiological Advanced Detection Emergency
Response System
limit of detection
MedISys
MHC
MoH
mRNA
MS
Medical Intelligence System
major histocompatibility complex
Ministry of Health
messenger RNA
messaging system
NATO
NCBI
NGO
NIAID
NIH
NINDS
NLS
NMRCD
NPDN
NPDRS
NRC
NRDM
North Atlantic Treaty Organization
National Center for Biotechnology Information
nongovernmental organization
National Institute of Allergy and Infectious Diseases
National Institutes of Health
National Institute of Neurological Disorders and Stroke
National Laboratory System
Naval Medical Research Center Detachment
National Plant Diagnostic Network
National Plant Disease Recovery System
National Research Council
National Retail Data Monitor
OIE
OIG
World Organization for Animal Health
Office of the Inspector General
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APPENDIX B
PCR
PDA
Pfam
PHIN
PMM
ProMED
polymerase chain reaction
personal digital assistant
Protein families database of alignments
Public Health Information Network
ProMED-mail
Program for Monitoring Emerging Diseases
RDA
RDP
RDT
RFI
RODS
RSS
RSVP
RT-PCR
representational difference analysis
Ribosomal Database Project
rapid diagnostic test
request for information
Real-Time Outbreak and Disease Surveillance System
Really Simple Syndication
Rapid Syndrome Validation Project
reverse transcriptase–PCR
SARS
SD
SLEV
SMS
SNOMED
SNOVET
SNVDO
SPC
SWOT
SYRIS
severe acute respiratory syndrome
standard deviation
St. Louis encephalitis virus
short message service
Standardized Nomenclature for Medicine
Standardized Nomenclature for Veterinary Medicine
Standardized Nomenclature for Veterinary Diagnoses and
Operations
statistical process control
Strengths, Weaknesses, Opportunities, and Threats
Syndromic Reporting Information System
TaxID
TB
TED
TPA
TRF
Taxonomy identification
tuberculosis
Technology, Entertainment, and Design
tripropylamine
time-resolved fluorescence
USAID
USAMRIID
USDA
USGS
USPS
U.S. Agency for International Development
U.S. Army Medical Research Institute of Infectious Diseases
U.S. Department of Agriculture
U.S. Geological Survey
U.S. Postal Service
VPN
virtual private network
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global infectious disease surveillance and detection
WCS
Wildlife Conservation Society
WHO
World Health Organization
WHO-OVL
Outbreak Verification List
Wildlife GAINS Wildlife Global Animal Information Network for Surveillance
WNV
West Nile virus
Copyright © National Academy of Sciences. All rights reserved.
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Appendix C
Forum Member Biographies
Stanley M. Lemon, M.D. (Chair), is the John Sealy Distinguished University
Chair and director of the Institute for Human Infections and Immunity at the
University of Texas Medical Branch (UTMB) at Galveston. He received his
undergraduate A.B. degree in biochemical sciences from Princeton University
summa cum laude and his M.D. with honors from the University of Rochester.
He completed postgraduate training in internal medicine and infectious diseases
at the University of North Carolina at Chapel Hill and is board certified in both.
From 1977 to 1983 he served with the U.S. Army Medical Research and Development Command, followed by a 14-year period on the faculty of the University
of North Carolina School of Medicine. He moved to UTMB in 1997, serving
first as chair of the Department of Microbiology and Immunology, then as dean
of the School of Medicine from 1999 to 2004. Dr. Lemon’s research interests
relate to the molecular virology and pathogenesis of the positive-stranded RNA
viruses responsible for hepatitis. He has had a long-standing interest in antiviral
and vaccine development and has served previously as chair of the Anti-Infective
Drugs Advisory Committee of the U.S. Food and Drug Administration (FDA).
He is the past chair of the Steering Committee on Hepatitis and Poliomyelitis of
the World Health Organization (WHO) Programme on Vaccine Development. He
currently serves as a member of the U.S. Delegation of the U.S.–Japan Cooperative Medical Sciences Program, and he chairs the Board of Scientific Councilors
of the National Center for Infectious Diseases (NCID) of the Centers for Disease
Control and Prevention (CDC). He was co-chair of the Committee on Advances
in Technology and the Prevention of Their Application to Next Generation Biowarfare Threats for the National Academy of Sciences (NAS), and he recently
chaired an Institute of Medicine (IOM) study committee related to vaccines
243
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global infectious disease surveillance and detection
for the protection of the military against naturally occurring infectious disease
threats.
Margaret A. Hamburg, M.D. (Vice-chair), is vice president for Biological Programs at the Nuclear Threat Initiative, a charitable organization working to reduce
the global threat from nuclear, biological, and chemical weapons. She is in charge
of the biological program area. She completed her internship and residency in
internal medicine at the New York Hospital/Cornell University Medical Center
and is certified by the American Board of Internal Medicine. Dr. Hamburg is a
graduate of Harvard College and Harvard Medical School. Before taking on her
current position, she was the assistant secretary for planning and evaluation, U.S.
Department of Health and Human Services (HHS), serving as a principal policy
advisor to the secretary of health and human services with responsibilities including policy formulation and analysis, the development and review of regulations
and legislation, budget analysis, strategic planning, and the conduct and coordination of policy research and program evaluation. Prior to this, she served for
nearly six years as the commissioner of health for the city of New York. As chief
health officer in the nation’s largest city, her many accomplishments included the
design and implementation of an internationally recognized tuberculosis control
program that produced dramatic declines in tuberculosis cases, the development
of initiatives that raised childhood immunization rates to record levels, and the
creation of the first public health bioterrorism preparedness program in the nation.
She currently serves on the Harvard University Board of Overseers. She has been
elected to membership in the IOM, the New York Academy of Medicine, and the
Council on Foreign Relations and is a fellow of the American Association for the
Advancement of Science (AAAS) and the American College of Physicians.
P. Frederick Sparling, M.D. (Vice-chair), is the J. Herbert Bate Professor Emeritus of Medicine, Microbiology, and Immunology at the University of North
Carolina (UNC) at Chapel Hill and is director of the North Carolina Sexually
Transmitted Infections Research Center. Previously he served as chair of the
Department of Medicine and chair of the Department of Microbiology and Immunology at UNC. He was president of the Infectious Diseases Society of America
(IDSA) from 1996 to 1997. He was also a member of the IOM’s Committee on
Microbial Threats to Health (1991–1992). Dr. Sparling’s laboratory research is in
the molecular biology of bacterial outer membrane proteins involved in pathogenesis, with a major emphasis on gonococci and meningococci. His current studies
focus on the biochemistry and genetics of iron-scavenging mechanisms used by
gonococci and meningococci and the structure and function of the gonococcal
porin proteins. He is pursuing the goal of a vaccine for gonorrhea.
David W. K. Acheson, M.D., is chief medical officer at the FDA’s Center for
Food Safety and Applied Nutrition. He received his medical degree at the Uni-
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APPENDIX C
versity of London. After completing internships in general surgery and medicine,
he continued his postdoctoral training in Manchester, England, as a Wellcome
Trust research fellow. He subsequently was a Wellcome Trust training fellow
in Infectious Diseases at the New England Medical Center and at the Wellcome
Research Unit in Vellore, India. He was associate professor of medicine, Division
of Geographic Medicine and Infectious Diseases, New England Medical Center,
until 2001. He then joined the faculties of the Department of Epidemiology
and Preventive Medicine and Department of Microbiology and Immunology at
the University of Maryland Medical School. Currently at FDA, Dr. Acheson’s
research concentration is on foodborne pathogens and encompasses a mixture of
molecular pathogenesis, cell biology, and epidemiology. Specifically, his research
focuses on Shiga toxin-producing E. coli and understanding toxin interaction
with intestinal epithelial cells using tissue culture models. His laboratory has also
undertaken a study to examine Shiga toxin-producing E. coli in food animals in
relation to virulence factors and antimicrobial resistance patterns. More recently,
Dr. Acheson initiated a project to understand the molecular pathogenesis of
Campylobacter jejuni. Other studies have undertaken surveillance of diarrheal
disease in the community to determine causes, outcomes, and risk factors of
unexplained diarrhea. Dr. Acheson has authored or coauthored more than 72 journal articles and 42 book chapters and reviews, and he is coauthor of the book Safe
Eating (Dell Health, 1998). He serves as a reviewer for more than 10 journals
and is on the editorial boards of Infection and Immunity and Clinical Infectious
Diseases. He is a fellow of the Royal College of Physicians and a fellow of the
Infectious Diseases Society of America, and he holds several patents.
Ruth L. Berkelman, M.D., is the Rollins Professor and director of the Center for
Public Health Preparedness and Research at the Rollins School of Public Health,
Emory University in Atlanta. She received her A.B. from Princeton University
and her M.D. from Harvard Medical School. Board certified in pediatrics and
internal medicine, she began her career at CDC in 1980 and later became deputy
director of NCID. She also served as a senior advisor to the director, CDC, and
as assistant surgeon general in the U.S. Public Health Service. In 2001 she came
to her current position at Emory University, directing a center focused on emerging infectious disease and other urgent threats to health, including terrorism. She
has also consulted with the biologic program of the Nuclear Threat Initiative and
is most recognized for her work in infectious diseases and disease surveillance.
She was elected to the IOM in 2004. Currently a member of the Board on Life
Sciences of The National Academies, she also chairs the Board of Public and
Scientific Affairs at the American Society of Microbiology (ASM).
Enriqueta C. Bond, Ph.D., is president of the Burroughs Wellcome Fund. She
received her undergraduate degree from Wellesley College, her M.A. from the
University of Virginia, and her Ph.D. in molecular biology and biochemical
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global infectious disease surveillance and detection
genetics from Georgetown University. She is a member of the IOM, the AAAS,
the ASM, and the American Public Health Association. Dr. Bond serves on the
council of the IOM as its vice chair; she chairs the Board of Scientific Counselors
for NCID at CDC, and she chairs the IOM’s Clinical Research Roundtable. She
serves on the board and the executive committee of the Research Triangle Park
Foundation and on the board of the Medicines for Malaria Venture. Prior to being
named president of the Burroughs Wellcome Fund in 1994, she had served on the
staff of the IOM since 1979, becoming the IOM’s executive officer in 1989.
Roger G. Breeze, Ph.D., received his veterinary degree in 1968 and his Ph.D.
in veterinary pathology in 1973, both from the University of Glasgow, Scotland.
He was engaged in teaching, diagnostic pathology, and research on respiratory
and cardiovascular diseases at the University of Glasgow Veterinary School from
1968 to 1977 and at Washington State University College of Veterinary Medicine from 1977 to 1987, where he was professor and chair of the Department of
Microbiology and Pathology. From 1984 to 1987 he was deputy director of the
Washington Technology Center, the state’s high-technology sciences initiative,
based in the College of Engineering at the University of Washington. In 1987,
he was appointed director of the U.S. Department of Agriculture’s (USDA’s)
Plum Island Animal Disease Center, a biosafety level 3 facility for research and
diagnosis of the world’s most dangerous livestock diseases. In that role he initiated research into the genomic and functional genomic basis of disease pathogenesis, diagnosis, and control of livestock RNA and DNA virus infections. This
work became the basis of U.S. defense against natural and deliberate infection
with these agents and led to his involvement in the early 1990s in biological
weapons defense and proliferation prevention. From 1995 to 1998, he directed
research programs in 20 laboratories in the Southeast for the USDA Agricultural Research Service before going to Washington, DC, to establish biological
weapons defense research programs for USDA. He received the Distinguished
Executive Award from President Clinton in 1998 for his work at Plum Island and
in biodefense. Since 2004 he has been chief executive officer of Centaur Science
Group, which provides consulting services in biodefense. His main commitment
is to the Defense Threat Reduction Agency’s Biological Weapons Proliferation
Prevention program in Europe, the Caucasus, and Central Asia.
Steven J. Brickner, Ph.D., is research advisor, antibacterials chemistry, at Pfizer
Global Research and Development. He received his Ph.D. in organic chemistry
from Cornell University and was a National Institutes of Health (NIH) postdoctoral research fellow at the University of Wisconsin–Madison. He is a medicinal
chemist with nearly 20 years of research experience in the pharmaceutical industry, all focused on the discovery and development of novel antibacterial agents.
He is an inventor or coinventor on 21 U.S. patents and has published numerous
scientific papers, primarily within the area of the oxazolidinones. Prior to join-
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APPENDIX C
ing Pfizer in 1996, he led a team at Pharmacia and Upjohn that discovered and
developed linezolid, the first member of a new class of antibiotics to be approved
in the past 35 years.
Nancy Carter-Foster, M.S.T.M., is senior advisor for health affairs for the U.S.
Department of State, assistant secretary for science and health, and the secretary’s
representative on HIV/AIDS. She is responsible for identifying emerging health
issues and making policy recommendations for U.S. foreign policy concerns regarding international health, and she coordinates the department’s interactions with the
nongovernmental community. She is a member of the IDSA and the AAAS. She has
helped bring focus to global health issues in U.S. foreign policy and has brought a
national security focus to global health. In prior positions as director for congressional and legislative affairs for the Economic and Business Affairs Bureau of the
U.S. Department of State, foreign policy advisory to the majority whip of the U.S.
House of Representatives, trade specialist advisor to the House of Representatives
Ways and Means Trade Subcommittee, and consultant to the World Bank, Asia
Technical Environment Division, Ms. Carter-Foster has worked on a wide variety
of health, trade, and environmental issues amassing in-depth knowledge and experience in policy development and program implementation.
Gail H. Cassell, Ph.D., is vice president of Scientific Affairs, Distinguished Lilly
Research Scholar for Infectious Diseases, Eli Lilly & Company. Previously she
was the Charles H. McCauley Professor and, beginning in 1987, the chair of the
Department of Microbiology, University of Alabama Schools of Medicine and
Dentistry at Birmingham, a department which, under her leadership, ranked first
in research funding from NIH since 1989. She is a member of the Director’s
Advisory Committee of CDC. Dr. Cassell is past president of the ASM and is
serving her third 3-year term as chair of the Public and Scientific Affairs Board of
the ASM. She is a former member of the NIH Director’s Advisory Committee and
a former member of the Advisory Council of the National Institute of Allergy and
Infectious Diseases. She has also served as an advisor on infectious diseases and
indirect costs of research to the White House Office on Science and Technology
and was previously chair of the Board of Scientific Counselors of NCID at CDC.
She served 8 years on the Bacteriology-Mycology-II Study Section and served
as its chair for 3 years. She serves on the editorial boards of several prestigious
scientific journals and has authored more than 275 articles and book chapters. She
has been intimately involved in the establishment of science policy and legislation related to biomedical research and public health. Dr. Cassell has received
several national and international awards and an honorary degree for her research
on infectious diseases.
Bill Colston, Ph.D., is currently the division leader for the Chemical and Biological Countermeasures Division at Lawrence Livermore National Laboratory
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global infectious disease surveillance and detection
(LLNL). This newly formed division consists of four programs whose missions
include threat awareness, detection, response, and attribution. These programs
are made up of approximately 190 researchers from a variety of disciplines. The
mission of these programs is to provide science, technology, and deployed capabilities to defend the nation, its people, and warfighters against the threat of biological and chemical terrorism. The larger vision is to meet the challenges of an
ever-changing threat by transforming our understanding of pathogenicity and host
response and expanding our reach globally. Dr. Colston holds a Ph.D. in biomedical engineering and has published numerous publications and patents, largely in
biological measurement sciences. Directly prior to this assignment, he founded
the Department of Homeland Security’s Biodefense Knowledge Center.
Col. Ralph (Loren) Erickson, M.D., Dr.P.H., M.P.H., is the director of the
Department of Defense Global Emerging Infections Surveillance and Response
System (DoD-GEIS) headquartered in Silver Spring, Maryland. He holds a B.S.
degree in chemistry from the University of Washington, an M.D. from the Uniformed Services University of the Health Sciences, an M.P.H. from Harvard, and
a Dr.P.H. from Johns Hopkins. Residency trained and board certified in preventive medicine, Dr. Erickson has held a number of leadership positions within
the Army Medical Department, including: director of the General Preventive
Medicine Residency Program, Walter Reed Army Institute of Research; director
of Epidemiology and Disease Surveillance, U.S. Army Center for Health Promotion and Preventive Medicine; commander of the U.S. Army Center for Health
Promotion and Preventive Medicine (Europe); and specialty leader for all U.S.
Army preventive medicine physicians.
Mark B. Feinberg, M.D., Ph.D., is vice president for Policy, Public Health, and
Medical Affairs in the Merck Vaccine Division of Merck & Co., Inc. He received
his bachelor’s degree magna cum laude from the University of Pennsylvania in
1978 and his M.D. and Ph.D. from Stanford University School of Medicine in
1987. From 1985 to 1986, Dr. Feinberg served as a project officer for the Committee on a National Strategy for AIDS of the IOM and the NAS. Following receipt
of his M.D. and Ph.D., he pursued postgraduate residency training in internal
medicine at the Brigham and Women’s Hospital of Harvard Medical School and
postdoctoral fellowship research in the laboratory of Dr. David Baltimore at the
Whitehead Institute for Biomedical Research. From 1991 to 1995, Dr. Feinberg
was an assistant professor of medicine, microbiology, and immunology at the University of California, San Francisco (UCSF), where he also served as an attending
physician in the AIDS/Oncology Division and as director of the Virology Research
Laboratory at San Francisco General Hospital. From 1995 to 1997, he was a medical officer in the Office of AIDS Research in the office of the director of NIH, and
chair of the NIH Coordinating Committee on AIDS Etiology and Pathogenesis
Research. During this period, he also served as executive secretary of the NIH
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APPENDIX C
Panel to Define Principles of Therapy of HIV Infection. Prior to joining Merck in
2004, Dr. Feinberg served as professor of medicine and microbiology and immunology at the Emory University School of Medicine and as an investigator at the
Emory Vaccine Center. He also founded and served as the medical director of the
Hope Clinic—a clinical research facility devoted to the clinical evaluation of novel
vaccines and to translational research studies of human immune system biology.
At UCSF and Emory, Dr. Feinberg and colleagues were engaged in the preclinical development and evaluation of novel vaccines for HIV and other infectious
diseases and in basic research studies focused on revealing fundamental aspects
of host–virus relationships that underlie the pathogenesis of HIV and simian
immunodeficiency virus infections. In addition to his other professional roles, he
has also served as a consultant to, and member of, several committees of the IOM
and the NAS.
J. Patrick Fitch, Ph.D., is laboratory director for the National Biodefense Analysis and Countermeasures Center (NBACC) and the president of Battelle National
Biodefense Institute, LLC (BNBI). BNBI manages and operates the NBACC
national laboratory for the Department of Homeland Security as a Federally
Funded Research and Development Center established in 2006. The NBACC
mission is to provide the nation with the scientific basis for awareness of biological threats and attribution of their use against the American public. Dr. Fitch
joined Battelle in 2006 as vice president for Biodefense Programs after more
than 20 years of experience leading multidisciplinary applied science teams at the
University of California’s Lawrence Livermore National Laboratory. From 2001
to 2006, he led the LLNL Chemical and Biological National Security Program
(CBNP), with applied science programs from pathogen biology and material
science to deployed systems. CBNP accomplishments include performing more
than 1 million assays on national security samples; setting up and operating 24/7
reach-back capabilities; setting up a nationwide bioalert system; receiving three
R&D 100 awards; designing signatures for validated assays in the CDC Laboratory Response Network and the National Animal Health Laboratory Network;
and designing, demonstrating, and deploying the BASIS biodetection system,
leading to the nationwide BioWatch system. He has authored several books and
book chapters, including An Engineering Introduction to Biotechnology. He has
chaired and served on several panels of The National Academies. His advisory
board activities have included U.S. Animal Health Association, Texas A&M
University DHS Center of Excellence, Central Florida University (College of
Engineering), Colorado State University (College of Engineering), California
State Breast Cancer Research Program, and Biomolecular Engineering. Dr. Fitch
was a fellow of the American Society for Laser Medicine and Surgery and an
associate editor of Circuits, Systems and Signal Processing. He has received two
national awards for medical devices, a technical writing award for an article in
Science, and an international best paper award from the Institute of Electrical
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global infectious disease surveillance and detection
and Electronics Engineers (IEEE). He also coinvented the technology, developed
the initial business plan, and successfully raised venture investments for a hightech medical device start-up company. Dr. Fitch received his Ph.D. from Purdue
University and B.S. from Loyola College of Maryland.
Capt. Darrell R. Galloway, M.S.C., Ph.D., is chief of the Medical Science
and Technology Division for the Chemical and Biological Defense Directorate
at the Defense Threat Reduction Agency. He received his baccalaureate degree
in microbiology from California State University in Los Angeles in 1973. After
completing military service in the U.S. Army as a medical corpsman from 1969
to 1972, Captain Galloway entered graduate school and completed a doctoral
degree in biochemistry in 1978 from the University of California, followed by
2 years of postgraduate training in immunochemistry as a fellow of the National
Cancer Institute at the Scripps Clinic and Research Foundation in La Jolla, California. Captain Galloway began his navy career at the Naval Medical Research
Institute in Bethesda, Maryland, where from 1980 to 1984 he served as a research
scientist working on vaccine development. In late 1984 Captain Galloway left
active service to pursue an academic appointment at Ohio State University, where
he is now a tenured faculty member in the Department of Microbiology. He also
holds appointments at the University of Maryland Biotechnology Institute and
the Uniformed Services University of Health Sciences. He has an international
reputation in the area of bacterial toxin research and has published more than 50
research papers on various studies of bacterial toxins. In recent years Captain
Galloway’s research has concentrated on anthrax and the development of DNAbased vaccine technology. His laboratory has contributed substantially to the
development of a new DNA-based vaccine against anthrax that has completed the
first phase of clinical trials. Captain Galloway is a member of the ASM and has
served as president of the Ohio branch of that organization. He received an NIH
Research Career Development Award. In 2005 Captain Galloway was awarded
the Joel M. Dalrymple Award for significant contributions to biodefense vaccine
development.
S. Elizabeth George, Ph.D., is deputy director, Biological Countermeasures
Portfolio Science and Technology Directorate, Department of Homeland Security
(DHS). Until merging into the new department in 2003, she was program manager
of the Chemical and Biological National Security Program in the Department of
Energy’s National Nuclear Security Administration’s Office of Nonproliferation
Research and Engineering. Significant accomplishments include the design and
deployment of BioWatch, the nation’s first civilian biological threat agent monitoring system, and PROTECT, the first civilian operational chemical detection
and response capability deployed in the Washington, DC, area subway system.
Previously, she spent 16 years at the U.S. Environmental Protection Agency
(EPA), Office of Research and Development, National Health and Ecological
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APPENDIX C
Effects Research Laboratory, Environmental Carcinogenesis Division, where she
was branch chief of the Molecular and Cellular Toxicology Branch. She received
her B.S. in biology in 1977 from Virginia Polytechnic Institute and State University and her M.S. and Ph.D. in microbiology in 1979 and 1984, respectively, from
North Carolina State University. From 1984 to 1986, she was a National Research
Council fellow in the laboratory of Dr. Larry Claxton at EPA. Dr. George is the
2005 chair of the Chemical and Biological Terrorism Defense Gordon Research
Conference. She has served as councilor for the Environmental Mutagen Society
and president and secretary of the Genotoxicity and Environmental Mutagen
Society. She holds memberships in the ASM and the AAAS and is an adjunct
faculty member in the School of Rural Public Health, Texas A&M University. She
is a recipient of the EPA Bronze Medal and Scientific and Technological Achievement Awards and DHS Under Secretary’s Award for Science and Technology.
She is the author of numerous journal articles and has presented her research at
national and international meetings.
Jesse L. Goodman, M.D., M.P.H., is director of FDA’s Center for Biologics
Evaluation and Research (CBER), which oversees medical, public health, and
policy activities concerning the development and assessment of vaccines, blood
products, tissues, and related devices and novel therapeutics, including cellular
and gene therapies. He moved full-time to FDA in 2001 from the University of
Minnesota, where he was professor of and director of the Division of Infectious
Diseases. A graduate of Harvard College, he received his M.D. at the Albert Einstein College of Medicine, did residency and fellowship training at the Hospital
of the University of Pennsylvania and at the University of California–Los Angeles (UCLA; where he was also chief medical resident), and is board certified in
internal medicine, oncology, and infectious diseases. He trained in the virology
laboratory of Jack Stevens at UCLA and has had an active laboratory program in
the molecular pathogenesis of infectious diseases. In 1995 his laboratory isolated
the etiologic agent of human granulocytic ehrlichiosis (HGE) and subsequently
characterized fundamental events involved in infection of leukocytes, including
their cellular receptors. He is editor of the book Tick Borne Diseases of Humans
published by ASM Press in 2005 and is a staff physician and infectious diseases
consultant at the NIH Clinical Center and the National Naval Medical Center/
Walter Reed Army Medical Center, as well as adjunct professor of medicine at
the University of Minnesota. He is active in a wide variety of clinical, public
health, and product development issues, including pandemic and emerging infectious disease threats, bioterrorism preparedness and response, and blood, tissue,
and vaccine safety and availability. In these activities, he has worked closely
with CDC, NIH, and other HHS components, academia, and the private sector,
and he has put into place an interactive team approach to emerging threats. This
model was used in the collaborative development and rapid implementation of
nationwide donor screening of the U.S. blood supply for West Nile virus. He has
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been elected to the American Society for Clinical Investigation (ASCI) and to
the IOM.
Eduardo Gotuzzo, M.D., is principal professor and director at the Instituto de
Medicina Tropical “Alexander von Humbolt,” Universidad Peruana Cayetan
Heredia (UPCH) in Lima, Peru, as well as chief of the Department of Infectious
and Tropical Diseases at the Cayetano Heredia Hospital. He is also an adjunct
professor of medicine at the University of Alabama, Birmingham School of
Medicine. Dr. Gotuzzo is an active member in numerous international societies
and has been president of the Latin America Society of Tropical Disease (2000–
2003), the IDSA Scientific Program (2000–2003), the International Organizing
Committee of the International Congress of Infectious Diseases (1994–present),
president-elect of the International Society for Infectious Diseases (1996–1998),
and president of the Peruvian Society of Internal Medicine (1991–1992). He has
published more than 230 articles and chapters as well as six manuals and one
book. Recent honors and awards include being named an honorary member of the
American Society of Tropical Medicine and Hygiene in 2002, associate member
of the National Academy of Medicine in 2002, honorary member of the Society
of Internal Medicine in 2000, and distinguished visitor at the Faculty of Medical
Sciences, University of Cordoba, Argentina, in 1999. In 1988 he received the
Golden Medal for Outstanding Contribution in the Field of Infectious Diseases
awarded by Trnava University, Slovakia.
Jo Handelsman, Ph.D., received her Ph.D. in molecular biology from the University of Wisconsin–Madison (UW–M) in 1984 and joined the faculty of the
UW–M Department of Plant Pathology in 1985, where she is currently a Howard
Hughes Medical Institute (HHMI) professor. Her research focuses on the genetic
and functional diversity of microorganisms in soil and insect gut communities.
The Handelsman lab has concentrated on discovery and biological activity of
novel antibiotics from cultured and uncultured bacteria and has contributed to the
pioneering of a new technique called metagenomics that facilitates the genomic
analysis of assemblages of uncultured microorganisms. Handelsman is studying
the mid-gut of the gypsy moth to understand the basis for resistance and susceptibility of microbial communities to invasion, developing it as a model for
the microbial community in the human gut. In addition to her passion for understanding the secret lives of bacteria, Dr. Handelsman is dedicated to improving
science education and the advancement of women in research universities. She
is director of the HHMI New Generation Program for Scientific Teaching, which
is dedicated to teaching graduate and postdoctoral students the principles and
practices of teaching and mentoring. She is codirector of The National Academies
Summer Institute for Undergraduate Education in Biology, a collaborative venture between HHMI and The National Academies that aims to train a nationwide
network of faculty who are outstanding teachers and mentors. Dr. Handelsman
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is codirector of the Women in Science and Engineering Leadership Institute
at UW–M, whose mission is to understand the impediments to the successful
recruitment and advancement of women faculty in the sciences and to develop
and study interventions intended to reduce those barriers.
Carole A. Heilman, Ph.D., is director of the Division of Microbiology and
Infectious Diseases (DMID) of the National Institute of Allergy and Infectious
Diseases (NIAID). She received her bachelor’s degree in biology from Boston
University in 1972 and earned her master’s degree and doctorate in microbiology from Rutgers University in 1976 and 1979, respectively. Dr. Heilman began
her NIH career as a postdoctoral research associate with the National Cancer
Institute, where she carried out research on the regulation of gene expression during cancer development. In 1986, she came to NIAID as the influenza and viral
respiratory diseases program officer in DMID and, in 1988, she was appointed
chief of the respiratory diseases branch, where she coordinated the development of acellular pertussis vaccines. She joined the Division of AIDS as deputy
director in 1997 and was responsible for developing the Innovation Grant Program for Approaches in HIV Vaccine Research. She is the recipient of several
notable awards for outstanding achievement. Throughout her extramural career,
Dr. Heilman has contributed articles on vaccine design and development to many
scientific journals and has served as a consultant to the World Bank and WHO.
She is also a member of several professional societies, including the IDSA, the
ASM, and the American Society of Virology.
David L. Heymann, M.D., is currently assistant director-general for communicable diseases and the representative of the director-general for polio eradication
at the World Health Organization. Prior to that, from July 1998 until July 2003,
Dr. Heymann was executive director of the WHO Communicable Diseases Cluster which includes WHO’s programs on infectious and tropical diseases, and
from which the public health response to SARS was mounted in 2003. From
October 1995 to July 1998 Dr. Heymann was director of the WHO Program on
Emerging and other Communicable Diseases, and prior to that was the chief of
research activities in the WHO Global Program on AIDS. Before joining WHO,
Dr. Heymann worked for 13 years as a medical epidemiologist in sub-Saharan
Africa (Cameroon, Côte d’Ivoire, Malawi, and the Democratic Republic of
Congo—formerly Zaire) on assignment from the CDC in CDC-supported activities. These activities aimed at strengthening capacity in surveillance of infectious
diseases and their control, with special emphasis on the childhood immunizable
diseases including measles and polio, African haemorrhagic fevers, poxviruses,
and malaria. While based in Africa, Dr. Heymann participated in the investigation of the first outbreak of Ebola in Yambuku (former Zaire) in 1976, then
again investigated the second outbreak of Ebola in 1977 in Tandala, and in 1995
directed the international response to the Ebola outbreak in Kikwit. Prior to these
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13 years in Africa, Dr. Heymann worked two years in India as a medical epidemiologist in the WHO Smallpox Eradication Program. Dr. Heymann holds a B.A.
from the Pennsylvania State University, an M.D. from Wake Forest University, a
Diploma in Tropical Medicine and Hygiene from the London School of Hygiene
and Tropical Medicine, and has completed practical epidemiology training in
the two-year Epidemic Intelligence Service (EIS) of CDC. He is a recipient of
the American Public Health Association Award for Excellence and the American
Society of Tropical Medicine and Hygiene Donald MacKay medal, and is a member of the IOM. Dr. Heymann has published over 140 scientific articles on infectious diseases and related issues in medical and scientific journals, and authored
several chapters on infectious diseases in medical textbooks. He is currently editor of the 18th edition of the Control of Communicable Diseases Manual, a joint
publication of WHO and the American Public Health Association.
Phil Hosbach is vice president of New Products and Immunization Policy at
Sanofi Pasteur. The departments under his supervision are new product marketing, state and federal government policy, business intelligence, bids and contracts,
medical communications, public health sales, and public health marketing. His
current responsibilities include oversight of immunization policy development.
He acts as Sanofi Pasteur’s principal liaison with CDC. Mr. Hosbach graduated
from Lafayette College in 1984 with a degree in biology. He has 20 years of
pharmaceutical industry experience, including the past 17 years focused solely on
vaccines. He began his career at American Home Products in Clinical Research
in 1984. He joined Aventis Pasteur (then Connaught Labs) in 1987 as clinical
research coordinator and has held research and development positions of increasing responsibility, including clinical research manager and director of clinical
operations. Mr. Hosbach also served as project manager for the development
and licensure of Tripedia, the first diphtheria, tetanus, and acellular pertussis
(DTaP) vaccine approved by FDA for use in U.S. infants. During his clinical
research career at Aventis Pasteur, he contributed to the development and licensure of seven vaccines and has authored or coauthored several clinical research
articles. From 2000 through 2002, Mr. Hosbach served on the board of directors
for Pocono Medical Center in East Stroudsburg, Pennsylvania. Since 2003 he
has served on the board of directors of Pocono Health Systems, which includes
Pocono Medical Center.
James M. Hughes, M.D., received his B.A. in 1966 and M.D. in 1971 from
Stanford University. He completed a residency in internal medicine at the University of Washington and a fellowship in infectious diseases at the University
of Virginia. He is board certified in internal medicine, infectious diseases, and
preventive medicine. He first joined CDC as an epidemic intelligence service
officer in 1973. During his CDC career, he has worked primarily in the areas
of foodborne disease and infection control in health-care settings. He became
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director of NCID in 1992. The center is currently working to address domestic
and global challenges posed by emerging infectious diseases and the threat of
bioterrorism. He is a member of the IOM and a fellow of the American College
of Physicians, the IDSA, and the AAAS. He is an assistant surgeon general in
the Public Health Service.
Stephen A. Johnston, Ph.D., is currently director of the Center for Innovations in Medicine in the Biodesign Institute at Arizona State University. His
center focuses on formulating and implementing disruptive technologies for
basic problems in health care. The center has three divisions: Genomes to Vaccines, Cancer Eradication, and DocInBox. The Genomes to Vaccines group has
developed high-throughput systems to screen for vaccine candidates and is applying them to predict and produce chemical vaccines. The Cancer Eradication
group is working on formulating a universal prophylactic vaccine for cancer.
The DocInBox group is developing technologies to facilitate presymptomatic
diagnosis. Dr. Johnston founded the Center for Biomedical Inventions (a.k.a.,
Center for Translation Research) at the University of Texas–Southwestern, the
first center of its kind in the medical arena. He and his colleagues have developed
numerous inventions and innovations, including the gene gun, genetic immunization, TEV protease system, organelle transformation, digital optical chemistry
arrays, expression library immunization, linear expression elements, and others.
He also was involved in transcription research for years, first cloning Gal4, then
later discovering functional domains in transcription factors and the connection
of the proteasome to transcription. He has been professor at the University of
Texas Southwestern Medical Center at Dallas and associate and assistant professor at Duke University. He has been involved in several capacities as an advisor
on biosecurity since 1996 and is a member of the WRCE SAB and a founding
member of BioChem 20/20.
Gerald T. Keusch, M.D., is provost and dean for Global Health at Boston
University and Boston University School of Public Health. He is a graduate of
Columbia College (1958) and Harvard Medical School (1963). After completing a residency in internal medicine, fellowship training in infectious diseases,
and 2 years as an NIH research associate at the Southeast Asia Treaty Organization (SEATO) Medical Research Laboratory in Bangkok, Thailand, Dr. Keusch
joined the faculty of Mt. Sinai School of Medicine in 1970, where he established
a laboratory to study the pathogenesis of bacillary dysentery and the biology and
biochemistry of Shiga toxin. In 1979 he moved to Tufts Medical School and New
England Medical Center in Boston to found the Division of Geographic Medicine, which focused on the molecular and cellular biology of tropical infectious
disease. In 1986 he integrated the clinical infectious diseases program into the
Division of Geographic Medicine and Infectious Diseases, continuing as division chief until 1998. He has worked in the laboratory and in the field in Latin
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America, Africa, and Asia on basic and clinical infectious diseases and HIV/
AIDS research. From 1998 to 2003, he was associate director for international
research and director of the Fogarty International Center at NIH. Dr. Keusch is a
member of the American Society for Clinical Investigation (ASCI), the Association of American Physicians, the ASM, and the IDSA. He has received the Squibb
(1981), Finland (1997), and Bristol (2002) awards of the IDSA. In 2002 he was
elected to the IOM.
Rima F. Khabbaz, M.D., is director of NCID at CDC. She received her B.S. in
1975 and her M.D. in 1979 from the American University of Beirut in Lebanon.
She trained in internal medicine and completed a fellowship in infectious diseases at the University of Maryland in Baltimore. She is board certified in
internal medicine. She first joined CDC as an epidemic intelligence service
officer in 1980. During her CDC career, she worked primarily in the areas of
health care–associated infections and viral diseases. She is a fellow of the IDSA
and an elected member of the American Epidemiologic Society. She served on
FDA’s Blood Product Advisory Committee, on FDA’s Transmissible Spongiform
Encephalopathy Advisory Committee and on the Annual Meeting Scientific Program Committee of the IDSA. She played a leading role in developing CDC’s
programs related to blood and food safety and in CDC’s responses to outbreaks
of new and reemerging diseases.
Lonnie J. King, D.V.M., is currently the director of CDC’s new National Center
for Zoonotic, Vector-Borne, and Enteric Diseases (NCZVED). Dr. King leads the
center’s activities for surveillance, diagnostics, disease investigations, epidemiology, research, public education, policy development, and disease prevention and
control programs. NCZVED also focuses on waterborne, foodborne, vectorborne,
and zoonotic diseases of public health concern, which also includes most of CDC’s
select and bioterrorism agents, neglected tropical diseases, and emerging zoonoses.
Before serving as director, he was the first chief of the agency’s Office of Strategy
and Innovation. In 1996 Dr. King was appointed dean of the College of Veterinary
Medicine, Michigan State University. He served for 10 years as dean of the college. As dean, he was the chief executive officer for academic programs, research,
the teaching hospital, diagnostic center for population and animal health, basic and
clinical science departments, and outreach and continuing education programs. As
dean and professor of large animal clinical sciences, Dr. King was instrumental
in obtaining funds for the construction of the $60 million Diagnostic Center for
Population and Animal Health, initiated the Center for Emerging Infectious Diseases in the college, served as the campus leader in food safety, and had oversight
for the National Food Safety and Toxicology Center. He brought the Center for
Integrative Toxicology to the college and was the university’s designated leader
for counterbioterrorism activities for his college and was involved in reestablishing
public health programs at Michigan State University. Prior to this, Dr. King was
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administrator for USDA’s Animal and Plant Health Inspection Service (APHIS).
Dr. King served as the country’s chief veterinary officer for 5 years and worked
extensively in global trade agreements within the North American Free Trade
Agreement and the World Trade Organization. Before beginning his government
career in 1977, he was in private veterinary practice for 7 years in Ohio and
Georgia. He received his B.S. and D.V.M. from Ohio State University in 1966
and 1970, respectively. He earned his M.S. in epidemiology from the University
of Minnesota while on special assignment with USDA in 1980. He received his
master’s in public administration from The American University in Washington,
DC, in 1991. Dr. King has a broad knowledge of animal agriculture and the veterinary profession through his work with other governmental agencies, universities,
major livestock and poultry groups, and private practitioners. Dr. King is a boardcertified member of the American College of Veterinary Preventive Medicine and
has completed the senior executive fellowship program at Harvard University. He
served as president of the Association of American Veterinary Medical Colleges
from 1999 to 2000 and was vice chair for the National Commission on Veterinary
Economic Issues from 2000 to 2004. Dr. King helped start the National Alliance
for Food Safety, served on the Governor’s Task Force on Chronic Wasting Disease for the state of Michigan, and was a member of four NAS committees; most
recently he chaired The National Academies Committee on Assessing the Nation’s
Framework for Addressing Animal Diseases. Dr. King is one of the developers
of the Science, Politics, and Animal Health Policy Fellowship Program, and he
lectures extensively on the future of animal health and veterinary medicine. He
served as a consultant and member of the Board of Scientific Counselors to CDC’s
National Center for Infectious Diseases and is a member of the IOM’s Forum on
Microbial Threats. Dr. King is an editor for the OIE Scientific Review on Emerging Zoonoses, is a current member of FDA’s Board of Scientific Advisors, and is
president of the American Veterinary Epidemiology Society. Dr. King was elected
to the IOM in 2004.
Col. George W. Korch, Ph.D., is commander, U.S. Army Medical Research
Institute for Infectious Diseases, Ft. Detrick, Maryland. Dr. Korch attended
Boston University and earned a B.S. in biology in 1974, followed by postgraduate
study in mammalian ecology at the University of Kansas from 1975 to 1978. He
earned his Ph.D. from the Johns Hopkins School of Hygiene and Public Health
in Immunology and Infectious Diseases in 1985, followed by postdoctoral experience at Johns Hopkins from 1985 to 1986. His areas of training and specialty are
the epidemiology of zoonotic viral pathogens and medical entomology. For the
past 15 years, he has also been engaged in research and program management for
medical defense against biological pathogens used in terrorism or warfare.
Joshua Lederberg, Ph.D., is professor emeritus of molecular genetics and informatics and Sackler Foundation Scholar at the Rockefeller University in New York
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City. His lifelong research, for which he received the Nobel Prize in 1958, has
been in genetic structure and function in microorganisms. He has a keen interest
in international health and from 1990 to 1992 was co-chair of a previous IOM
Committee on Emerging Microbial Threats to Health. Currently he is co-chair
of the Committee on Emerging Microbial Threats to Health in the Twenty-First
Century. He has been a member of the NAS since 1957 and is a charter member
of the IOM.
Lynn G. Marks, M.D., is board certified in internal medicine and infectious diseases. He was on the faculty at the University of South Alabama College of Medicine in the Infectious Diseases Department, focusing on patient care, teaching,
and research, where his academic research interest was in the molecular genetics
of bacterial pathogenicity. He subsequently joined the anti-infectives clinical
group of SmithKline Beecham (now GlaxoSmithKline) and later advanced to be
global head of the Consumer Healthcare Division Medical and Regulatory Group.
He then returned to pharmaceutical research and development as global head of
the Infectious Diseases Therapeutic Area Strategy Team for GlaxoSmithKline.
Edward McSweegan, Ph.D., is a program officer at NIAID. He graduated from
Boston College with a B.S. in 1978. He has an M.S. in microbiology from the
University of New Hampshire and a Ph.D. in microbiology from the University
of Rhode Island. He was a National Research Council Associate from 1984 to
1986 and did postdoctoral research at the Naval Medical Research Institute in
Bethesda, Maryland. Dr. McSweegan served as an AAAS diplomacy fellow in the
U.S. State Department from 1986 to 1988 and negotiated science and technology
agreements with Poland, Hungary, and the former Soviet Union. After moving to
NIH, he continued to work on international health and science projects in Egypt,
Israel, India, and Russia. Currently, he manages NIAID’s bilateral program with
India, the Indo–U.S. Vaccine Action Program, and represents NIAID in the HHS
Biotechnology Engagement Program with Russia and related countries. He is a
member of the AAAS, the ASM, and the DC Science Writers Association. He is
the author of numerous journal and science articles.
Stephen S. Morse, Ph.D., is founding director of the Center for Public Health
Preparedness at the Mailman School of Public Health of Columbia University and
is an associate professor in the epidemiology department. He recently returned
to Columbia after 4 years in government service as program manager at the
Defense Advanced Research Projects Agency (DARPA), where he codirected
the Pathogen Countermeasures Program and subsequently directed the Advanced
Diagnostics Program. Before coming to Columbia, he was assistant professor of
virology at Rockefeller University in New York, where he remains an adjunct faculty member. He is the editor of two books, Emerging Viruses (Oxford University
Press, 1993; paperback, 1996), which was selected by American Scientist for its
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APPENDIX C
list of 100 Top Science Books of the 20th Century, and The Evolutionary Biology
of Viruses (Raven Press, 1994). He currently serves as a section editor of the CDC
journal Emerging Infectious Diseases and was formerly an editor-in-chief of the
Pasteur Institute’s journal Research in Virology. Dr. Morse was chair and principal
organizer of the 1989 NIAID/NIH Conference on Emerging Viruses, for which he
originated the term and concept of emerging viruses/infections. He has served as
a member of the IOM/NAS Committee on Emerging Microbial Threats to Health,
chaired its Task Force on Viruses, and was a contributor to the resulting report,
Emerging Infections (1992). He was a member of the IOM’s Committee on Xenograft Transplantation and he currently serves on the Steering Committee of the
IOM’s Forum on Emerging Infections (now the Forum on Microbial Threats). Dr.
Morse also served as an adviser to WHO, the Pan‑American Health Organization,
FDA, the Defense Threat Reduction Agency, and other agencies. He is a fellow of
the New York Academy of Sciences and a past chair of its microbiology section,
a fellow of the American Academy of Microbiology of the American College of
Epidemiology, and an elected life member of the Council on Foreign Relations.
He was the founding chair of ProMED, the nonprofit international Program to
Monitor Emerging Diseases, and was one of the originators of ProMED-mail,
an international network inaugurated by ProMED in 1994 for outbreak reporting
and disease monitoring using the Internet. Dr. Morse received his Ph.D. from the
University of Wisconsin–Madison.
Michael T. Osterholm, Ph.D., M.P.H., is director of the Center for Infectious
Disease Research and Policy at the University of Minnesota, where he is also professor at the School of Public Health. Previously, Dr. Osterholm was the state epidemiologist and chief of the acute disease epidemiology section for the Minnesota
Department of Health. He has received numerous research awards from NIAID
and CDC. He served as principal investigator for the CDC-sponsored Emerging
Infections Program in Minnesota. He has published more than 240 articles and
abstracts on various emerging infectious disease problems and is the author of the
best-selling book, Living Terrors: What America Needs to Know to Survive the
Coming Bioterrorist Catastrophe. He is past president of the Council of State and
Territorial Epidemiologists. He currently serves on the IOM Forum on Microbial
Threats. He has also served on the IOM Committee to Ensure Safe Food from
Production to Consumption, the IOM Committee on the Department of Defense
Persian Gulf Syndrome Comprehensive Clinical Evaluation Program, and as a
reviewer for the IOM report on chemical and biological terrorism.
George Poste, Ph.D., D.V.M., is director of the Arizona Biodesign Institute and
Dell E. Webb Distinguished Professor of Biology at Arizona State University.
From 1992 to 1999, he was chief science and technology officer and president,
Research and Development of SmithKline Beecham (SB). During his tenure at
SB, he was associated with the successful registration of 29 drug, vaccine, and
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diagnostic products. He is chairman of diaDexus and Structural GenomiX in
California and Orchid Biosciences in Princeton. He serves on the board of directors of AdvancePCS and Monsanto. He is an advisor on biotechnology to several
venture capital funds and investment banks. In May 2003, he was appointed as
director of the Arizona Biodesign Institute at Arizona State University. This is a
major new initiative combining research groups in biotechnology, nanotechnology, materials science, advanced computing, and neuromorphic engineering.
He is a fellow of Pembroke College in Cambridge and distinguished fellow at
the Hoover Institution and Stanford University. He is a member of the Defense
Science Board of the U.S. Department of Defense. In this capacity he chairs the
Task Force on Bioterrorism. He is also a member of the NAS Working Group on
Defense Against Bioweapons. Dr. Poste is a board-certified pathologist, a fellow
of the Royal Society, and a fellow of the Academy of Medical Sciences. He was
awarded the rank of Commander of the British Empire by Queen Elizabeth II in
1999 for services to medicine and for the advancement of biotechnology. He has
published more than 350 scientific papers; has coedited 15 books on cancer, biotechnology, and infectious diseases; and serves on the editorial board of multiple
technical journals. He is routinely invited to be the keynote speaker at a wide
variety of academic, corporate, investment, and government meetings to discuss
the impact of biotechnology and genetics on health care and the challenges posed
by bioterrorism.
David A. Relman, M.D., is an associate professor of medicine (infectious diseases and geographic medicine) and of microbiology and immunology at Stanford
University School of Medicine, and chief of the infectious disease section at the
Veterans Affairs (VA) Palo Alto Health Care System. Dr. Relman received his
B.S. in biology from the Massachusetts Institute of Technology and his M.D.
from Harvard Medical School. He completed his residency in internal medicine
and a clinical fellowship in infectious diseases at Massachusetts General Hospital,
Boston, after which he moved to Stanford for a postdoctoral fellowship in 1986,
and joined the faculty there in 1994. His research focus is on understanding the
structure and role of the human indigenous microbial communities in health and
disease. This work brings together approaches from ecology, population biology,
environmental microbiology, genomics, and clinical medicine. A second area
of investigation explores the classification structure of humans and nonhuman
primates with systemic infectious diseases, based on patterns of genome-wide
gene transcript abundance in blood and other tissues. The goals of this work are to
understand mechanisms of host–pathogen interaction, as well as predict clinical
outcome at early time points in the disease process. His scientific achievements
include the description of a novel approach for identifying previously unknown
pathogens, the characterization of a number of new human microbial pathogens,
including the agent of Whipple’s disease, and some of the most in-depth analyses
to date of human indigenous microbial communities. Among his other activities,
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Dr. Relman currently serves as chair of the Board of Scientific Counselors of the
National Institute of Dental and Craniofacial Research (NIH), is a member of the
National Science Advisory Board for Biosecurity, and advises a number of U.S.
government departments and agencies on matters related to pathogen diversity,
the future life sciences landscape, and the nature of present and future biological
threats. He was co-chair of the Committee on Advances in Technology and the
Prevention of Their Application to Next Generation Biowarfare Threats for the
NAS. He received the Squibb Award from the IDSA in 2001, the Senior Scholar
Award in Global Infectious Diseases from the Ellison Medical Foundation in
2002, an NIH Director’s Pioneer Award in 2006, and a Doris Duke Distinguished
Clinical Scientist Award in 2006. He is also a fellow of the American Academy
of Microbiology.
Gary A. Roselle, M.D., received his M.D. from the Ohio State University School
of Medicine in 1973. He served his residency at the Northwestern University
School of Medicine and his infectious diseases fellowship at the University of
Cincinnati School of Medicine. He is the program director for infectious diseases
for the VA Central Office in Washington, DC, as well as the chief of the medical
service at the Cincinnati VA Medical Center. He is a professor of medicine in
the Department of Internal Medicine, Division of Infectious Diseases at the University of Cincinnati College of Medicine. Dr. Roselle serves on several national
advisory committees. In addition, he is currently heading the Emerging Pathogens
Initiative for the Department of Veterans Affairs. He has received commendations
from the Cincinnati Medical Center director, the under secretary for health for
the Department of Veterans Affairs, and the secretary of veterans affairs for his
work in the infectious diseases program for the Department of Veterans Affairs.
He has been an invited speaker at several national and international meetings and
has published more than 80 papers and several book chapters.
Janet Shoemaker is director of the ASM’s Public Affairs Office, a position she
has held since 1989. She is responsible for managing the legislative and regulatory affairs of this 42,000-member organization, the largest single biological science society in the world. She has served as principal investigator for a project
funded by the National Science Foundation (NSF) to collect and disseminate data
on the job market for recent doctorates in microbiology and has played a key role
in ASM projects, including the production of the ASM Employment Outlook in
the Microbiological Sciences and The Impact of Managed Care and Health System Change on Clinical Microbiology. Previously, she held positions as assistant
director of public affairs for the ASM, as ASM coordinator of the U.S./U.S.S.R.
Exchange Program in Microbiology, a program sponsored and coordinated by
NSF and the U.S. Department of State, and as a freelance editor and writer. She
received her baccalaureate, cum laude, from the University of Massachusetts, and
is a graduate of the George Washington University programs in public policy and
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in editing and publications. She has served as commissioner to the Commission
on Professionals in Science and Technology and as the ASM representative to
the ad hoc Group for Medical Research Funding, and is a member of Women in
Government Relations, the American Society of Association Executives, and the
AAAS. She has coauthored published articles on research funding, biotechnology,
biological weapons control, and public policy issues related to microbiology.
Brian J. Staskawicz, Ph.D., is professor and chair, Department of Plant and
Microbial Biology, University of California–Berkeley. Dr. Staskawicz received
his B.A. in biology from Bates College in 1974 and his Ph.D. from the University
of California–Berkeley in 1980. Dr. Staskawicz’s work has contributed greatly to
understanding the molecular interactions between plants and their pathogens. He
was elected to the NAS in 1998 for elucidating the mechanisms of disease resistance, as his lab was the first to clone a bacterial effector gene from a pathogen
and among the first to clone and characterize plant disease-resistance genes. Dr.
Staskawicz’s research focuses on the interaction of the bacteria, Pseudomonas
and Xanthomonas, with Arabidopsis, tomato, and pepper. He has published extensively in this area and is a one of the leading scientists in the world working on
elucidating the molecular basis of plant innate immunity.
Terence Taylor is president and director of the International Council for the Life
Sciences (ICLS). He is responsible for the overall direction of the ICLS and its
programs, which have the goal of enhancing global biosafety and biosecurity.
From 1995 to 2005, he was assistant director of the International Institute for
Strategic Studies (IISS), a leading independent international institute, and president and executive director of its U.S. office (2001 to 2005). He studies international security policy, risk analysis, and scientific and technological developments
and their impact on political and economic stability worldwide. At IISS he was
one of the Institute’s leading experts on issues associated with nuclear, biological,
and chemical weapons and their means of delivery. In his previous appointments,
he has had particular responsibilities for issues affecting public safety and security in relation to biological risks and advances in the life sciences. He was one of
the commissioners to the United Nations (UN) Special Commission on Iraq, for
which he also conducted missions as a chief inspector. He was a research fellow
on the Science Program at the Center for International Security and Cooperation
at Stanford University, where he carried out, among other subjects, studies of the
implications for government and industry of the weapons of mass destruction
treaties and agreements. He has also carried out consultancy work for the International Committee of the Red Cross on the implementation and development of
the laws of armed conflict. He has served as chairman of the World Federation of
Scientists’ Permanent Monitoring Panel on Risk Analysis. He served as a career
officer in the British Army on operations in many parts of the world, including counterterrorist operations and UN peacekeeping. His publications include
Copyright © National Academy of Sciences. All rights reserved.
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263
APPENDIX C
monographs, book chapters, and articles for, among others, Stanford University,
the World Economic Forum, Stockholm International Peace Research Institute
(SIPRI), the Crimes of War Project, International Herald Tribune, Wall Street
Journal, the International Defence Review, the Independent (London), Tiempo
(Madrid), the International and Comparative Law Quarterly, the Washington
Quarterly, and other scholarly journals, including unsigned contributions to IISS
publications.
Copyright © National Academy of Sciences. All rights reserved.
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Copyright © National Academy of Sciences. All rights reserved.
Detection: Assessing the Challenges -- Finding
Solutions, Workshop Summary
Forum on Microbial Threats, Stanley M. Lemon,
Margaret A. Hamburg, P. Frederick Sparling, Eileen R.
Choffnes, and Alison Mack, Rapporteurs
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Global Infectious Disease
Surveillance and Detection:
Assessing the Challenges—
Finding Solutions
Workshop Summary
Rapporteurs: Stanley M. Lemon, Margaret A. Hamburg,
P. Frederick Sparling, Eileen R. Choffnes, and Alison Mack
Forum on Microbial Threats
Board on Global Health
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Advising the Nation. Improving Health.
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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FORUM ON MICROBIAL THREATS
STANLEY M. LEMON (Chair), School of Medicine, University of Texas
Medical Branch, Galveston
MARGARET A. HAMBURG (Vice-chair), Nuclear Threat Initiative/Global
Health & Security Initiative, Washington, DC
P. FREDERICK SPARLING (Vice-chair), University of North Carolina,
Chapel Hill
DAVID W. K. ACHESON, Center for Food Safety and Applied Nutrition,
Food and Drug Administration, Rockville, Maryland
RUTH L. BERKELMAN, Emory University, Center for Public Health Pre
paredness and Research, Rollins School of Public Health, Atlanta, Georgia
ENRIQUETA C. BOND, Burroughs Wellcome Fund, Research Triangle Park,
North Carolina
ROGER G. BREEZE, Centaur Science Group, Washington, DC
STEVEN J. BRICKNER, Pfizer Global Research and Development, Pfizer
Inc., Groton, Connecticut
NANCY CARTER-FOSTER, Program for Emerging Infections and
HIV/AIDS, U.S. Department of State, Washington, DC
GAIL H. CASSELL, Eli Lilly & Company, Indianapolis, Indiana
BILL COLSTON, Lawrence Livermore National Laboratory, Livermore,
California
RALPH L. ERICKSON, Global Emerging Infections Surveillance and
Response System, Department of Defense, Silver Spring, Maryland
MARK B. FEINBERG, Merck Vaccine Division, Merck & Co., West Point,
Pennsylvania
J. PATRICK FITCH, National Biodefense Analysis and Countermeasures
Center, Frederick, Maryland
DARRELL R. GALLOWAY, Medical S&T Division, Defense Threat
Reduction Agency, Fort Belvoir, Virginia
S. ELIZABETH GEORGE, Biological and Chemical Countermeasures
Program, Department of Homeland Security, Washington, DC
JESSE L. GOODMAN, Center for Biologics Evaluation and Research, Food
and Drug Administration, Rockville, Maryland
EDUARDO GOTUZZO, Instituto de Medicina Tropical–Alexander von
Humbolt, Universidad Peruana Cayetano Heredia, Lima, Peru
JO HANDELSMAN, College of Agricultural and Life Sciences, University of
Wisconsin, Madison
CAROLE A. HEILMAN, Division of Microbiology and Infectious Diseases,
National Institute of Allergy and Infectious Diseases, National Institutes of
Health, Bethesda, Maryland
DAVID L. HEYMANN, Polio Eradication, World Health Organization,
Geneva, Switzerland
PHIL HOSBACH, New Products and Immunization Policy, Sanofi Pasteur,
Swiftwater, Pennsylvania
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
JAMES M. HUGHES, Global Infectious Diseases Program, Emory
University, Atlanta, Georgia
STEPHEN A. JOHNSTON, Arizona BioDesign Institute, Arizona State
University, Tempe
GERALD T. KEUSCH, Boston University School of Medicine and Boston
University School of Public Health, Massachusetts
RIMA F. KHABBAZ, National Center for Preparedness, Detection and
Control of Infectious Diseases, Centers for Disease Control and
Prevention, Atlanta, Georgia
LONNIE J. KING, Center for Zoonotic, Vectorborne, and Enteric Diseases,
Centers for Disease Control and Prevention, Atlanta, Georgia
GEORGE W. KORCH, U.S. Army Medical Research Institute for Infectious
Diseases, Fort Detrick, Maryland
JOSHUA LEDERBERG, The Rockefeller University, New York
LYNN G. MARKS, Medicine Development Center, GlaxoSmithKline,
Collegeville, Pennsylvania
EDWARD McSWEEGAN, National Institute of Allergy and Infectious
Diseases, National Institutes of Health, Bethesda, Maryland
STEPHEN S. MORSE, Center for Public Health Preparedness, Columbia
University, New York
MICHAEL T. OSTERHOLM, Center for Infectious Disease Research and
Policy, School of Public Health, University of Minnesota, Minneapolis
GEORGE POSTE, Arizona BioDesign Institute, Arizona State University,
Tempe
DAVID A. RELMAN, Stanford University, Palo Alto, California
GARY A. ROSELLE, Central Office, Veterans Health Administration,
Department of Veterans Affairs, Washington, DC
JANET SHOEMAKER, Office of Public Affairs, American Society for
Microbiology, Washington, DC
BRIAN J. STASKAWICZ, Department of Plant and Microbial Biology,
University of California, Berkeley
TERENCE TAYLOR, International Council for the Life Sciences,
Washington, DC
Staff
EILEEN CHOFFNES, Forum Director
ALLISON BRANTLEY, Senior Program Assistant*
SARAH BRONKO, Senior Program Assistant†
ALISON MACK, Science Writer
KATE SKOCZDOPOLE, Research Associate
*Ending June 2007.
†Beginning June 2007.
vi
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BOARD ON GLOBAL HEALTH
Margaret Hamburg (chair), Consultant, Nuclear Threat Initiative,
Washington, DC
George Alleyne, Director Emeritus, Pan American Health Organization,
Washington, DC
Donald Berwick, Clinical Professor of Pediatrics and Health Care Policy,
Harvard Medical School, and President and Chief Executive Officer,
Institute of Healthcare Improvement, Boston, Massachusetts
Jo Ivey Boufford (IOM Foreign Secretary), President, New York Academy of
Medicine, New York
David R. Challoner, Vice President for Health Affairs, Emeritus, University of
Florida, Gainesville
Ciro de Quadros, Albert B. Sabin Vaccine Institute, Washington, DC
Sue Goldie, Associate Professor of Health Decision Science, Department
of Health Policy and Management, Center for Risk Analysis, Harvard
University School of Public Health, Boston, Massachusetts
Richard Guerrant, Thomas H. Hunter Professor of International Medicine
and Director, Center for Global Health, University of Virginia School of
Medicine, Charlottesville
Gerald T. Keusch, Assistant Provost for Global Health, Boston University
School of Medicine, and Associate Dean for Global Health, Boston
University School of Public Health, Massachusetts
Jeffrey Koplan, Vice President for Academic Health Affairs, Emory
University, Atlanta, Georgia
Sheila Leatherman, Research Professor, University of North Carolina School of
Public Health, Chapel Hill
Michael Merson, Director, Duke Global Health Institute, Duke University,
Durham, NC
Mark L. Rosenberg, Executive Director, Task Force for Child Survival and
Development, Emory University, Decatur, Georgia
Philip Russell, Professor Emeritus, Bloomberg School of Public Health, The
Johns Hopkins University, Baltimore, Maryland
Staff
Patrick Kelley, Director
Allison Brantley, Senior Program Assistant
IOM boards do not review or approve individual reports and are not asked to endorse conclusions
and recommendations. The responsibility for the content of the reports rests with the authors and the
institution.
vii
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Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Reviewers
This report has been reviewed in draft form by individuals chosen for their
diverse perspectives and technical expertise, in accordance with procedures
approved by the National Research Council’s Report Review Committee. The
purpose of this independent review is to provide candid and critical comments
that will assist the institution in making its published report as sound as possible
and to ensure that the report meets institutional standards for objectivity, evidence, and responsiveness to the study charge. The review comments and draft
manuscript remain confidential to protect the integrity of the deliberative process.
We wish to thank the following individuals for their review of this report:
John Besser, Public Health Laboratory, Minnesota Department of Health
R. James Cook, Department of Plant Pathology, Washington State
University
Charlotte A Gaydos, Division of Infectious Diseases, The Johns Hopkins
University and International STD Reference Laboratory
Although the reviewers listed above have provided many constructive comments and suggestions, they were not asked to endorse the final draft of the report
before its release. The review of this report was overseen by Melvin Worth,
Scholar-in-Residence, Institute of Medicine. Appointed by the Institute of Medicine, he was responsible for making certain that an independent examination of
this report was carried out in accordance with institutional procedures and that all
review comments were carefully considered. Responsibility for the final content
of this report rests entirely with the authoring committee and the institution.
ix
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Preface
The Forum on Emerging Infections was created by the Institute of Medicine
(IOM) in 1996 in response to a request from the Centers for Disease Control and
Prevention (CDC) and the National Institutes of Health (NIH). The purpose of
the Forum is to provide structured opportunities for leaders from government,
academia, and industry to meet and examine issues of shared concern regarding
research, prevention, detection, and management of emerging or reemerging
infectious diseases. In pursuing this task, the Forum provides a venue to foster
the exchange of information and ideas, identify areas in need of greater attention,
clarify policy issues by enhancing knowledge and identifying points of agreement, and inform decision makers about science and policy issues. The Forum
seeks to illuminate issues rather than resolve them; for this reason, it does not
provide advice or recommendations on any specific policy initiative pending
before any agency or organization. Its value derives instead from the diversity
of its membership and from the contributions that individual members make
throughout the activities of the Forum. In September 2003, the Forum changed
its name to the Forum on Microbial Threats.
About the Workshop
Early detection is essential to the control of emerging, reemerging, and novel
infectious diseases, including agents of bioterrorism. Containing the spread of
such a disease in a profoundly interconnected world requires active vigilance
for signs of an outbreak, rapid recognition of its presence, and diagnosis of
its microbial cause, as well as strategies and resources for an appropriate and
efficient response. While often viewed in terms of public health, the challenges
xi
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http://www.nap.edu/catalog/11996.html
xii
PREFACE
of detecting natural and intentionally introduced disease outbreaks are equally
shared by the plant and animal health communities.
Currently, disease surveillance and detection relies heavily on the astute
individual: the clinician, veterinarian, grower, livestock manager, or agricultural
extension agent who notices atypical or suspicious symptoms and brings them
to the attention of public health, veterinary medicine, or agricultural officials—
including academicians and zoological parks. While most developed countries
have a surveillance system in place and the ability to detect and diagnose human,
animal, and plant diseases, many developing countries—where most of the global
population resides—may not have the resources or infrastructure to support such
activities. Under such circumstances, disease detection occurs on the local level
and depends entirely on the early recognition of both known and novel infectious
diseases.
Technological advances in disease surveillance and detection such as regional
syndromic surveillance, bioinformatics, and new rapid diagnostic methods have
the potential to improve infectious disease control and prevention efforts. Further
improvements are likely to result from ongoing innovations in infectious disease
diagnostics, reporting, and surveillance. However, a number of challenges remain
to be met before deployment of rapid, low-cost, sensitive, and specific point-ofcare disease diagnostics become a reality.
The Forum on Microbial Threats of the Institute of Medicine hosted a public
workshop in Washington, DC, on December 12 and 13, 2006, to consider the
scientific and policy issues—some of them long standing, others more recently
arisen—relevant to the practice of disease surveillance and detection. Through
invited presentations and discussions, participants examined current and emerging methods and strategies for the surveillance and detection of human, animal,
and plant diseases, and assessed the resource needs and opportunities for improving and coordinating infectious disease surveillance, detection, and reporting.
Acknowledgments
The Forum on Microbial Threats and the IOM wish to express their warmest
appreciation to the individuals and organizations who gave their valuable time to
provide information and advice to the Forum through their participation in this
workshop. A full list of presenters can be found in Appendix A.
The Forum is indebted to the IOM staff who contributed during the course
of the workshop and the production of this workshop summary. On behalf of the
Forum, we gratefully acknowledge the efforts led by Eileen Choffnes, director
of the Forum, and Kate Skoczdopole, research associate, for dedicating much
effort and time to developing this workshop’s agenda and for their thoughtful and
insightful approach and skill in translating the workshop’s proceedings and discussion into this workshop summary. We would also like to thank the following
IOM staff and consultants for their valuable contributions to this activity: Patrick
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
xiii
PREFACE
Kelley, Alison Mack, Sarah Bronko, Bronwyn Schrecker, Allison Brantley, Lara
Andersen, and Laura Penny.
Finally, the Forum wishes to recognize the sponsors that supported this
activity. Financial support for this project was provided by the U.S. Department
of Health and Human Services: National Institutes of Health, National Institute
of Allergy and Infectious Diseases, Centers for Disease Control and Prevention,
and Food and Drug Administration; U.S. Department of Defense: Global Emerging Infections Surveillance and Response System, Walter Reed Army Institute of
Research, and Defense Threat Reduction Agency; U.S. Department of Veterans
Affairs; U.S. Department of Homeland Security; Lawrence Livermore National
Laboratory; American Society for Microbiology; Sanofi Pasteur; Burroughs
Wellcome Fund; Pfizer; GlaxoSmithKline; Infectious Diseases Society of America; and the Merck Company Foundation. The views presented in this workshop
summary report are those of the workshop participants and rapporteurs and are
not necessarily those of the Forum on Microbial Threats or its sponsors.
Stanley M. Lemon, Chair
Margaret A. Hamburg, Vice-chair
P. Frederick Sparling, Vice-chair
Forum on Microbial Threats
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Contents
Summary and Assessment
1
1 Surveillance Strategies
Overview, 45
Syndromic Surveillance: Moving from Theory to Practice, 49
Patrick W. Kelley, M.D., Dr.P.H.
Syndromic Surveillance in Public Health Practice, 63
Michael A. Stoto, Ph.D.
Implications of “Real Time” Versus “Batch Reporting” for
Surveillance, 72
Joseph Lombardo, M.S.
One World—One Health: Wildlife and Emerging Disease
Surveillance, 77
William B. Karesh, D.V.M.
Agricultural Biosecurity: Threats and Impacts for Plant Pathogens, 86
Jacqueline Fletcher, Ph.D., and James P. Stack, Ph.D.
Plant Biosecurity Infrastructure for Disease Surveillance and
Diagnostics, 95
James P. Stack, Ph.D., and Jacqueline Fletcher, Ph.D.
References, 102
2
Surveillance Networks
Overview, 107
Global Infectious Disease Surveillance and Early Warning Systems:
ProMED and ProMED-Mail, 109
Stephen S. Morse, Ph.D.
xv
Copyright © National Academy of Sciences. All rights reserved.
45
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xvi
CONTENTS
Global Public Health Surveillance: The Role of Nontraditional
Surveillance Tools, 116
Abla Mawudeku, M.P.H., M. Ruben, M.D., Ph.D.,
and R. Lemay, B.Sc., M.B.A.
HealthMap: Internet-Based Emerging Infectious Disease
Intelligence, 122
John S. Brownstein, Ph.D., Clark C. Freifeld, B.S., Ben Y. Reis, Ph.D.,
and Kenneth D. Mandl, M.D., M.P.H.
Using Cell Phone Technology for Infectious Disease Surveillance in
Low-Resource Environments: A Case Study from Peru, 136
Pamela R. Johnson, Ph.D., and David L. Blazes, M.D., M.P.H.
�����������������������������������������������������������
References, 153
3
Detection and Diagnostics
158
Overview, 158
Partnering for Better Microbial Diagnostics, 160
Mark D. Perkins, M.D., and Peter M. Small, M.D.
Rapid Infectious Disease Diagnostic Assays, 165
Mark J. Wolcott, Ph.D., Randal J. Schoepp, Ph.D.,
David A. Norwood, Ph.D., and David R. Shoemaker, Ph.D.
Emerging Tools for Microbial Diagnosis, Surveillance, and
Discovery, 177
W. Ian Lipkin, M.D., and Thomas Briese, Ph.D.
The Potential Importance of Presymptomatic, Host-Based Diagnosis in
Biodefense and Standard Health Care, 193
Stephen Albert Johnston, Ph.D.
References, 207
4
Resource Needs and Opportunities
Overview, 213
Coordination of Disease Surveillance, Detection, Diagnostics, and
Reporting, 216
William D. Hueston, D.V.M., Ph.D.
Improving Infectious Disease Surveillance and Detection: A Public
Health Laboratory Perspective, 224
Frances Pouch Downes, Dr.P.H.
References, 230
Appendixes
A Agenda
B Acronyms
C Forum Member Biographies
Copyright © National Academy of Sciences. All rights reserved.
213
233
238
243
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Tables, Figures, and Boxes
Tables
SA-1
SA-2
1-1
1-2
1-3
Animal Diseases Associated with Direct and Indirect Human
Impacts, 12
Current Public Health Paradigm and Alternative World View, 34
Sources for Syndromic Surveillance, 2003 and 2006 Annual Meeting
Abstracts, 62
Potential Sources of Data for Syndromic Surveillance, 62
U.S. Select Agent List for Plants, 91
2-1
Top Infectious Disease Alerts from the HealthMap System, October 1,
2006–February 16, 2007, 128
3-1
3-2
Department of Defense (DoD) Acquisition Program for Diagnostic
Devices, 168
Criteria for Proof of Causation, 179
4-1
Current Public Health Paradigm and Alternative World View, 221
Figures
SA-1
SA-2
SA-3
The economic impact of selected infectious diseases, 13
Traditional public health reporting, 18
The power of the ProMED surveillance network, 19
xvii
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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xviii
TABLES, FIGURES, AND BOXES
SA-4
Source of initial reporting of potential events of public health concern
by WHO between January 1, 2001, and December 31, 2002, 21
SA-5 HealthMap alert volume by source, 23
SA-6 Telephone subscribers per 100 inhabitants, Africa 1995–2004, 24
SA-7 Star Trek medical tricorder, 30
1-1
1-2
1-3
1-4
1-5
1-6
1-7
1-8
1-9
1-10
2-1
2-2
Syndromic surveillance of U.S. marines for treated diarrheal syndromes during the lead-up to the Persian Gulf War, 1990–1991, 52
Conceptual steps in development and implementation of a syndromic
surveillance system in a community, 53
The donut-hole effect, 55
Estimated sensitivity for West Nile virus by different surveillance
methods, 57
E. coli O157:H7 spinach-associated outbreak, 2006, 58
Time associated with confirming spinach-related illness, 58
Locations of surveillance systems in abstracts for the 2006 International Society for Disease Surveillance (ISDS) meeting, 61
System requirements for public health surveillance, 63
Sensitivity of syndromic surveillance (probability of detection by day)
for influenza-like illness at a typical urban hospital emergency room
using four detection algorithms, 67
Electronic health monitoring components, 74
2-8
2-9
2-10
2-11
Epidemic intelligence framework, 117
Global Public Health Intelligence Network (GPHIN) flow of information, 119
Screenshot of the HealthMap system, 125
Framework for Internet-based surveillance, 126
HealthMap geographic coverage, October 1, 2006–
February 16, 2007, 130
Distribution of the earth’s population, 138
Being able to enter and access data from any available communications channels can optimize the use of existing infrastructure, 141
Health-care personnel collect data, 146
Alerta network, 147
Data flow from the field, 148
Outbreak of diarrhea as reported by the system, 150
3-1
3-2
3-3
3-4
3-5
Product development path for microbial diagnostics, 164
Infection and response time course, 166
Orthogonal diagnostic testing, 167
Acquisition program—evolutionary strategy, 168
Diagnostic system architecture, 172
2-3
2-4
2-5
2-6
2-7
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xix
TABLES, FIGURES, AND BOXES
3-6
3-7
3-8
3-9
3-10
3-11
3-12
3-13
3-14
3-15
3-16
3-17
3-18
3-19
3-20
3-21
3-22
3-23
3-24
Comprehensive integrated diagnostic system, 176
A staged strategy for pathogen detection and discovery, 183
Schematic representation of MassTag PCR procedure, 183
Greene pathogen database, 186
The Bio-Maginot line, 195
Changing spectrum of biothreat risk, 196
Growth of GenBank, 1982–2005, 197
The combination of rapid knowledge and technological growth will
create the potential to make new pathogens, 198
The threat space is becoming increasingly complex, 198
Biosignature pattern recognition in human diseases, 199
Personalized medicine based on biosignatures, 200
Biosignatures versus biomarkers, 201
Upper respiratory disease incubation periods, 202
Program to create DocInBox diagnosis, 203
Health-care spending projections, 204
In 2005, 18 percent of GDP was spent on health care, 205
Comparison of U.S. spending on energy and health care,
1970–2004, 206
Average annual health-care expenditures by age, 2005, 206
Human species needs to square life’s curve, 207
Box
3-1
Example of Diagnostic Systems Validation Parameters, 173
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Summary and Assessment
GLOBAL INFECTIOUS DISEASE SURVEILLANCE AND DETECTION:
ASSESSING THE CHALLENGES—fINDING SOLUTIONS
Early detection is essential to the control of emerging, reemerging, and novel
infectious diseases, whether naturally occurring or intentionally introduced. Containing the spread of such diseases in a profoundly interconnected world requires
active vigilance for signs of an outbreak, rapid recognition of its presence, and
diagnosis of its microbial cause, in addition to strategies and resources for an
appropriate and efficient response. Although these actions are often viewed in
terms of human public health, they also challenge the plant and animal health
communities.
Surveillance, defined as “the continual scrutiny of all aspects of occurrence
and spread of a disease that are pertinent to effective control” (IOM, 2003; Last,
1995; WHO, 2000), involves the “systematic collection, analysis, interpretation,
and dissemination of health data” (WHO, 2000). Disease detection and diagnosis is the act of discovering a novel, emerging, or reemerging disease or disease
event and identifying its cause. Diagnosis is “the cornerstone of effective disease
control and prevention efforts, including surveillance” (IOM, 2003).
Disease surveillance and detection relies heavily on the astute individual: the
clinician, veterinarian, plant pathologist, farmer, livestock manager, or agricultural
extension agent who notices something unusual, atypical, or suspicious and brings
this discovery in a timely way to the attention of an appropriate representative of
human public health, veterinary medicine, or agriculture. Most developed countries have the ability to detect and diagnose human, animal, and plant diseases
The Forum’s role was limited to planning the workshop, and the workshop summary has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop.
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global infectious disease surveillance and detection
and have some type of active or passive surveillance for many well-characterized
agents. However, many developing countries—where most of the global population
resides—lack the resources or infrastructure to support such activities.
One way to close this gap in infectious disease surveillance and detection
may lie with the dispersion of technological advances such as regional syndromic surveillance, bioinformatics, and rapid diagnostic methods. Such tools
and approaches have already made important contributions to infectious disease
control and prevention efforts, albeit mainly in the developed world. Further
improvements are expected to result from ongoing progress in infectious disease
awareness and reporting, and from the continued development and deployment
of efficient, low-cost diagnostic platforms. A major challenge to global disease
surveillance and detection, and to this workshop, is not only the detection and
reporting of well-characterized “known” infectious diseases, but also the ability
to detect novel, emerging, or reemerging infectious diseases in relatively lowtech environments. There is a corresponding need to also develop redundant/
complimentary systems for infectious disease detection that go beyond the yield
of the more traditional surveillance systems and approaches.
The Institute of Medicine’s (IOM’s) Forum on Microbial Threats convened
a workshop addressing Global Infectious Disease Surveillance and Detection:
Assessing the Challenges—Finding Solutions on December 12 and 13, 2006, to
consider these and other scientific and policy issues relevant to the practice of
disease surveillance and detection. To adequately cover a broad range of topics
related to global infectious disease surveillance and detection, the Forum had
to be selective in prioritizing the challenges and exploring solutions to disease
detection and surveillance.
While the workshop did explore a variety of conventional and novel
approaches for disease surveillance and detection, the workshop organizers did
not attempt to critique standard domestic disease detection approaches nor did the
workshop make recommendations about what an “optimal” or “desirable” disease
surveillance and detection system would look like. Workshop participants examined current and emerging methods and strategies for the surveillance, detection,
and diagnosis of human, animal, and plant diseases in order to assess resource
needs and opportunities for improving and coordinating global infectious disease
surveillance, detection, and reporting.
Organization of Workshop Summary
This workshop summary was prepared for the Forum membership in the
name of the rapporteurs and includes a collection of individually authored papers
and commentary. Sections of the workshop summary not specifically attributed
The individually authored papers and commentaries of the speakers and participants at this workshop reflect their appreciation of disease detection and surveillance. As such, we have limited control
over how the experts defined disease surveillance and detection. For our purposes, surveillance is
defined on page 1.
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SUMMARY AND ASSESSMENT
to an individual reflect the views of the rapporteurs and not those of the Forum
on Microbial Threats, its sponsors, or the IOM. The contents of the unattributed
sections are based on the presentations and discussions at the workshop.
The workshop summary is organized into chapters as a topic-by-topic description of the presentations and discussions that took place at the workshop.
Its purpose is to present lessons from relevant experience, to delineate a range of
pivotal issues and their respective problems, and to offer potential responses as
described by workshop participants.
Although this workshop summary provides an account of the individual
presentations, it also reflects an important aspect of the Forum philosophy. The
workshop functions as a dialogue among representatives from different sectors
and presents their beliefs about which areas may merit further attention. The
reader should be aware, however, that the material presented here expresses
the views and opinions of the individuals participating in the workshop and not
the deliberations and conclusions of a formally constituted IOM study committee. These proceedings summarize only what participants stated in the workshop
and are not intended to be an exhaustive exploration of the subject matter or a
representation of consensus evaluation.
Surveillance Strategies
The practice of infectious disease surveillance is no longer restricted to
its original role in recognizing outbreaks of feared human diseases. Workshop
presentations reflected diverse goals, approaches, and methodologies for disease
surveillance in humans, animals, and plants. To place these presentations and
ensuing discussions in context, we begin by briefly describing the multiple purposes served by public health surveillance, as well as current disease surveillance
practices in animals and plants.
Surveillance Purposes and Practices
Public Health Surveillance
In the United States, public health surveillance for infectious disease is conducted through a variety of state and federal programs (GAO, 2004). Health-care
providers and others report cases of “notifiable” infectious disease (as defined by
local and state health codes) to health departments; health department officials
verify disease reports, monitor disease incidence, identify possible outbreaks, and
forward their findings to the Centers for Disease Control and Prevention (CDC).
CDC and other federal agencies, including the Food and Drug Administration
(FDA), the U.S. Department of Agriculture (USDA), and the Department of
Defense (DoD), independently gather and analyze information for disease surveillance. In addition, these agencies fund domestic and international networks of
disease surveillance laboratories that develop diagnostic tests and conduct disease
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global infectious disease surveillance and detection
diagnostic research. Although the CDC has provided guidelines for surveillance
systems funded by the federal government, evaluation is generally lacking. Furthermore, as noted by Forum member Edward McSweegan, little evidence has
been provided on the cost-effectiveness of massive federal public health surveillance investments (see also Eban, 2007).
Early Warning
Some surveillance systems are designed to provide early warning of a disease
threat by detecting the mere presence of potentially infectious microorganisms.
The federal BioWatch program, for example, uses a network of aerosol sampling
stations to monitor major U.S. population centers for a range of potential biological agents, such as anthrax, plague, and tularemia (the entire list of pathogens is
not publicly available) (Shea and Lister, 2003; OIG, 2005). The goal of this program is to detect biological agents within 36 hours of release, allowing federal,
state, and local officials to organize a timely response (OIG, 2005).
Surveillance also extends to symptoms indicative of infectious disease. Syndromic surveillance—the real time monitoring of nonspecific, prediagnostic
indicators for disease outbreaks—has been widely adopted by cities, states, and
the federal government as a means to provide early warning of infectious disease
outbreaks (Sosin, 2003; Stoto, 2005). Several syndromic surveillance systems are
currently operational. The Real Time Outbreak and Disease Surveillance System
(RODS) is used by several states to gather data on the symptoms of emergency
room patients (GAO, 2004). The RODS laboratory at the University of Pittsburgh
also created the National Retail Data Monitor (NRDM) to examine sales of overthe-counter health-care products. The Electronic Surveillance System for the
Early Notification of Community-Based Epidemics (ESSENCE), operated by
DoD, allows epidemiologists to track, in real-time, syndromes reported in daily
data feeds from regional hospitals and clinics in the National Capital area (GAO,
2004). The federal BioSense program—in which the United States has invested
an estimated $230 million since its 2004 inception—aggregates data relevant to
bioterrorism and other public health threats from numerous electronic sources
The
term “syndromic surveillance” applies to surveillance using health-related data that precede
diagnosis and signal a sufficient probability of a case or an outbreak to warrant further public health
response. Though historically syndromic surveillance has been used to target investigation of potential
cases, its utility for detecting outbreaks associated with bioterrorism is increasingly being explored
by public health officials (CDC, 2006a).
The National Retail Data Monitor (NRDM) is a public health surveillance tool that collects and
analyzes daily sales data for over-the-counter health-care products. NRDM collects sales data for
selected over-the-counter health-care products in near-real time from more than 15,000 retail stores
and makes them available to public health officials. NRDM is one of the first examples of a national
data utility for public health surveillance that collects, redistributes, and analyzes daily sales-volume
data of selected health-care products, thereby reducing the effort for both data providers and health
departments. For further information on the NRDM, see Wagner et al., 2004.
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SUMMARY AND ASSESSMENT
(GAO, 2004; Eban, 2007). Despite the considerable investments that have been
made in domestic syndromic surveillance systems, many workshop participants
noted, their promise remains largely unproven (Descenclos, 2006; Bravata et al.,
2004; Reingold, 2003; RAND Corporation, 2004; Stoto, 2005; Sosin, 2003).
Situational Awareness
Surveillance approaches are also used to monitor the progress and outcome
of an intervention to mitigate or stop the progression of a communicable disease,
as during the recent severe acute respiratory syndrome (SARS) pandemic (IOM,
2004; Heymann and Rodier, 2004) and in the campaigns to eradicate smallpox
(Henderson, 1999) and polio (WHO, 2006). The broad and multifaceted use
of surveillance to describe and inform response over the entire course of an
outbreak, known as “situational awareness,” was a central topic of workshop
discussion, as noted below.
Animals
The practice of surveillance is not limited to human diseases. Some surveillance systems protect economically and ecologically important animal or plant
species; others are designed to detect transmission of a zoonotic disease among
animal and human populations over space and time, and to predict future transmission patterns.
Within the complex network of federal agencies that govern animal health,
separate—and in some cases, parallel—surveillance programs are conducted by
USDA, Department of Homeland Security (DHS), DoD, Department of Health
and Human Services (HHS), the Department of the Interior (DoI), and Department of Commerce (NRC, 2005). As noted in the recent National Research Council report, Animal Health at the Crossroads, “whether due to historic structures
or functions of . . . related federal, state, and local governments, or because of
changes and challenges in funding and resources, there is an apparent disconnect
between [animal health] agencies that should function in partnership” (NRC,
2005). A further element of disintegration is introduced through the practice of
disease-specific surveillance at both federal and state levels.
Technological advances in disease detection that have benefited public health
surveillance—such as rapid, automated, sensitive, and portable sampling and
assay systems and DNA-based diagnostic tools—remain to be adapted to track
animal diseases (NRC, 2005). Such tools could have significantly reduced the
severe burden of recent outbreaks such as exotic Newcastle disease (END) among
chickens in the United States and foot-and-mouth disease (FMD) among cattle
in the United Kingdom; a recent analysis supports the use of polymerase chain
reaction (PCR) to screen bulk milk for the FMD virus (Thurmond and Perez,
2006). Other early warning technologies with potential application to animal
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global infectious disease surveillance and detection
disease surveillance include embedded monitoring chips to measure temperature
and other physiological states, gene-based pathogen assays, and biosensors.
Plants
Plant disease surveillance occurs at several levels: through growers, who
monitor crops for signs of disease; at the local and regional levels, by private
crop consultants and USDA cooperative extension agents who diagnose disease
and provide advice to growers on outbreak management; at the national level,
through programs such as the National Plant Diagnostic Network (NPDN; see
subsequent discussion) and BioWatch; and at the international level through collaborative research organizations such as the Consultative Group on International
Agriculture Research (CGIAR) (Fletcher, 2005; Stack et al., 2006).
In recent years, a broad range of molecular techniques, including PCR-based
and immunological assays and DNA arrays, have been adapted to detect and track
the spread of plant pathogens (Alvarez, 2004; Schaad et al., 2003). Although
routine diagnosis of many crop diseases can now be made within a day by realtime PCR, there is further need to develop same-day, onsite protocols for identifying plant pathogens, as well as standardized procedures to validate diagnostic
protocols (Schaad et al., 2003). In theory, earlier detection of plant pathogens
could be achieved through the capture of molecular signals from pathogens in
situ; however, this and related technologies are likely to be first applied to detect
animal and human pathogens (Cook, 2005; Schaad et al., 2003).
Public Health Surveillance: A Local Perspective
The traditional model of infectious disease surveillance remains essential
to public health practice, particularly at the local level. Speaker Marci Layton,
of the New York City Department of Health and Mental Hygiene (DOHMH),
emphasized the importance of reports—of both routine and unusual findings—by
health-care providers to local health departments. The interpretation and investigation of such reports by DOHMH officials supports the identification and control
of infectious disease in one of the world’s largest and most cosmopolitan cities
(see Chapter 1 overview). These efforts have been boosted in recent years by the
introduction of electronic reporting for laboratory results and web-based reporting by health-care providers. An alert system has also been established to inform
area health-care providers of public health emergencies.
Because of the high risk for disease importation into New York City, DOHMH
officials stay abreast of international infectious disease trends, ramping up surveillance and alerting health-care providers in response to threatened outbreaks.
The city has also invested federal funding to improve the ability of hospital
triage systems to identify and appropriately treat patients who show symptoms
associated with an emerging infectious disease. This is crucial, Layton observed,
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SUMMARY AND ASSESSMENT
because New York City “could be the next Toronto, with an unrecognized SARS
outbreak from overseas.”
Syndromic Surveillance
Layton noted that many infectious disease threats (e.g., influenza, SARS,
and viral encephalitis, as well as potential bioterrorism agents such as anthrax
and smallpox) manifest as syndromes with nonspecific symptoms (“influenzalike symptoms”). In the case of a rapidly spreading, emerging infectious disease,
laboratory diagnosis may be impossible. Under these circumstances, she said,
syndromic surveillance systems can alert public health authorities to an outbreak
before it is revealed in reports from health-care providers.
Keynote speaker Patrick Kelley, director of the Institute of Medicine’s Board
on Global Health, and presenter Michael Stoto, of the Georgetown University’s
School of Nursing and Health Studies, reviewed the theoretical underpinnings
and historical development of syndromic surveillance (see Kelley, Stoto in
Chapter 1). When people first develop symptoms, following an exposure or
first contact with a novel or rapidly emerging infectious disease, they may be
much more likely to attempt to treat themselves and stay home from work or
school rather than seeking care from a health-care provider to obtain a clinical
or laboratory diagnosis (Stoto, 2005). Syndromic surveillance systems monitor
existing descriptive data of these behaviors (e.g., school and work absenteeism,
sales of over-the-counter medications, illness-related 911 calls, emergency room
admissions for symptoms indicative of infectious disease) for patterns or clusters of behaviors suggestive of an illness outbreak. The concept of syndromic
surveillance is doubly attractive because in addition to its potential to increase
the speed and effectiveness of the public health response to natural or deliberate
disease outbreaks, it costs far less to implement than traditional, labor-intensive
approaches to disease surveillance (Stoto, 2005). However, the ability of syndromic surveillance to reduce disease-related morbidity and mortality remains to
be demonstrated, as does its cost-effectiveness (Bravata et al., 2004; Reingold,
2003; RAND Corporation, 2004; Stoto, 2005; Sosin, 2003). Although rigorous
evaluations of syndromic surveillance in general may be impossible, individual
systems can be assessed under a variety of circumstances (Reingold, 2003).
Moreover, because syndromic surveillance systems are warning devices, it will
be critical to determine their utility within the context of health systems that
respond to both “true” and “false” alarms (Pavlin, 2003; RAND Corporation,
2004).
Global Syndromic Surveillance
In parts of the world where clinicians are in short supply, syndromic surveillance offers a promising model for disease detection, Kelley observed (see
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global infectious disease surveillance and detection
Chapter 1). Infectious disease is a major cause of morbidity and mortality in
low-resource populations, and such environments frequently provide amplifying
conditions for emerging pathogens. Recognition of this threat has spurred the
World Health Organization (WHO) to revise the International Health Regulations
(IHRs)—the legal framework for international cooperation on infectious disease
surveillance. Once limited to a trio of internationally notifiable diseases (plague,
cholera, and yellow fever), as of June 15, 2007, the revised IHRs became the
“world’s first legally binding agreement in the fight against public health emergencies of international concern” (WHO, 2007). Reporting of new and reemerging diseases with epidemic or pandemic potential, as well as diseases associated
with acute chemical or radionuclear events, will be mandatory regardless of their
origin or source (WHO, 2007).
“The mandate for general global public health surveillance is moving beyond
named diseases to encompass a global responsibility to detect and report in a
timely manner internationally important disease events, whether they are individual cases or clusters, whether they are well-defined diseases or ill-defined
diseases,” Kelley explained. Syndrome detection is central to this new paradigm,
and should be viewed as one of a collection of approaches to global surveillance
for infectious diseases, he said. However, he also noted considerable challenges
in moving syndromic surveillance from theory to practice.
Syndromic Surveillance by Design
Kelley emphasized that a key step in developing effective syndromic surveillance systems—and one that has frequently been overlooked—is the precise
definition of system capabilities. While considerable effort has been applied to
the development of syndromic definitions (e.g., for flu-like illnesses that may
indicate bioterrorism), far less attention has been paid to identifying robust
detectors of those conditions, he said. Moreover, rather than formulate clear and
specific questions and design systems to answer them, he observed that developers of syndromic surveillance systems have too often created systems based on
opportunistic datasets.
In addition to appropriate data to answer essential questions, a system for
public health surveillance requires powerful analytical tools, as well as technically proficient analysts to use them and accurately interpret the findings, Kelley
said. He added that these considerations are equally applicable to domestic
surveillance programs that, due to their complexity, might be fruitfully developed through academic partnerships with individual communities. Kelley also
advocated strengthening the epidemiological capacity at the local level in order
to inform the interpretation of syndromic findings in light of “local epidemi-
ological peculiarities,” as well as to ensure a rapid response to syndromic
alerts.
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SUMMARY AND ASSESSMENT
From Syndromic Surveillance to “Situational Awareness”
Syndromic surveillance systems are handicapped by their very nature. Not
only must they obtain relevant and accurate data quickly and from a variety of
sources, but they must also be tuned to recognize unusual trends against a highly
variable background; otherwise, syndromic surveillance systems may either miss
an important event or generate unacceptable levels of false positives (see contributions by Kelley, Stoto in Chapter 1). Indeed, Stoto explained, according to
the syndromic detection algorithm, it is impossible to increase the sensitivity,
specificity, or timeliness of syndromic detection without reducing the other two
attributes. This point is illustrated by a recent model of outbreak detection for
inhalational anthrax by Buckeridge and colleagues (2006), who concluded that
“when syndromic surveillance was sufficiently sensitive to detect a substantial
proportion of outbreaks before clinical case finding, it generated frequent false
alarms” (Buckeridge et al., 2006).
Stoto explored several additional examples of this dilemma, all of which
support his contention that traditional, statistics-based syndromic surveillance
systems are unsuited to the detection of rare, small-scale events such as a localized biological attack or the initial cases of a newly imported or emerging disease.
He suggested, rather, that syndromic surveillance was most likely to be valuable
in detecting potentially large-scale, natural disease outbreaks (e.g., seasonal and
pandemic influenza, foodborne disease) for which the useful “detection window”
is relatively broad.
Case-Finding by Syndrome
Instead of bypassing health-care providers, Stoto said that syndromic surveillance technology could be used to “arm astute physicians and health departments with modern approaches to finding small numbers of cases” and allow
health professionals to identify them before they are formally diagnosed. Such
“case-finding” surveillance systems currently in operation include the Syndromic
Reporting Information System (SYRIS) (ARES, 2007; Mandl et al., 2004; CDC,
2006b), Rapid Syndrome Validation Project (RSVP) (Zelicoff et al., 2001), and
Lightweight Epidemiological Advanced Detection Emergency Response System (LEADERS) (Green and Kaufman, 2002). Because case-finding syndromic
surveillance requires early reporting of symptoms, it can only succeed in “an
atmosphere that doesn’t penalize people for getting it wrong,” Stoto said (and,
as other participants noted, for getting it right, that is, for being the bearer of bad
news). Under enabling conditions, he said, case-finding syndromic surveillance
could build the kind of strong relationships between public health and health-care
providers that are critical to effective outbreak response.
“Like any alarm system, [syndromic surveillance is] only as good as what
happens when the bell rings,” Stoto concluded. “It must be followed with active
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10
global infectious disease surveillance and detection
surveillance and epidemiological investigation, and with policy decisions regarding intervention.” Speaker Joseph Lombardo, of the Johns Hopkins University
Applied Physics Laboratory, further advised that syndromic surveillance systems
be designed to meet the specific needs of epidemiologists and public health analysts. “The tools need to be built to support those individuals, and I believe public
health informatics has a tremendous role in doing that,” he said.
Situational Awareness
Several workshop participants described the use of syndromic surveillance
data beyond the mere detection of behavioral “signals” of an outbreak. Kelley
noted that syndromic data could support efforts to characterize infectious diseases, help target outbreak response, and inform risk communication. Lombardo
distinguished between syndromic surveillance, which he defined as an automated
detection and alarm system, and “situational awareness,” a term long used by
DoD that encompasses disease classification, tracking, response, and outcome
monitoring, in addition to detection. Viewed through the lens of situational
awareness, syndromic surveillance provides a rapid means to obtain descriptive
data throughout the course of an infectious disease outbreak. Epidemiologists
and others who monitor surveillance findings represent “the most important component of an advanced disease surveillance system,” Lombardo insisted. “They
cannot be replaced by statistics.”
Real-Time and Batched Reporting
In addition to collecting strategic data, well-designed public health surveillance systems incorporate appropriate mechanisms to process information and
deliver it to users. The computational performance of these tasks may occur
in “real time” or it may be “batched,” according to Lombardo, who explained
the implications of these descriptions for infectious disease surveillance (see
Chapter 1).
Real-time computing methods (presently used in video games and automotive safety systems) permit an immediate response to surveillance data, Lombardo
said. Batching may occur at any of several junctures along the path from data
collection to reporting, he explained; the term “batched reporting” may therefore
reflect the simultaneous collection of multiple data points, or the contemporaneous processing of data collected at different times, or the reporting, at regular
intervals, of the outcome of sequentially processed data. Batched health data may
be reported to users as soon as it is processed, at regular intervals, or accessed
on demand.
Breaking the electronic surveillance process into a series of steps, Lombardo
compared the potential and consequences for real-time and batched reporting.
Only certain syndromic surveillance data are available in real time, he noted.
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SUMMARY AND ASSESSMENT
11
For example, while cash registers transmit medication purchases immediately,
schools report absenteeism on a daily basis. Moreover, he observed, “the benefits
of real-time data collection are only realized if the other components of a surveillance system are real-time as well.”
Data may be continuously communicated for processing via a virtual private
network (used in some hospitals), or it may be sent by file transfer protocol as
batched files in intervals of seconds to hours. At the data processing step, the
distinction between real time and batched may not be meaningful if computation
is complex and therefore time consuming, Lombardo observed. For example, a
spatial analysis of disease phenomena across a series of ZIP codes could take a
long time to process; however, surveillance systems can allow analysts selectively to invoke certain processes in real time in order to monitor a potentially
urgent situation.
Surveillance reports can be delivered in real time, in the form of automatic
alerts, but Lombardo described considerable problems with this feature. As previously noted, many reports that are based on syndromic data represent false
positives and will therefore require an epidemiologist’s attention and expertise to
discern a true signal among considerable background noise. This can take time.
Unless surveillance reports are subject to continuous analysis, it makes no
sense to invest resources in providing them on a real-time basis, Lombardo concluded. “Getting information several times an hour should be more than adequate
for public health needs,” he said. To provide for public health emergencies, he
envisioned two modes of operation for advanced disease surveillance systems:
batched reporting for routine analysis, and real-time reporting, which would be
based on case definition and used for more focused surveillance during a crisis.
Animal Disease Surveillance
Two important factors contribute to the proliferation of zoonotic diseases:
the explosive growth of human and domestic animal populations, and the increasingly close physical proximity within which humans and domestic and wild
animals live (Karesh and Cook, 2005; NRC, 2005). Infectious diseases primarily
affecting animals can have both direct and indirect impacts on humans (Table
SA-1), including significant economic consequences (Figure SA-1). Therefore it
is widely acknowledged that the timely identification of future emerging microbial threats (on the order of SARS, West Nile virus, or H5N1 avian influenza)
will require an integrated international approach to disease surveillance. Progress
toward this goal has been hampered by a variety of economic and political factors, most notably the threat of trade embargoes against countries that voluntarily
report livestock or wildlife disease outbreaks.
Although they share comparable objectives, the U.S. animal health community lags far behind its public health counterpart in terms of surveillance
infrastructure and technology (NRC, 2005). These deficits were raised in several
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global infectious disease surveillance and detection
TABLE SA-1 Animal Diseases Associated with Direct and Indirect Human
Impacts
Infectious Disease
Affects
Wildlife
Brucellosis
Canine Parvovirus
Chagas
Distemper
Foot-and-mouth disease
Leishmania
Leptospirosis
Rabies
Scabies
Toxoplasmosis
X
X
X
X
X
X
X
X
X
X
Affects
Domestic
Animals
Affects
Humans
Directly
Affects
Humans
Indirectly
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SOURCE: WCS (2007).
workshop discussions, and particularly in comments from veterinary pathologist Tracey McNamara of the Wildlife Conservation Society (WCS). In 1999,
McNamara linked the presence of dead birds on the grounds of two New York
City zoos with the first human cases of West Nile encephalitis in the United
States. Thereafter, she led the effort to create a national surveillance network for
the disease involving more than 35 zoos (Watanabe, 2002). A far more comprehensive and integrated strategy is needed for the surveillance of zoonoses, McNamara said. She noted that there is no provision for veterinarians who routinely
diagnose infectious disease in zoo animals and wildlife to report unusual findings
or send samples to public health authorities for testing, as physicians are required
to do. “Zoos are the most overlooked long-term epidemiological monitoring stations in the United States and in the world today,” she concluded.
As part of their overall mission, WCS conducts routine surveillance for a
wide variety of infectious diseases in animals around the world, including the
20,000 residents of zoological parks in the New York City area. In his presentation, William Karesh, director of the Society’s Field Veterinary Program,
described ongoing programs to monitor two important zoonoses: Ebola virus and
avian influenza (see Karesh in Chapter 1).
Ebola Virus Surveillance in Central Africa
In a reversal of standard public health thinking, WCS views humans as a
worrisome source of diseases that infect great apes. To protect endangered gorillas in central Africa from the Ebola virus, WCS has supported human disease
surveillance among the underserved populations that live in close contact with
the gorillas by training local people in simple data collection, syndromic surveil-
Copyright © National Academy of Sciences. All rights reserved.
Copyright © National Academy of Sciences. All rights reserved.
1992
$10B
$20B
$30B
$40B
1993
1994
1995
1996
1997
1999
SA-1 Broadside
2001
2002
2003
2004
BSE, U.S.
$3.5B
Avian flu, Asia
U.S., Canada
$10B
BSE, Canada
$1.5B
BSE,
Japan Avian flu, EU
$500M
$1.5B
2000
Nipah,,Malaysia
$350-400M
Swine flu,
Netherlands
$2.3B
1998
Foot and Mouth
Taiwan, $5-8B
Lyme disease
U.S., $2.5B
BSE, UK
$10-13B
Foot and Mouth
UK
$30B
SARS
China, Hong Kong,
Singapore, Canada,…
$50B+
FIGURE SA-1 The economic impact of selected infectious diseases.
SOURCE: Karesh (2006). Reprinted with permission from Bio-era. Copyright 2007.
Estimated cost
$50B
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global infectious disease surveillance and detection
lance, and basic laboratory diagnosis. These efforts, which helped to identify the
link between human outbreaks of Ebola virus and the consumption of gorilla and
chimpanzee meat (Leroy et al., 2004), now enable community members to avoid
infection with the virus by providing early warning of outbreaks in animals. Current surveillance is also directed toward evaluating the effectiveness of human
Ebola vaccine candidates in wildlife.
In addition to their efforts on behalf of gorillas, WCS has sought to teach
people in central Africa how to avoid getting Ebola through basic hygiene measures such as hand washing and cooking meat thoroughly. These lessons have
afforded opportunities to improve overall food safety in communities, Karesh
observed.
Global Surveillance for Avian Influenza
Over the course of several years, WCS has worked with individual governments to conduct surveillance for avian influenza in wild birds. This typically
involves basic epidemiology and viral sample collection and characterization
(by CDC); in some instances, birds are tracked with radio transmitters. In Mongolia, such a program has provided a candidate virus for development of a
human influenza vaccine, Karesh said. More recently, these individual efforts
have been combined into the Global Avian Influenza Network for Surveillance
(GAINS). The program seeks to expand international surveillance for influenza
in wild birds and promote the dissemination of surveillance information to governments, international organizations, the private sector, and the public. With
support from USDA, the U.S. Agency for International Development (USAID),
and the Food and Agriculture Organization of the United Nations (FAO), GAINS
trains individuals and organizations to collect samples for analysis by a network
of diagnostic labs, the results of which are disseminated through a common,
open-access database. Participants in the program, which currently reaches 24
countries, include hunters, birdwatchers, and other members of the public, as
well as animal health professionals. Karesh acknowledged that GAINS raises
privacy concerns in the United States. (“Who wants to say they have a sick bird
on their property?”), but he also observed, “the rest of the world doesn’t seem to
have that problem.”
Indeed, as Karesh notes in Chapter 1, the early success of GAINS has led
to an expansion of the program to address a broader range of infectious diseases
and species. The Wildlife Global Animal Information Network for Surveillance
(Wildlife GAINS) aims to establish “a comprehensive worldwide wildlife health
surveillance system to enhance preparedness for and awareness of emerging
infectious diseases,” he reports.
See
http://www.gains.org.
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SUMMARY AND ASSESSMENT
15
Plant Disease Surveillance and Detection
While plant health programs address many of the same challenges (e.g.,
globalization, biosecurity) and use similar tools and approaches as their animal
and public health counterparts, the near impossibility of preventing the global
spread of plant pathogens orients surveillance and detection toward preparedness
for disease. Agricultural production in the United States is especially vulnerable
because it encompasses vast areas, observed speaker Jacqueline Fletcher of the
University of Oklahoma (see Fletcher and Stack in Chapter 1).
Considerable time often elapses between the introduction of an agricultural
pathogen and its detection; therefore, federal programs such as the aforementioned NPDN focus on the early detection of plant diseases to minimize economic
losses. Because it would be too expensive to eradicate the more than 50,000 plant
diseases currently in the United States, the typical strategy is to minimize the
economic impact of each disease, Fletcher explained. However, given sufficient
warning prior to the introduction of a new plant disease threat, researchers can
reduce the impact of disease by identifying chemical control measures or by
breeding resistant crop varieties.
National Plant Diagnostic Network
Early detection, aimed at reducing the economic impact of plant diseases, is
the central mission of NPDN, according to speaker James Stack of Kansas State
University (see Stack and Fletcher in Chapter 1). Created in 2002 by the U.S.
Secretary of Agriculture, NPDN links plant disease and pest diagnostic facilities
at land grant universities in order to provide rapid detection and accurate diagnosis of important plant pathogens and pests (Stack et al., 2006). These efforts
received further federal support in 2004, under a Homeland Security Presidential
Directive (HSPD-9), which “establishes a national policy to defend the agriculture and food system against terrorist attacks, major disasters, and other emergencies.” HSPD-9 mandates the development of a national agricultural biosecurity
initiative that would expand capacity for disease detection and diagnosis (White
House, 2004).
According to Stack, NPDN is currently pursuing a range of passive and
active disease surveillance strategies. These include sentinel surveillance for specific pathogens (e.g., soybean rust, introduced to the United States by hurricanes
in 2004); random surveys for plant disease conducted by specialists throughout
the country; strategic and bidirectional surveillance, which attempt to locate the
source of disease outbreaks; syndromic surveillance (also for soybean rust); and
biosensors (for toxin-producing pathogens in stored grains and seeds). While
mandatory reporting of high-consequence pathogens and pests has been instituted
in some circumstances, Stack noted that the considerable disincentives to do so
probably lead to high rates of noncompliance.
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global infectious disease surveillance and detection
NPDN has also undertaken several projects intended to maximize the productivity of shrinking numbers of plant scientists trained in diagnosing disease,
Stack said. These include the creation of a curriculum to teach agricultural
workers to recognize signs of important plant diseases, and the development of
diagnostic databases and a “telemedicine” system that links state agricultural labs
to diagnostic experts.
National Center for Plant Biosecurity
Fletcher discussed a proposal for a comprehensive National Center for Plant
Biosecurity that has been endorsed by a broad coalition of scientific societies with
a common interest in crop protection. It is envisioned that the center, modeled on
CDC, would coordinate plant disease information at the national level and collect and disseminate knowledge on plant-disease management and agricultural
biosecurity. The center’s mission would be fundamentally different from that of
USDA, which is driven by the needs of agribusiness and focused on near-term
profitability, Stack explained. “We need another group that can step back from
that and look at our plant-based systems from a strategic standpoint,” he said.
Although the threat of agricultural bioterrorism provided the impetus for
proposing the center’s creation, Fletcher said, its benefits would be substantial in
the absence of such crises. This is particularly true because former USDA functions, such as the Animal and Plant Health Inspection Service (APHIS) and the
Plum Island Animal Disease Center, were subsumed by DHS, Stack observed.
That move has diminished attention to the specific missions of these agencies,
which represent “a first pair of eyes for what is coming into the country,” he said.
“If they don’t know what they are looking for, then that’s wasted time.”
Surveillance Networks
In traditional public health surveillance (based on reports from medical
practitioners, as described in the previous section), information travels up or
down the public health hierarchy, from the local to the international level and
vice versa. According to Forum member Stephen Morse, this seemingly orderly
scenario tends to produce surveillance that is patchy and erratic due to differing
priorities at various levels of the public health system, and information that is
too often focused on “diseases of the moment.” By contrast, electronic network
surveillance systems have the potential to recognize any outbreak, including that
of an emerging or otherwise unexpected disease, on a global scale.
The presentations and discussions summarized below demonstrate the power
of electronic networks to collect and integrate information on infectious disease
from a variety of sources and the ability of networks to disseminate such intelligence widely and rapidly to the user community. Participants also noted several
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SUMMARY AND ASSESSMENT
limitations of disease surveillance networks and—much as they had done for
syndromic surveillance systems—urged the creation of network surveillance
technologies that address specific public health needs and strengthen connections
between “astute clinicians” and public health practitioners.
ProMED-Mail
The first disease surveillance network, ProMED-mail (PMM), began in 1994
as a project of the Federation of American Scientists’ Program for Monitoring
Emerging Diseases (ProMED) (Madoff and Woodall, 2005). Morse, a founding
member of both ProMED and PMM, recounted that the network was initially
intended to enhance communication between working group members; however,
the listserv’s potential as an outbreak reporting system was quickly recognized
and expanded (see Morse in Chapter 2). Now sponsored by the International
Society for Infectious Diseases, PMM is a free, nonprofit, noncommercial, moderated e-mail list that serves in excess of 37,000 subscribers in more than 150
countries, as well as anyone with access to the website.
As illustrated in Figure SA-2, traditional public health reporting follows a
linear “bottom-up” process, beginning with an ill person presenting to a local
doctor, where they may receive medical tests. If the doctor or laboratorian finds
evidence of a “reportable” disease, or merely something unusual, he or she
reports the discovery to local health officials. If the apparent threat is severe, local
health officials report it to the national ministry or department of health, which
forwards the report to international health organizations (“world bodies”) if the
case is of global concern.
Figure SA-3 depicts the nonhierarchical ProMED network, which fosters the
exchange of information on reported diseases among a variety of sources.
In addition to volunteer “rapporteurs,” who provide information on possible
infectious disease outbreaks specific to their geographic area, PMM receives
information from subscribers (who may report firsthand or from other sources)
and from staff-conducted searches of the Internet, media, and various official and
unofficial websites (Madoff, 2004). Moderators assess these reports for plausibility (via established rumor verification protocols and private query to experts), edit
them as necessary, and often add comments or context before posting. Furthermore, because PMM aggregates reports from various locations, it can reveal the
geographical extent of an outbreak. Morse noted that this system has resulted in
several emerging disease reporting “firsts,” including outbreaks of Ebola virus in
Zaire (1995), West Nile virus in the United States (1999), SARS in China (2002),
and H5N1 avian influenza in Indonesia (2003).
See
http://www.promedmail.org.
Copyright © National Academy of Sciences. All rights reserved.
Public
Public
Copyright © National Academy of Sciences. All rights reserved.
Public
Practitioners
Local officials
FIGURE SA-2 Traditional public health reporting.
SOURCE: Figure courtesy of Dr. Larry Madoff.
Labs
Practitioners
Practitioners
Local officials
Ministry of Health
Type Title Here
SA-2 Broadside
Labs
Public
Practitioners
Public
Practitioners
Public
Practitioners
Local officials
Ministry of Health
Type Title Here
Local officials
World bodies: UN, WHO, FAO, OIE
Type Title Here
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SUMMARY AND ASSESSMENT
Ministries of Health
WHO
Media
Health-care workers
Laboratories
Lay public
Local health officials
FIGURE SA-3 The power of the ProMED surveillance network.
SOURCE: Figure courtesy of Dr. Larry Madoff.
Global Outbreak Alert and Response Network
SA-3
To connect the growing number of surveillance networks that followed
PMM in terms of capacity for infectious disease diagnosis and response, WHO
established the Global Outbreak Alert and Response Network (GOARN) in
2000. Conceived as a “network of networks,” GOARN pools human and technical resources from more than 100 institutions around the world (WHO, 2005)
in order to rapidly identify, confirm, and respond to outbreaks of international
importance. In 2002, after receiving worrisome reports from the Global Public
Health Intelligence Network (GPHIN; see below) and the U.S. Global Emerging
Infection Surveillance and Response System (GEIS), GOARN initiated the global
response to an outbreak of a disease that would be named SARS (IOM, 2004;
Heymann and Rodier, 2004).
The Global Public Health Intelligence Network (GPHIN)
Harnessing the power of automated Internet searching for disease surveillance, GPHIN scans thousands of websites in eight languages—including those
identified by two “news aggregators,” who monitor thousands of news sources in
dozens of languages—for early signs of infectious disease outbreaks in humans,
animals, and plants, as well as for chemical incidents and disease threats associated with natural disasters (Mykhalovskiy and Weir, 2006). Abla Mawudeku,
manager of GPHIN within the Public Health Agency of Canada, described the
network’s creation by that agency in partnership with WHO in 1998, its operation
and ongoing development, and its possible future as part of a planned open-access
See
http://www.who.int/csr/outbreaknetwork/en/.
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global infectious disease surveillance and detection
surveillance program under the auspices of a yet-to-be-named nongovernmental
organization (see Mawudeku et al. in Chapter 2).
After a scoring system sorts some 2,000 articles retrieved by GPHIN daily,
a team of multilingual, multidisciplinary, and multicultural analysts review those
articles deemed most relevant, Mawudeku explained. Several analysts work in
staggered shifts to provide round-the-clock coverage. Upon receiving a report of
concern, they follow a decision tree, based on IHR criteria (which may lead analysts to corroborate reports with other surveillance networks, such as ProMEDmail), to determine whether to post an alert. GPHIN does not systematically
validate the information it posts, but relies on WHO to verify outbreak alerts
through its country contacts (Mykhalovskiy and Weir, 2006). Figure SA-4 shows
the source of initial reporting of events of potential public health concern by
WHO in 2001–2002.
Subscribers to GPHIN receive alerts by e-mail or when they log on to the
system’s website. In addition to WHO and Canadian governmental agencies
(e.g., food inspection, defense, police), GPHIN’s audience includes ministries
of health and departments of agriculture from several nations, as well as FAO,
the World Organization for Animal Health (OIE), and the North Atlantic Treaty
Organization (NATO). Depending on the services provided, GPHIN subscriptions
(which in part reflect the expense of subscribing to news aggregators) cost 30,000
to 200,000 Canadian dollars per year, according to Mawudeku (Public Health
Agency of Canada, 2007).
To continue to improve its service, GPHIN has begun to evaluate its own effectiveness. Criteria are based on the number of users; the timeliness, sensitivity, and specificity of alerts; the stability of the system in terms of limited downtime; and the flexibility
of the system in terms of accommodating new technologies and in modifying search
criteria to gather information on a situation of interest, Mawudeku said. The cost of
operating and upgrading the system is a continual challenge, she observed, as well as
a barrier to use by low-resource countries and agencies. However, recent events may
portend a change in this situation. Having received the Technology, Entertainment and
Design (TED) prize in 2006, epidemiologist Larry Brilliant (who played a key role in
WHO’s campaign to eliminate smallpox, and who currently serves as Google’s chief
of philanthropy) is currently marshalling an effort by the influential TED community
to expand and enhance the GPHIN model (Zetter, 2006; Google, 2006; Hempel, 2006).
With GPHIN as a starting point, Brilliant hopes to create a freely available, internationally independent system for the early detection of infectious disease outbreaks.
Due to potential conflicts of interest with the Canadian government, GPHIN’s
staff cannot participate in the negotiations to make this service independent,
Mawudeku explained. “I can’t tell you what will happen to the GPHIN system,
whether we will continue to be within the [Public Health Agency of Canada] or
not,” she said, adding that Google’s attention to GPHIN had at least prompted
Office
International des Epizooties.
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SUMMARY AND ASSESSMENT
Organization
Verified
Not verified
GPHIN
MOH
News Media
NGO
Other Org.
Personal Com.
UN Org.
WHO
WHO Country Off.
WHO Regional Off.
0
50
100
150
Number of events
200
FIGURE SA-4 Source of initial reporting of potential events of public health concern by
WHO between January 1, 2001, and December 31, 2002. Legend: Global Public Health
Intelligence Network (GPHIN); Ministry of Health (MOH); Nongovernmental Organization (NGO); United Nations (UN); World Health Organization (WHO).
SOURCE: Mawudeku et al. (2002).
SA-4
recognition that the network would benefit from greater financial support than the
Canadian government currently provides. It would also satisfy the concerns of
Forum member Gerald Keusch, who observed that government-operated sources
of surveillance information raise “serious issues of credibility.”
HealthMap
HealthMap,
a freely available, web-based surveillance network operating since September 2006, provides a global view of infectious disease outbreaks as reported by the WHO, PMM, Google News,10 and Eurosurveillance.11
John Brownstein, of the Children’s Hospital Informatics Program, Harvard–
See
http://www.HealthMap.org.
http://www.who.int/csr/don/en/.
10 See http://news.google.com/news?hl=en&ned=us&ie=UTF-8&scoring=d&q=intitle:outbreak +
-satire+-%22press+release%22+-%22Communiqués+de+presse%22.
11 Eurosurveillance, a free and open-access multiformat journal, publishes peer-reviewed information
on communicable diseases from a European perspective. In March 2007, Eurosurveillance became
the independent scientific in-house journal of the European Centre for Disease Control and Prevention
(ECDC) in Stockholm, Sweden. For more information, see http://www.eurosurveillance.org.
See
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global infectious disease surveillance and detection
Massachusetts Institute of Technology (MIT) Division of Health Sciences and
Technology, and the Harvard Medical School Center for Medical Bioinformatics,
described the design of the system and efforts to evaluate its data sources (see
Brownstein et al. in Chapter 2).
There is an abundance of open-source electronic surveillance networks for
infectious disease, Brownstein said, but none provide a truly global perspective
due to gaps in geographic or population coverage and expertise. HealthMap
attempts to bridge these gaps by aggregating and integrating information from
several surveillance networks to produce a graphic, continually updated model
of global disease outbreaks over space and time. Alerts are displayed on a
global map that can be viewed at a wide range of resolutions and they are
linked to source sites that provide news of the outbreak and information on
the disease.
Recognizing the tradeoffs between alert sensitivity and specificity,
HealthMap’s creators are conducting an ongoing evaluation of their data sources
with respect to these criteria (see Brownstein et al. in Chapter 2). Brownstein
reported that, based on their first two months’ of data, PMM provided slightly
greater timeliness and better coverage of rare infections as compared with Google
News. On the other hand, he noted, news feeds provide a larger volume of data,
making them more useful for describing the temporal and spatial distribution of
large-scale seasonal infections (Figure SA-5). Brownstein believes “there is a real
value in integrating these data sources . . . to get a much better picture of a global
state of infectious diseases.”
HealthMap’s creators plan to expand their data sources to include CDC,
the private sector, laboratories, the military, and blog searches. They also plan
to incorporate information on animal infections and biotic and abiotic factors
that influence disease emergence and transmission, Brownstein said. In addition
to addressing reporting biases in current datasets, he noted that these additional
sources should support the assessment of population risk, disease severity, and
pathogen transmission within the HealthMap model. Data verification remains a
challenge, he added; with only two employees, HealthMap must rely on data that
have been validated by others—such as ProMED-mail reports.
Several participants recognized potential synergies between HealthMap
and GPHIN, with each network offering important elements (HealthMap’s
openness; GPHIN’s reach and verification capacity) of a long desired and
sought-after “system of systems” approach to infectious disease surveillance.
GPHIN’s current status within Health Canada and its reliance on commercial
news aggregation services would likely prohibit the network from supplying
data to HealthMap, Mawudeku explained; however, such collaboration could
be possible if GPHIN evolves into an open, nongovernmental network as envisioned by Brilliant.
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Report volume
SUMMARY AND ASSESSMENT
FIGURE SA-5 HealthMap alert volume by source. Google News: 899 (14.2 per day; 95
percent CI 11.8-17.2); ProMED: 257 (4.2 per day; 95 percent CI 3.5–4.7); World Health
Organization: 15.
SOURCE: Brownstein (2006).
The Voxiva Model for Resource-Constrained Environments
As several workshop participants observed, a global infectious disease surveillance system capable of early detectionSA-5
and response must identify outbreaks
where they most often arise: in the world’s most impoverished communities.
Many developing countries, however, lack adequate disease surveillance systems
capable of finding, diagnosing, and responding to diseases of global concern.
These countries must also detect and control outbreaks of common diseases,
such as measles, within their own borders. This is the void Voxiva12 attempts to
fill, according to speaker Pamela Johnson, the company’s cofounder (see Johnson
and Blazes in Chapter 2). Although projects have been launched to enable disease
reporting in low-resource settings via the Internet, personal digital assistants
(PDAs), and satellite dishes, she noted that none of these technologies directly
reached the inhabitants of remote communities at risk for infectious disease
outbreaks. By contrast, she reported that cellular phones have begun to connect
even the most isolated villages as their usage rate grows far faster than that of the
12 Founded in 2001, Voxiva aims to find practical ways of using information technology for health
and development in low-resource environments by creating innovative software that allows health
professionals to enter and access data using the Internet, a cell phone, and other devices. This new
capability makes early identification, treatment, and response possible for public health concerns.
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global infectious disease surveillance and detection
Internet. Figure SA-6 illustrates the rapid growth of cell phone usage in Africa
between 1994 and 2004.
Like other electronic surveillance networks, Voxiva is ultimately web-based,
Johnson said. The network receives input from a variety of sources, including cellular and fixed-line telephones, personal computers, PDAs, and paperbased communications to “optimize the use of existing infrastructure to create
multiple-channel, redundant systems” for data collection, she explained. Information is captured in a database that can then be shared with those who contribute
reports, along with tools for data analysis and visualization. Gaining access to
surveillance information and tools—in addition to acknowledgment for their
participation—gives inhabitants of outbreak communities a powerful incentive
for reporting, Johnson said.
Voxiva conducts both syndromic and traditional surveillance for human
disease in a variety of settings in Asia, Africa, South America, and the United
States, as well as systems to monitor animal health and adverse events. In Peru,
Voxiva created a system to replace the paper-based monitoring of illness among
members of its navy, a project described by David Blazes of the U.S. Naval
Medical Research Center in Lima (see Johnson and Blazes in Chapter 2). When
naval personnel or their family members present with disease symptoms at remote
clinics in the Amazon jungle, for example, nurses or physicians enter data via
cellular or toll-free public phones, or if necessary, relay it via radio to another site
with telephone access. The data are captured, displayed in real time on a private
web-based platform, and used to generate messages and alerts that feed back to
FIGURE SA-6 Telephone subscribers per 100 inhabitants, Africa 1995–2004.
SOURCE: Reproduced with the kind permission of the International Telecommunication
Union (2006).
SA-6 © National Academy of Sciences. All rights reserved.
Copyright
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SUMMARY AND ASSESSMENT
25
the reporting clinics. “The Peruvian Navy had no idea how many cases of any
disease were occurring over a period of time,” Blazes observed. “Just setting
baseline trends was very important.”
Like GPHIN, Blazes said that Voxiva has begun to evaluate its surveillance
systems, based on criteria such as simplicity, flexibility, stability, and sustainability, as defined by CDC (CDC, 2001). But Voxiva’s involvement in public health
extends well beyond surveillance, he noted: Their systems are linked to diagnosis
and response teams that can provide guidance or assistance in the event of an outbreak. In addition, Voxiva provides basic training in epidemiology and outbreak
management to its clients, using freely available, web-based curricula.13 All these
functions contribute to Voxiva’s overarching purpose, as defined by Johnson, to
use informatics to build and support networks of astute clinicians.
Considerations for Surveillance Networks
In response to these presentations, workshop participants raised a series of
general issues regarding the structure, function, and future of public health surveillance networks. Although the open-access PMM and HealthMap networks
are well established and poised to expand, some Forum members noted that
none of these networks features the sort of open editing made popular by the
free online encyclopedia Wikipedia.14 Brownstein said that HealthMap may add
a user editing function, but input would be limited to a group of experts. Keusch
pointed out that a similar “portal” model has been used to collect other types of
information; for example, to construct the Encyclopedia of Earth, a free, searchable collection of articles on earth science and ecology written by a diverse team
of experts who collaborate and review each other’s work.15 By contrast, Forum
member Gary Roselle expressed concern that HealthMap’s “beautiful maps of
data” derive from potentially erroneous newspapers and websites, and worse,
could be influenced to manipulate markets. In subsequent remarks, speaker Will
Hueston (see next section and Chapter 4) asserted that the maps would “set back
international development because it supports the idea that a country either has
the disease or doesn’t have the disease and the country either is at zero risk or
is at risk.” Furthermore, he predicted that the vast economic consequences (e.g.,
trade embargoes; decreased tourism and investment) of such labels would inhibit
disease reporting.
Regarding limitations in network access, one Forum member wondered how
public response to the SARS pandemic might have changed had GPHIN been
13 To
date Voxiva has trained more than 1,300 epidemiologists on the basics of outbreak management. Their objectives and curricula are in Spanish and English and are freely available on the
Web. For more information about the training provided by Voxiva, see http://www.nmrcd.med.navy.
mil/outbreak/.
14 See http://www.wikipedia.org.
15 See http://www.digitaluniverse.net/portal/earth/.
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global infectious disease surveillance and detection
freely accessible. Mawudeku speculated that the release of unverified information might have created unnecessary panic, and she advised that such information be accompanied by qualifying commentary if it were provided in an open
version of GPHIN. Another barrier to network openness exists at the level of
data acquisition. Countries do not share surveillance data without government
approval, participants observed, and the IHRs do not presently impose sufficient
consequences to overcome economic barriers to reporting disease. This necessarily limits information available to surveillance networks, except perhaps Voxiva,
whose clients own their data and use the network’s information as they see fit. On
the other hand, Johnson pointed out, clients sufficiently interested in collecting
such data tend to have the greatest capacity to respond to an apparent outbreak.
Looking to the future, Forum member George Korch asked how surveillance
data accumulated by networks might be analyzed further to tease out underlying
factors and relationships, such as previously unknown societal or environmental
influences on disease transmission. To the extent that they occur at all, such analyses are currently conducted on an ad hoc basis; however, both Brownstein and
Mawudeku said their networks are discussing possibilities for deeper and more
detailed surveillance studies, which are likely to proceed as collaborations with
academia and research institutions. Brownstein also predicted that basic research
in Internet-based surveillance would benefit from the recent “explosion of work”
on syndromic surveillance systems; for example, by using previously developed
methods to characterize datasets and reveal their hidden biases.
Finally, participants observed that surveillance networks, like other advanced
technologies that have been integrated into the practice of public health, tend to
be driven by innovation rather than designed to solve important problems. They
urged greater involvement by the public health community in creating tools in
response to pressing public health challenges, and noted that the development of
a common lexicon by technologists and public health practitioners is crucial to
advancing their collaboration.
Detection and Diagnostics
Current microbial detection and identification methods include microbiological culture, nucleic acid-based techniques such as gene amplification via
PCR, and immunological (antibody-based) assays (Peruski and Peruski, 2003;
Fredricks and Relman, 1999; Tang et al., 1997). Each of these platforms offers
complementary advantages and disadvantages for infectious disease diagnosis:
• Microbiological culture, with staining and microscopy, is the most
widely used method for identifying pathogens, particularly in developing countries. Despite being slow and limited in sensitivity for some clinically relevant
microbes, culture often provides the best means to assess complex microbial
phenotypes, such as drug resistance.
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• PCR is a sensitive, specific, and rapid approach for identifying microbes,
including those that are nonviable or inactivated (Peruski and Peruski, 2003;
Gilbert, 2002). Hundreds of different microbe-specific nucleic acid amplification tests have been described, but only a few such tests are routinely used in a
clinical setting to detect pathogens that include N. gonorrheae, C. trachomatis,
herpes simplex virus, and HIV (Fredricks and Relman, 1999; Tang et al., 1997).
PCR methods may also be used to detect drug resistance in pathogens (Fluit et
al., 2001), but the diversity of genotypes and mechanisms associated with this
phenotype, and the difficulty of predicting expression from simple gene detection, have hampered the universal adoption of this approach. Real-time quantitative PCR, which permits sample processing in minutes, powers environmental
detection systems for infectious diseases and biological warfare agents, as well
as innovative point-of-care diagnostic tests (Ivnitski et al., 2003; Peruski and
Peruski, 2003; Raja et al., 2005).
• Immunoassays are usually less sensitive and specific than culture and
PCR (Peruski and Peruski, 2003). Solid-phase, “hand-held” immunoassays for
specific pathogens are rapid, rugged, and easy to use. However, their application
is generally limited to screening or confirming diagnoses.
Newer diagnostic platforms, still largely in development, include nucleic acid
microarrays (“labs on chips” containing hundreds to thousands of oligonucleotide
probes for signature sequences) and mass spectrometry techniques for sequence
analysis (Briese et al., 2005; Palacios et al., 2006; Palacios et al., 2007; Anthony
et al., 2001). These technologies permit detection of a wide range of known
disease-causing organisms (not limited to microbes) and can often distinguish
new pathogen species, strains, and genotypes. Additional innovations include
methods for the simultaneous identification of complex mixtures of organisms
(Ecker et al., 2005; Hofstadler et al., 2005). Potential applications of such multiplexed detection technologies include the characterization of polymicrobial
infections common in epidemics of respiratory disease, and the creation of “universal biosensors” to permit the simultaneous identification of a broad range of
infectious agents in an environmental or clinical sample.
The Diagnostic Landscape
Workshop presentations on infectious disease detection and diagnostics followed a metaphorical road as they surveyed the immediate landscape of capacity, needs, and challenges; anticipated developments around the next turn; and
imagined a far horizon of disease diagnosis prior to the appearance of symptoms.
In the course of this journey, participants examined a variety of approaches to
infectious disease detection and diagnosis and raised significant considerations
for continued development of this field.
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global infectious disease surveillance and detection
Developing Countries
While threats posed by emerging diseases, pandemic influenza, and bioterrorism underscored workshop discussion, Mark Perkins of the Foundation for
Innovative New Diagnostics (FIND) reminded participants of the severe burden presently imposed on the developing world by infectious diseases such as
tuberculosis (TB) and malaria (see Perkins and Small in Chapter 3). Culture and
microscopy are often the only diagnostic technologies available in developing
countries, typically through a small number of facilities that cannot begin to meet
national needs. This not only hinders treatment for infectious disease in developing countries, he noted, but surveillance as well. Perkins reported that half of
the 22 countries with the highest burden of disease from TB have three or fewer
laboratories that can perform drug-susceptibility testing, a key component of TB
treatment and control; similar barriers also deter the detection and treatment of
trypanosomaisis and malaria.
Developing countries’ needs for rapid, accurate, inexpensive, and robust
diagnostics could be met by recent advances in genomics, proteomics, and materials science, but for the lack of a profitable market for such developments,
Perkins observed. FIND therefore guides the development and adoption of novel
diagnostic products for diseases of the developing world in much the same way as
public–private partnerships have been established to produce drugs and vaccines
for low-resource settings (Perkins and Small, 2006). With FIND’s support, companies that produce low-cost diagnostics for use in developing countries realize
sufficient cost savings (in manufacturing, approval procedures, and marketing)
to sustain profits. “So far it has been a very successful model,” Perkins reported.
“We have about 18 different technologies in the pipeline.”
Diagnostics for TB figure prominently among the Foundation’s current projects. Perkins described a liquid culture system for TB that reduces detection time
by several weeks; a phage replication assay and an automated detection system,
both capable of detecting rifampicin-resistant TB in sputum (signaling a patient
that will fail standard therapy); and an easy-to-use PCR diagnostic system that
can be performed in clinics without laboratory support. He cautioned that many
substandard rapid tests for TB (as well as other diseases, including malaria) have
already appeared on the market. “Small companies, the kinds of companies that are
making these tests, are not going to invest in going back to the genome and figuring
out what the right targets are,” he observed. Nevertheless, Perkins concluded, “Our
belief at FIND is that if you make the right technology, people will use it.”
On the Battlefield
Much like public health workers in developing countries, soldiers at risk
of contracting infectious diseases, either from the natural environment or from
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bioweapons, need diagnostics that are rugged, rapid, and easy to use. According
to speaker Mark Wolcott of the Diagnostic Systems Division at the U.S. Army
Medical Research Institute of Infectious Diseases (USAMRIID), diagnostic
assays must satisfy additional criteria for use in battle. Accuracy is paramount,
and tests must recognize a broad range of potential pathogens, he explained.
“Negatives are problems,” he said, “and false negatives [which may result from a
bioengineered pathogen] are of greater concern than false positives.” The military
currently relies on a combination of PCR tests, immunoassays, and traditional
microbiology to diagnose infectious diseases in the field, while pursuing a strategy to develop comprehensive diagnostic tools.
Animal Diseases
Recognizing the advantages of DNA-based diagnostic tools, Alex Ardans and
colleagues have developed PCR-based assays to screen for pathogens associated
with exotic Newcastle disease (END) in poultry and foot-and-mouth disease
(FMD) in cattle (Crossley et al., 2005; Heller, 2006; Thurmond and Perez, 2006).
Ardans, who directs the California Animal Health and Food Safety Laboratory
System, also described how the discovery of TB among cattle in several of the
state’s large dairies led to the development of a highly efficient testing program.
Although the state laboratory system spearheads surveillance for several
important animal diseases (including zoonoses such as avian influenza, bovine
spongiform encephalopathy, and West Nile encephalitis), Ardans suggested that
its most crucial role is in recognizing unusual disease events. He noted, for
example, that while END was “no stranger” to rural California, a recent outbreak
in an urban setting—among fighting cocks, whose handlers worked in and spread
the disease to commercial operations—took the state by surprise. The laboratory
responded by optimizing an existing real-time PCR assay for END that was used
to perform more than 85,000 tests (Crossley et al., 2005). “These emergency
efforts are a real opportunity to develop some new knowledge,” Ardans said.
“They are unique in what they will give us, and it’s a rare opportunity to improve
the diagnostics. [How else] would you get a chance to validate an assay using
85,000 samples?”
Such situations, Ardans observed, also highlight the importance of meeting
diagnostic needs with appropriate technologies. In pursuing the source of E. coli
O157:H7 in a recent outbreak in spinach, laboratory researchers discovered that
the use of a gauze swab to sample irrigation waters for contaminants performed
better than newer concentration technologies. (As previously noted, surveillance
for infectious plant diseases depends largely on available methods of disease
detection and diagnosis; see also Chapter 1.)
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global infectious disease surveillance and detection
The Road Ahead: Diagnostics in Development
Inspired in part by the image of the original Star Trek’s character “Bones” ®
diagnosing a patient with a wave of his medical tricorder (Figure SA-7), Wolcott
and fellow DoD researchers are attempting to construct an “integrated diagnostic
system” for field use that can detect viruses, bacteria, toxins, “and anything else
that could possibly be thrown at us in the biological detection arena,” he said.
The current prototype relies on automated real-time PCR, but DoD researchers
are testing a wide range of diagnostic technologies (e.g., microarrays, handheld
immunoassays, electrochemiluminescence) and targets (e.g., microbial toxins, as
well as nucleic acids), according to Wolcott. “We have to have multiple platforms
to give us the assurance that what we are reporting up the chain of command is
actually there,” he said. The ultimate goal is to combine multiple platforms into a
single, universal system for field diagnosis. While the time constraints and primitive conditions of battle present significant barriers to the use of microarrays,
Wolcott speculated that chip technology eventually would be adapted to provide
point-of-care diagnosis for soldiers in action.
FIGURE SA-7 Star Trek medical tricorder.16
SOURCE: Printed with permission from CBS Paramount.
16 The
medical tricorder was a palm-sized, handheld, device used by doctors in the Star Trek universe of the 23rd and 24th centuries to help diagnose diseases and collect bodily information about a
patient. The device scanned a living patient, interpreted and displayed the data obtained from the scan
to the user, and recorded the data to isolinear chips (Wikipedia contributors, 2007).
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Following a similar technological progression from PCR to microarrays, the
Pandora’s Box Project, based at Columbia University’s Greene Infectious Disease Laboratory, employs a staged strategy for molecular pathogen surveillance
and discovery (see Lipkin and Briese in Chapter 3) (Palacios et al., 2007). As
described by speaker and Greene Laboratory director W. Ian Lipkin, the first stage
consists of MassTag PCR, a technique that attaches reporter “tags” of distinct
masses to the amplified sequences, permitting the simultaneous, highly sensitive detection of more than 20 different pathogens. This platform, which is both
inexpensive (at approximately $10 per 20-plex assay) and rapid, has been used
to distinguish among various viral hemorrhagic fevers, Lipkin said; it is currently
being adapted for the diagnosis of gastroenteritis. MassTag PCR has also enabled
the recent discovery of a virus responsible for a significant proportion of flu-like
respiratory disease (Lamson et al., 2006).
A second stage of diagnosis becomes necessary when the first stage fails,
or when a larger number of sequences must be screened, Lipkin continued. For
this purpose, the researchers first designed a pair of extensive microarrays, called
GreeneChips, for viruses and other respiratory pathogens, and then a panmicrobial array that incorporates more than 29,000 60-mer probes from filamentous
fungi and yeasts, and parasites, as well as from viruses and bacteria that infect
vertebrates (Palacios et al., 2007). Together, these arrays comprise a system for
assaying nucleic acids extracted from clinical samples (e.g., nasopharyngeal
aspirates, blood, urine) or cell culture. If the less expensive ($100 per assay)
respiratory or viral arrays fail to detect a pathogen, he explained, “then we go to
progressively more comprehensive chips that top out at approximately $350.”
“These are surveillance tools,” Lipkin said of both MassTag PCR and
GreeneChips. “All they do is give you a plus/minus, presence-or-absence, sort of
an answer, if they give you an answer at all. You ultimately have to come back
to surveillance assays [such as] quantitation, with real-time PCR, [and] you have
to do serology.” More importantly, he observed, because diagnosis requires the
integration of various test results with other information, such as epidemiological data, the GreeneChip “is never really going to replace a seasoned, thoughtful
clinician.”
Lipkin also noted that, despite the obvious advantages of multiplexed detection (and in anticipation of less expensive versions of microarrays), the widespread adoption of microarrays for disease detection would require a revision
in regulatory standards based on the more sensitive single-agent model. “The
gold standard, invariably, is single-agent [detection] with an identical match
between template and probe as opposed to multiplex systems, which tolerate
sequence divergence,” he explained. The need to obtain intellectual property
licenses for each of potentially thousands of sequences restricts the development
of array-based diagnostics, Lipkin added. However, both regulatory and intellectual property barriers could be minimized by constructing multiplex assays of
20 or so carefully chosen sequences, according to Forum member Patrick Fitch,
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of Battelle Memorial Institute. “Defining the problem space goes a long way to
getting optimization of the assay you want,” he concluded.
GreeneChips are tools for discovery, as well as for diagnosis. Because as
many as 100 different regions of a genome may be represented on the chip, assays
reveal enough sequence information to enable the rapid sequencing of novel
pathogens, several of which have been characterized. Analyses of GreenChip data
have led to the identification of a novel target for antiviral drugs, which Lipkin
described as an “on/off switch in the human immune system.” He predicted that
broad, unbiased pathogen-detection methods will continue to provoke unanticipated discoveries and enable researchers to explore the apparent link between
infectious and chronic diseases.
The Far Horizon: Presymptomatic Diagnosis
Imagining a future in which bioterrorism agents are continually reengineered
to evade standard detection and diagnostic methods, as well as therapeutics,
speaker and Forum member Stephen Johnston proposed a model of diagnosis
for exposure to a pathogen prior to the appearance of symptoms (see Johnston
in Chapter 3). In this situation, he argued, specific defenses against threat agents
(e.g., vaccines) will be useless. Instead, he envisions the creation of platforms
for defense against the full range of potential bioweapons, such as the means to
recognize and respond to the earliest possible signs of infectious disease in individual patients. Host-based, presymptomatic diagnosis could be accomplished by
monitoring a person’s blood serum chemistry for changes suggestive of compromised health status, Johnston explained; he is currently involved in developing
a device to perform such analyses. He noted that the noninvasive sampling of
breath and saliva is attractive in theory, but that neither of these sources offered
the diversity or concentration of metabolic components found in blood.
Monitoring the biological signatures of infectious disease will require making thousands to millions of simultaneous measurements and comparing them
to well-established baselines, Johnston said. Ideally, this would occur through
a continuous process. Therefore the monitoring device would need to be easily accessible (e.g., in the home), robust, inexpensive, and capable of quickly
measuring thousands of variables—specifications that also apply to point-of-care
devices for low-resource settings. Because the symptoms of respiratory viruses
appear in as little as one day, Johnston hypothesized that presymptomatic detection would need to register changes in the nanomolar-to-picomolar range and
would require clear baselines and the integration of multiple measurements to
avoid an unacceptable level of false positives. In response, Forum member David
Relman of Stanford University referred to an article by Kohane and colleagues
(2006), who describe substantive risks inherent in the practice of personalized,
genomic medicine, among them the imprudence of using “testing panels comprising a sizeable fraction of the genome for clinical care or screening” (Kohane et
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al., 2006). Johnston acknowledged that scant evidence—most of it derived from
early postinfection transcription patterns—suggests such measurements could
actually anticipate the development of respiratory symptoms. He attributed this
dearth of supporting data to the lack of funding for research in this area and to
the yet-unsolved problem of what, exactly, to measure, and how. Johnston and
coworkers are currently attempting to develop synthetic antibody techniques for
monitoring infection-related changes in protein levels.
In addition to offering the best chance of treatment for known, emerging,
or bioengineered pathogens, detecting infectious disease at the earliest possible
moment would permit diagnosis-based triage and increase the effectiveness of
quarantine or other social distancing measures, Johnston predicted. He anticipated that presymptomatic diagnosis will have an even greater impact on everyday medical care. “We have a healthcare system that can’t be sustained in terms
of physical economy,” he said, adding that care for ill patients accounts for nearly
90 percent of health-care spending. “Why does it cost so much? Because we are
diagnosing sick people, taking care of sick people; we even develop our drugs
for sick people.” Therefore, he insisted, our society has no choice but to move
from postsymptomatic to presymptomatic diagnosis.
Considerations for Detection and Diagnosis
Given the considerable interdependence of surveillance, detection, and diagnostic activities as they relate to infectious disease, it is not surprising that key
challenges identified by workshop participants in their discussions of surveillance
strategies would resurface as they explored current and future prospects for disease detection and diagnosis. Once again, participants stressed the importance of
selecting and acquiring clinically relevant samples or specimens, the establishment of said relevance against a background of natural variation, and the need
for standards to guide system design and evaluation.
Workshop participants also considered the status of infectious disease
diagnostics, which they characterized as a largely unsupported area within the
crowded field of medical diagnostics. Fitch observed that pharmaceutical companies tend to develop relatively low-margin diagnostic tests only when they can
be linked to highly profitable therapeutics (e.g., for cardiac disease and cancer).
Nevertheless, participants urged that the vast experience of commercial producers
of medical diagnostics be brought to bear on public efforts to develop applications for infectious diseases. For example, Relman suggested that industry could
participate in efforts to identify and evaluate common principles and platforms
for sample processing, signal generation and detection, and data analysis. However, he added, these considerations are contingent on a more fundamental set
of yet-to-be-determined specifications for any surveillance or detection program:
the exact set of questions to be answered and the appropriate setting in which to
ask them.
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global infectious disease surveillance and detection
The Challenge of Coordination
Workshop participants, having considered a broad range of tools and strategies for infectious disease surveillance, detection, and diagnosis, turned to the
difficult issue of effectively combining them. Hueston, director of the University
of Minnesota’s Center for Animal Health and Food Safety, launched this discussion with his presentation on the coordination of disease surveillance, detection,
diagnostics, and reporting. This topic is a frequent focus of Hueston’s work,
which emphasizes risk communication and the facilitation of public–private
partnerships (see Chapter 4).
Shifting the Public Health Paradigm
Certain powerful concepts and conditions that influence the practice of public health inhibit the coordination of infectious disease surveillance, detection,
and diagnosis, according to Hueston. Table SA-2 summarizes these elements of
the current public health paradigm, as defined by Hueston, and pairs them with
his proposed alternatives.
Hueston identified several factors driving the current paradigm that specifically undermine public health coordination. Chief among them is high health
TABLE SA-2 Current Public Health Paradigm and Alternative World View
Current Paradigm
Alternative World View
Health focus is individual; benefits
accrue primarily to the developed world
Health focus is global society; benefits accrue to all
Health is absence of disease
Health is well-being (in mind, body, spirit)
Infectious disease is all about the agent
Infectious disease emerges at the convergence of agent,
host, environment
Zero risk is achievable
Zero risk is unachievable; risk management is the goal
Success is eradication/cure
Success is homeostasis with microbes that are
ubiquitous, constantly evolving, and adapting
Public health function is to react
Public health function is health promotion
Reaction requires agent detection
Risk management can be successful whether or not
microbe is identified
Urgency dictates priority
Surveillance informs policy and guides action on basis
of importance
Answers lie solely in technology
Answers involve people, politics, partners
SOURCE: Hueston (2006).
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status in the United States, which reinforces the tendency of public health to
focus on the urgent (i.e., the disease or agent du jour) rather than the important
(i.e., emergency preparedness); this situation is exacerbated by a budget process
that takes money from “important” programs to fund “urgent” ones. Parochialism
influences our sense of urgency, he observed, causing us “to focus on those things
about which we are most interested in the United States as opposed to looking at
the true [global] public health priorities.” Hueston added that assigning blame for
public health threats—and especially the tendency to “shoot the messengers” who
identify them—suppresses essential collaboration in surveillance. For example,
before the United States adopted a policy of “zero tolerance” for food contamination, companies monitored for more pathogens and kept records of their findings,
a practice that supported scientific evaluation of the impact of new intervention
strategies. Now, he said, “if they monitor and get positive reports, they are culpable and have self-incriminated, so they stopped monitoring.”
Coordinating the spectrum of public health activities associated with disease
surveillance and detection is an inherently political task, and therefore strongly
influenced by societal and organizational culture, Hueston asserted. “To be effective in politics over the long term and to build coordination and collaboration
requires people skills,” he observed, and yet increasingly in educational fields
relevant to public health, considerations of interpersonal and executive skills are
largely ignored under the misguided assumption that science and technology can
replace them. Rather, as Korch noted in the ensuing discussion, in a risk management model of public health, understanding and responding to specific social
contexts is crucial to effective risk reduction and communication.
There is no “magic bullet to change paradigms,” Hueston stated, stressing
that steady progress can be made through small successes. This progress, albeit
slow, needs to be properly recognized and celebrated. Because the most effective engine for change is educating the next generation of leaders early in their
careers, he urged educators to encourage greater global and transdisciplinary
awareness in future public health professionals.
Optimal Surveillance for Risk Management
Clearing the way for true coordination and collaboration would enable optimal surveillance, as Hueston defined it: an integrated and dynamic system with
ongoing data collection and real-time analysis to inform risk management, and
thereby drive policy and action, with a feedback process to facilitate continuous
evolution and adaptation. Information would be drawn from a broad range of
disciplines relevant to physical and mental health, as well as domestic and wild
animal health and plant health, through the complementary processes of agent
surveillance and host and environmental monitoring.
In the discussion that followed his presentation, Hueston noted the potential
economic benefits of surveillance systems for both developing and industrial-
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ized countries, but also warned that too much openness could undermine such
systems. “If our goal is to promote public health, and surveillance precipitates
action to control the disease, do we always have to make the information public?”
he wondered aloud. Forum member Johnston responded emphatically that such
secrecy “has only gotten us in trouble, that it is elitist and that it is only going
to come back and bite us in the long run. If we want to foster a further schism
between the public and the scientific community, the best thing we can do for that
is to withhold information.” Hueston responded that he agreed with Johnston’s
position in principle, but insisted that under some circumstances, the unintended
consequences of publicizing information outweighs the potential benefits, such
as sharing of animal disease surveillance data in wildlife that precipitates unwarranted trade restrictions on commercially produced products. He concluded that
the release of surveillance information should be evaluated on a case-by-case
basis. Forum member Margaret Hamburg noted that timing is crucial to such
communication and observed that public health officials “get into trouble if we
provide information before we fully understand it and before we understand how
we are going to respond.”
Because the definition of risk is individual and fueled by emotion, public
health professionals must address the perception of risk, Hueston explained. Trust
is not built merely by sharing data, but by helping people understand information
by providing it in context, he said. But, he continued, this is only the first stage.
The public must then be actively engaged to discuss their perception of risk and
identify priorities for action.
Needs and Opportunities
This section recounts needs and opportunities for both research and policy
derived from workshop discussions on infectious disease surveillance, detection,
and diagnosis. Participants, including members of a concluding discussion panel
(see Chapter 4 overview), identified a series of issues critical to the development and implementation of effective methods and strategies for the detection
of infectious disease and described key challenges in responding to increasingly
early disease alerts.
Critical Issues in Infectious Disease Surveillance and Detection
The following areas were the subject of extended discussion with reference
to both surveillance and detection.
System Design and Development
Hueston captured a recurring theme in this workshop’s discussion when
he quoted management guru Stephen Covey’s advice to “begin with the end in
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mind” (Covey, 1989). As previously noted, many decried the evolution of surveillance and detection systems based on available technologies and databases,
rather than in response to well-defined public health needs. Participants suggested
the following actions to improve the design and development of surveillance and
detection systems:
• Develop a common design lexicon to improve communication and collaboration between public health practitioners and information technologists.
• Devise methods to analyze surveillance data through time in order to
understand factors and mechanisms that underlie apparent trends.
• Create syndromic surveillance systems that can adapt to signals as they
are received so that an increase in symptom prevalence prompts intensified
testing.
• Broaden the purview of surveillance to encompass social circumstances
that affect public health.
• Incorporate mechanisms to filter surveillance data to reduce false-positive
(and panic-inducing) alarms.
• Recognize and incorporate promising surveillance concepts from noninfectious disease applications.
• Support basic research in disease surveillance, especially among plant and
animal populations.
• Develop incentives to promote the development of infectious disease
diagnostics and to integrate academic and commercial efforts toward this goal.
• Consider models of infectious disease beyond the replication of viruses
or bacteria within organ systems. These would include toxin-producing microbes
(e.g., Clostridium botulinum) and pathogens that affect the immune system or
immune responses (including delayed or chronic effects, such as those associated
with hepatitis C and human immunodeficiency virus [HIV]).
• Do not overlook longstanding and effective elements of disease detection:
pathology, microbiology, and of course, the astute clinician.
System Evaluation
Workshop participants encouraged critical analysis, comparison, and evaluation of the performance of existing surveillance and detection systems, and in
particular, of the U.S. BioSense (syndromic surveillance) and BioWatch (specific
threat detection) programs. Their suggestions include the following:
• Identify the essential components of a global infectious disease surveillance system in order to prioritize funding.
• Support operational research to evaluate and optimize informatic systems for processing epidemiological data, particularly when used in syndromic
surveillance.
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global infectious disease surveillance and detection
• Develop methods to analyze and compare cost-effectiveness of surveillance and detection systems.
• Design mechanisms for continuous feedback and improvement into surveillance and detection systems.
• Reconsider the role of syndromic surveillance in disease control, given
the lack of evidence for its effectiveness in early detection of biological attacks
and its promise for tracking large-scale, natural disease outbreaks such as H5N1
avian influenza.
Integration of Information
Workshop participants also stressed the importance of integrating information on infectious diseases from diverse sources and methods to obtain a
comprehensive view of disease risk and severity. In particular, they encouraged
the development of mechanisms to connect local sources of surveillance data
(including information on animal infections, insect vector distributions, climate,
and vegetation) with global surveillance networks.
Information Transparency, Control, and Access
As noted in the previous section, workshop participants expressed divergent
opinions concerning the risks and benefits associated with the public disclosure of
surveillance findings. Most participants acknowledged a need to balance transparency—a foundation of both public and international trust—against the potential
consequences associated with public misinterpretation and overreaction. Several
participants urged consideration of political and economic factors, as well as
timing (i.e., releasing surveillance information by public health authorities only
after it is fully understood and a response is planned or underway), in making
such decisions.
Reporting
Recognizing that the reporting of unusual findings by health practitioners
(and subsequently by governments) is essential to infectious disease surveillance
and detection, workshop participants considered a range of incentives to promote
the affirmative reporting of human, animal, and plant health status at all levels,
including the following:
• Develop and broadly implement standards for infectious disease reporting
and sample submission to public health laboratories.
• Pay clinicians, especially those in developing countries, to report findings
to national public health authorities.
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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SUMMARY AND ASSESSMENT
39
• Ensure the confidentiality of health practitioners who report infectious
disease, while recognizing their contribution to public health. In the case of agricultural diseases, provide financial support for farmers who report disease and
guard intellectual property rights of seed companies who assist in identifying
vulnerable germplasm.
Participants also suggested a variety of mechanisms and tools to improve the
collection and use of reported information, as follows:
• Fund the procurement, storage, submission, and diagnostic testing of clinical and animal specimens from a broad spectrum of private and public sources.
• Encourage data collection to support the characterization of natural variation and define baseline health status; reward the reporting of negative data.
WHO’s Health Metrics Network, a global partnership to build capacity and
expertise to provide better health information to decision makers at all levels,
represents a potential source of baseline data.17
• Support the development of global surveillance and laboratory capacity
as mandated by recent revisions to the IHRs. Some suggested that this could
be accomplished through increased funding to WHO; others argued that WHO
must first be reformed and strengthened; others questioned whether a new intergovernmental entity would need to be invented to achieve the goals set by the
IHRs.
• Support parallel efforts by OIE, NATO, USDA, and the European Union
to develop global surveillance capacity for animal and plant diseases.
From Alarm to Action
In the spirit of beginning with the end in mind, workshop participants also
considered the fate of information derived from infectious disease surveillance
and detection systems. Several participants observed that U.S. government investment in the detection of biological threats far outstrips its ability to respond to
such crises. Some decried the shortsightedness of creating global surveillance
networks for infectious disease without also providing for disease control and
containment, as well as for public preparedness and risk communication. As
Kelley acknowledged, far more than science will be required to help affected
communities accept the uncertainty that characterizes the course of an infectious
disease emergency and the ensuing public health response.
17 See
http://www.who.int/healthmetrics/about/whatishmn/en/print.html.
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global infectious disease surveillance and detection
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1
Surveillance Strategies
OVERVIEW
This chapter includes workshop presentations that illustrate a variety of goals,
approaches, and methodologies for disease surveillance in humans, animals, and
plants. As noted in the chapter’s first paper by keynote speaker Patrick Kelley,
director of the Institute of Medicine’s Board on Global Health, current concepts
of public health surveillance, inspired by approaches to military intelligence data
gathering, originated in the 1950s. Today, traditional surveillance practices of
disease reporting (by physicians, veterinarians, infection control practitioners,
laboratorians, and medical examiners), followed by epidemiological and laboratory investigation, constitute the mainstay of local infectious disease surveillance
where such expensive methods are feasible (mainly in developed countries).
However, a range of nontraditional strategies including syndromic surveillance
(the topic of Kelley’s paper, and another in this chapter by Michael Stoto) and
electronic surveillance (the subject of Chapter 2), may prove well suited to settings where clinicians, laboratories, and hospitals are in short supply.
Local Surveillance: New York City
Although New York City’s size, diversity, and significance to international
transportation create considerable opportunities for infectious outbreaks, local
approaches to surveillance resemble those of many communities around the
world, according to presenter Marci Layton of the New York City Department
of Health and Mental Hygiene (DOHMH). New York health codes mandate
disease reporting for more than 70 infectious diseases, ranging from common
45
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global infectious disease surveillance and detection
pathogens such as Salmonella to the potentially disastrous, such as smallpox
and anthrax. The health department receives reports by traditional phone, mail,
and fax and—following a significant recent investment—by electronic and webbased methods as well. Participation in an electronic clinical laboratory reporting
system, a secure network that allows DOHMH to receive laboratory-confirmed
diagnoses in a timely manner, is mandated for all laboratories that diagnose New
York City residents. This system enables DOHMH to spot citywide and neighborhood disease trends in routinely reported data that an individual physician would
not be able to recognize, Layton said.
Upon receiving a report, DOHMH initiates an investigation to examine risk
factors for infection in order to determine disease transmission routes, and, if
appropriate, to arrange prophylaxis. “The most important thing we try to do is to
make sure that every health care provider knows who and how to call to make a
report,” Layton said.
In the event of an apparent or actual public health emergency, New York
City’s health alert system quickly disseminates information to providers on the
nature of the emergency and instructions on preparing and delivering diagnostic
specimens. Because New York City is at high risk for receiving imported disease,
DOHMH stays attuned to global infectious disease issues via surveillance networks such as ProMED-mail (see Morse in Chapter 2) and responds to reports
of significant disease activity abroad by ramping up surveillance and alerting
health-care providers in New York City to look for signs of an outbreak. After an
outbreak of West Nile virus in 1999, and in light of increasing concern regarding the potential use of zoonotic diseases as bioterrorism agents, animal diseases
were made reportable in New York City in 2000.
DOHMH has invested considerable hospital-preparedness funding to improve
the ability of triage systems to recognize patients with significant risk factors for
infectious disease, particularly patients with fever and respiratory illness who
have traveled recently. This is crucial because, in Layton’s words, “New York
City could be the next Toronto, with an unrecognized imported outbreak of severe
acute respiratory syndrome (SARS)—or of bioterrorism, E. coli, or most worrisome of all, avian influenza.”
The realization that many unreported, hospitalized cases of viral encephalitis (a reportable disease) manifested during the West Nile virus outbreak caused
DOHMH to adopt procedures to monitor similar nonspecific clinical syndromes.
In 1998, the city began syndromic surveillance based on ambulance dispatch
data; the system was expanded to monitor the entire emergency department
in the wake of the 2001 World Trade Center attack, then further to monitor
pharmacy sales, employee health, school absenteeism, and primary care visits.
One of the most challenging aspects of responding to a syndromic signal is
getting specimens to a lab for diagnostic testing, Layton observed, particularly
specimens from the acutely ill patients typically seen in emergency departments.
Rapid diagnostic testing is performed for a variety of pathogens at a single New
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47
York City hospital, but only limited information is obtained from this proof-ofconcept project.
To better balance time spent investigating syndromic surveillance signals
versus outbreaks detected through traditional means, DOHMH is developing
a protocol to reduce time wasted on false positives while ensuring the prompt
investigation of real outbreaks. Syndromic surveillance systems have proven to
be most useful for monitoring citywide seasonal outbreaks of infectious diseases
(e.g., norovirus, influenza, respiratory syncytial virus [RSV]), Layton said, and
less useful for detecting localized outbreaks.
“In my view, syndromic surveillance will never replace traditional surveillance, which is where most surveillance resources should continue to be
invested,” she concluded. “The real public health challenge lies in creating the
necessary infrastructure to analyze surveillance data, set priorities, and conduct
investigations. I am concerned that increased investment in syndromic surveillance may occur at the expense of state and local public health infrastructure.
More generally, if current funding patterns continue, whereby national programs
addressing emerging infections and bioterrorism receive more and public health
at the state and local levels receive less, our ability to make use of surveillance
information will suffer.”
Toward Earlier Warning
Through the use of prediagnostic data, syndromic surveillance aims to provide timelier identification of disease outbreaks than can be attained through
traditional surveillance methods, Kelley writes. After reviewing the theoretical
underpinnings and historical development of syndromic surveillance, he discusses its potential applications in developing countries and its promise as a
vehicle for achieving global disease surveillance as mandated in recent revisions
of the International Health Regulations (IHRs). Unfortunately, “hasty, opportunistic implementations of syndromic surveillance,” including some U.S. projects,
“have not allowed the theoretical power of the method a fair test,” he observes.
In their stead, Kelley advocates the creation of surveillance systems, including
syndromic components, designed to answer clear and specific questions. He also
considers how syndromic surveillance could be applied to detect serious but lowfrequency threats such as bioterror attacks, SARS, or avian influenza in time to
contain their further spread.
Following Kelley’s paper, with its focus on the design of syndromic surveillance systems, Stoto’s essay considers their evaluation. He defines and applies a
framework for gauging the usefulness of syndromic surveillance in public health
practice, then uses it to identify a number of statistical and practical challenges
to using such surveillance for detecting bioterrorist events. By contrast, he finds
promise in using syndromic surveillance to detect natural disease outbreaks
(including seasonal and pandemic influenza), and in monitoring public health
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global infectious disease surveillance and detection
response to disease outbreaks. Realizing this potential will require designing
systems that focus on these uses rather than being optimized for timely detection
of large-scale bioterrorist attacks, Stoto concludes.
The next paper, by Joseph Lombardo of the Johns Hopkins Applied Physics
Laboratory, addresses another aspect of timeliness in surveillance: the implications of “real-time” versus “batch reporting” of surveillance information. Noting
that confusion has arisen around the use of these terms, Lombardo carefully
defines them and provides illustrative examples. He concludes by describing the
possible combination of both modes in surveillance systems that use efficient
“batched” surveillance processes for the routine monitoring of public health,
and more resource-intensive “real-time” processes to examine specific threats
as they arise.
Surveillance of Animal and Plant Diseases
Recognizing that “the health of people, animals, plants, and the environment
in which we all live are inextricably linked,” in the words of workshop presenter
William Karesh, surveillance must encompass far more than human diseases.
Karesh’s contribution to this chapter describes initial efforts toward this goal,
focusing on projects undertaken by his own organization, the Wildlife Conservation Society (WCS). He describes the threat spectrum, origins, risk factors, and
consequences of infectious disease in wild animals, and he observes that “the
immediate effects of the diseases themselves are often the least of the worries.
Infectious diseases of people and animals are drivers of poverty and associated
civil unrest, disrupt ‘free’ ecosystem services such as drinking water and plant
pollination, and can ruin otherwise well-planned and sustainable economic development efforts.”
In two papers that conclude the chapter, plant pathologists Jacqueline Fletcher
of Oklahoma State University and James Stack of Kansas State University define
threats (both natural and intentional) to U.S. crops and provide examples of
high-consequence plant diseases. The first paper outlines components of a strong
plant biosecurity strategy, discusses progress toward its achievement, and notes
opportunities for further improvement. In the second paper, the authors evaluate
each component of the biosecurity strategy (prevention, surveillance, detection,
diagnosis, response, and recovery) and suggest specific actions the United States
could take to support each area.
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SURVEILLANCE STRATEGIES
49
SYNDROMIC SURVEILLANCE:
MOVING FROM THEORY TO PRACTICE
Patrick W. Kelley, M.D., Dr.P.H.
The National Academies
Assessing the health of a community has similarities to assessing the health
of a person. A variety of detectors of ill health can be brought to bear in ways that
range from passive monitoring that depends on those affected to raise a concern
to active and aggressive monitoring of those apparently without complaint to
identify the earliest manifestations of a problem. The desire for earlier detection of acute health problems at either the individual or community level has in
recent years stimulated the search for better “detector” mechanisms. Syndromic
surveillance is one of these now in vogue as a solution to the growing challenge
of early disease detection in communities and management of consequent public
health interventions.
Though infectious disease reporting started in Europe and the United States
in the late 1800s, it was not until 1925 that all U.S. states participated in national
morbidity reporting. Only after Alex Langmuir went to the Centers for Disease
Control and Prevention (CDC) in 1950 did the term “surveillance” become conceptualized beyond the monitoring contacts of persons with contagious diseases.
At CDC Langmuir developed a concept of surveillance inspired by military
intelligence data gathering and incorporated the approach into daily public health
practice. Soon CDC had national systems for malaria, polio, and influenza. In
more recent times, advances in laboratory and mathematical methods and technologies have pushed horizons farther and stretched academic definitions. These
cutting-edge approaches to disease detection at the community level encompass
networks for surveillance using molecular fingerprinting and exciting, web-based
methods of information capture and assessment such as the Program for Monitoring Emerging Diseases (ProMED) and the Canadian-World Health Organization (WHO) Global Public Health Intelligence Network (GPHIN). In this
more demanding context, we now have the evolution of automated syndromic
surveillance.
The elaboration of more sophisticated approaches to surveillance has been
stimulated by the recognition over the past 30 years of at least 30 “new” emerging
infectious diseases. These encompass infections of plants, animals, and human
beings. Of course, an acute concern is the threat of bioterrorism but many naturally occurring emerging disease outbreaks have highlighted the need for rapid
detection and characterization. Perhaps the greatest concern now is the need to
promptly recognize the syndromic pattern of an H5N1 influenza outbreak, here
Director,
Board on Global Health and Director, Board on African Science Academy Development,
Institute of Medicine.
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global infectious disease surveillance and detection
or in remote parts of Asia or Africa, so that aggressive attempts to eliminate it
can be instituted before it becomes uncontainable. Similar urgency arose during the 2003 severe acute respiratory syndrome (SARS) epidemic. For some of
these emerging infections, it was months before an agent was isolated, and thus
timely and sensitive public health surveillance and response was syndromic to a
great degree. The tragedies of HIV in Africa and the slow recognition of SARS
in China are reminders of the consequences of slow responses and motivate the
question of what surveillance system designs could have made a difference. With
bioterrorism a rapid assessment and response is even more critical.
“Syndromic surveillance” is defined by CDC as the collection and analysis of
“health-related data that precede diagnosis and signal with sufficient probability
of a case or an outbreak to warrant further public health response” (CDC, 2006a).
This differs from more traditional surveillance in several ways but primarily the
objective is that by using prediagnostic data, syndromic surveillance aims to be
timelier in identifying emerging problems. The phenomena of emerging infections and all the associated aspects of globalization that accompany them, as
well as the specter of bioterrorism, drive the need to be more cognizant of public
health events and to act despite limited information. Timeliness is not the only
advantage of the method, though. An additional goal is that syndromic surveillance should be more sensitive at detecting aberrations in normal patterns because
it does not depend on confirmed diagnoses, something that can be an expensive
proposition, especially in developing countries.
Some advocates have great enthusiasm for transitioning syndromic surveillance from the epidemiologic laboratory into routine practice, but others are skeptical, preferring to put their confidence in traditional approaches and the “astute
clinicians” who have risen to the occasion so often in this country. Unfortunately,
while developed countries have a fair number of clinicians who are astute at
least much of the time, the developing world, where so many disease problems
emerge, is a different case. A system of complementary systems—including clinicians, traditional methods, and well-designed syndromic surveillance tailored to
the setting of a particular community—may ultimately yield the wide range of
perspectives needed to meet the demanding public health challenges of emerging
infections and globalization. The best mix of surveillance interventions will vary
from community to community. A challenge now is to do the operations research
to adapt academic surveillance concepts to unique community circumstances.
This is important not only in communities with strong health systems, but also
in developing countries, where nontraditional approaches may be more essential
and affordable than in places with a relative abundance of astute clinicians, laboratories, and hospitals, such as the United States.
Some observers seem frustrated by syndromic surveillance because it has
detected few outbreaks, as implemented in the United States over the past few
years. Many doubt that it will perform better than alternative mechanisms to alert
the public health community to a problem. Perhaps though hasty, opportunistic
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51
implementations of syndromic surveillance have not allowed the theoretical
power of the method a fair test. Also, the purposes of syndromic surveillance go
beyond earlier detection and provide situational awareness across a community,
something that individual clinicians can rarely provide. Though other mechanisms, to include astute clinicians, may help recognize a problem, an effective
surveillance system, syndromic or otherwise, should also rapidly characterize
a problem epidemiologically because this is essential to efficiently target what
are invariably limited response assets. A system should enable civic leaders to
establish the boundaries of the problem and allay some unjustified fears through
more credible risk communication.
In tabletop exercises of public health crises, the value of information for
management has been highlighted both as being in short supply and as being
something that a properly constructed syndromic surveillance system should
help develop. In one important biodefense tabletop simulation exercise, “Dark
Winter,” Frank Keating, former governor of Oklahoma, said:
You can’t respond and make decisions unless you have the crispest, most current, and best information. And that’s what strikes me as a civil leader . . . that
is . . . clearly missing (O’Toole et al., 2002).
Central to effective surveillance is beginning with a clear appreciation for the
capabilities sought. Precisely what phenomena need detection, in precisely what
populations is the detection needed, and what data would be most effective for
that purpose? Much work has been accomplished in developing syndromic definitions and analytic algorithms but before syndromic surveillance is seen as the
solution, the full range of scenarios that need to be detected must be considered
as well as how best to build epidemiologic “detectors” for demographically different communities in both rich and poor countries.
Although in the United States there is a tendency to associate syndromic
surveillance with the specter of bioterrorism, WHO has come to recognize that
the protection of global health against emerging infections was poorly served by
the last version of the International Health Regulations (IHRs), which mandated
reporting to WHO only three specific diseases: yellow fever, plague, and cholera.
Realizing that some of the most critical recent global public health threats—such
as AIDS, SARS, Ebola, pandemic influenza, and Nipah virus—initially were
ill-defined syndromes, a new version of the IHRs has been adopted by member
states and is set to go into effect in 2007. This document calls on countries to
maintain, at the local level, capabilities to detect and assess not only well-defined
diseases and established causes of death, but also to report any significant levels
of morbidity of potential international public health importance. So, the mandate
for general global public health surveillance is moving beyond defined diseases
to encompassing a global responsibility to detect and report, in a timely manner,
internationally important disease events whether they are well or ill defined and
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global infectious disease surveillance and detection
Percentage treated (per week)
whether they are individual cases or clusters. A capability for syndromic detection
seems central to the new paradigm, especially in countries that lack the resources
for extensive use of more specific approaches.
Although the term “syndromic surveillance” has only been in vogue for
about a decade and is thought to represent somewhat of a frontier in surveillance, the potential contributions of “prediagnostic surveillance” have been long
established. In tracking down the last cases of smallpox and polio in developing
countries, syndromic monitoring has been central. For decades, the military has
also used syndromic approaches to monitor unit health on deployments and in
training because it was the most cost-effective, rapid, and reliable way to monitor the health of the force, especially in austere conditions. The military often
operates in settings with limited laboratory support, but with a critical need to
detect health threats in a timely manner. For example, Figure 1-1 illustrates the
tracking of diarrheal syndromes in a U.S. Marine force during the first Gulf
War of 1990–1991. With regular syndromic tracking of morbidity seen in sick
call, outbreaks were routinely recognized quickly by competent epidemiologists
against normal background rates. Investigations were launched rapidly to contain
problems that could debilitate unit combat effectiveness.
In U.S. military basic training camps, where respiratory syndromes are
particularly devastating, for decades there has been well-developed, centrally
monitored syndromic surveillance for acute respiratory syndromes (Gray, 2005;
Gunzenhauser, 2003). Syndromic surveillance in the basic training setting has
been used routinely to guide the use of mass antibiotic prophylaxis to prevent outbreaks of rheumatic fever when syndromically associated thresholds are crossed.
Week
FIGURE 1-1 Syndromic surveillance of U.S. marines for treated diarrheal syndromes
during the lead-up to the Persian Gulf War, 1990–1991.
SOURCE: Hanson (2005).
1.1
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SURVEILLANCE STRATEGIES
All of these practical implementations of syndromic surveillance reflect
movement from theory and simple systems to complex systems. Moving from
theory to practice involves a larger context where pieces must be made to work
together and adapted to the locality.
Reflecting all the elements to be integrated, one might define a surveillance
system, as distinct from surveillance, as follows:
A system for public health surveillance is a group of integrated and qualityassured, cost-effective, and legally and professionally acceptable processes,
designed for the purpose of identifying in an ongoing, flexible, standardized,
timely, simple, sensitive, and predictive manner the emergence of meaningful epidemiologic phenomena and their specific associations. These processes
include human, laboratory, and informatics activities to skillfully manage information derived from an entire defined community (or a subgroup thereof that
is sufficiently representative and large) and to disseminate that information in a
timely and useful manner to those able to implement appropriate public health
interventions.
As shown in Figure 1-2, a surveillance system needs to be seen in the context in which it works and as reflecting a hierarchy of elements that depend on
each other. One needs a clear and specific idea of what questions the system
should address. Who should be under surveillance and for what are most critical. Developers of syndromic surveillance systems often start to conceptualize
Identification
of system parts
Theory
Research on
parts
Envisioning the
whole system
Research on
integrated parts
Small-scale
proof of concept
Adaptive
development
Recognizing the
question—What
needs to be
detected?
Scale--up and
systems integration
Evaluation and
improvement
FIGURE 1-2 Conceptual steps in development and implementation of a syndromic surveillance system in a community.
SOURCE: Kelley (2006).
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global infectious disease surveillance and detection
a system with opportunistically available data rather than a clear definition of
the range of scenarios that their surveillance system must be able to recognize
as priorities. Typical “opportunistic” data might be routinely collected for other
purposes during an emergency room consultation or from “convenient” sources
such as government clinics regardless of how well they sample the community
of interest. Opportunistic datasets are rarely the strongest cornerstone on which
to build and can handicap an otherwise rigorous implementation.
Different epidemiologic scenarios will affect populations in different ways.
Key though is that if one wants to detect any epidemiologic scenario, the population under surveillance should include the one likely affected. If space and time
separate these populations, as may be the case with the most easily available
“opportunistic” datasets, little signal will be generated. If demographic misclassification affects the description with respect to person, place, and time, associations may be missed. If one lets the surveillance question drive the development
of the database used, there is a better chance that the population under surveillance will generate a strong signal because it will include a substantial fraction of
those exposed. Resources should be invested into negotiating for and developing
data with the richest “veins of ore” rather than focusing it proportionately on the
mining of poorly conceived data sources with ever more complex analytic methods. An example of this became obvious in looking at convenient outpatient data
in the Department of Defense (DoD) Electronic Surveillance System for the Early
Notification of Community-based Epidemics (ESSENCE), developed in the late
1990s for use for surveillance in the National Capital Region.
Like syndromic surveillance systems, the datasets initially available to
ESSENCE routinely classified patients experiencing morbidity by the ZIP code
of residence. The problem is that one could reasonably assume that most exposures, natural or manmade, would occur away from home in places such as the
Pentagon, the Capitol, a sports venue, or the subway. As became evident in a
geographic analysis, the bulk of military health-care beneficiaries tracked through
ESSENCE did not live where many exposures would most likely occur, in the
District of Columbia, but rather had homes scattered over a hundred ZIP codes
throughout the region. This residence-based misclassification, stemming from the
use of “opportunistic data” easily at hand, would have greatly diluted syndromic
signals arising from exposures at the workplace. This misclassification produces
what might be termed the “donut-hole effect” (Figure 1-3).
As exposed persons migrate from a center city worksite of exposure, where
they might be classified most effectively as an “exposed” population, they disperse into the suburbs, where they blend with unexposed populations so completely that any signal is greatly damped out. Overcoming this depends on not
settling for datasets of convenience. Populations in which those under medical
surveillance have limited geographic mobility can help correct for the donuthole effect. Students at universities might be one example. Residents of nursing
homes and prisons may be other populations where there is less risk that place of
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SURVEILLANCE STRATEGIES
National Capital Area
Counts of military beneficiaries by ZIP
NCA
1-500
500-1,000
1,000-5,000
5,000-10,000
10,000-50,000
50,000+
FIGURE 1-3 The donut-hole effect.
SOURCE: Kelley (2006).
exposure and place of residence differ.
1-3Another setting is military basic training.
However, a limitation of many of these populations is that they may not be near
the locations where surveillance is most critically needed, making their ability to
serve as sentinels less than ideal.
With the DoD ESSENCE, some of the most impressive syndromic signals
have come from basic training outbreaks, where the exposed population lived and
worked in the same location. This meant there was no problem with the migration
phenomena causing people exposed in one place to be classified geographically
in another. The strength of the signal and its rapid detection was also greatly
facilitated by the ability to attribute morbidity to a well-defined denominator
population that included most cases. For populations on the move, if they work
in high-value targets such as centers of government, it may be a high-yield investment to develop a way to ensure that they can be classified by both their primary
residence and primary workplace.
In moving from syndromic surveillance theory to practice, the first step is
appreciating not what data are at hand, but what are the “who, what, and when”
questions that need to be answered. The most effective surveillance systems will
likely be systems of systems because the questions to be answered will reflect
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global infectious disease surveillance and detection
multiple scenarios, each of which presents a different challenge. The classic
incident is an exposure to a whole community. In the bioterrorism scenario, this
might be a regionwide aerosol plume, but many other scenarios may be even more
likely and successful. Potential exposure scenarios include the following:
• Regionwide aerosol plume
• Seeding of a focal or traveling population with contagious (suicidal) persons (e.g., smallpox)
• Contaminated food distribution (e.g., Salmonella spp., hepatitis, E. coli,
or bovine spongiform encephalopathy)
• Contaminated water supply (focal or general)
• Focused attack against high-value worksite or event (e.g., letters to
Congress)
• Generalized aerosol plume against high-value site
• Focused aerosol attack against general population (e.g., mass transit)
The classic image is of a region-wide aerosol plume that distributes kilograms of an agent upwind from a population center with the idea of causing tens
of thousands of deaths and incapacitations. This is perhaps the worst case, but
likely the easiest to detect because it could affect large numbers of people across
a wide geographic swath. Perhaps a more likely challenge for public health would
be the seeding of a focal or traveling population with an infectious agent, such
as SARS or pandemic influenza. Debate is needed on the question of how best
to apply syndromic surveillance methods to detect serious, but lower frequency,
events in time to contain their further spread. Beyond the astute clinician, who
may be an uncommon commodity especially in some developing countries, what
is the most sensitive mechanism to detect aberrancy at the population level when
only a handful of nondescript cases are initially involved, as might be the case
with an early human pandemic influenza scenario? Could the initial hands full
of cases of SARS in Viet Nam or China have been better contained if alerts had
been raised earlier and if communications to those who could have acted had been
more rapid? How could syndromic surveillance have been adapted to supplement
the astute clinician in the scenarios in Hanoi, Hong Kong, Singapore, or Toronto?
Does syndromic surveillance have a role in scenarios such as these or in identifying clusters of avian flu in Indonesia or Cambodia?
In considering rare but important low-frequency emergences of a new infectious disease, the example of West Nile further illustrates the fact that the questions asked of a surveillance system differ based on the agent and the scenario
to be detected. For West Nile encephalitis, tracking infrequent and not highly
unique human syndromes across a large general human population may not
be the most effective way to achieve the rapid recognition envisioned in the
new IHRs. Figure 1-4 shows the estimated sensitivity for West Nile virus by
different surveillance methods. A system of systems that includes animals that
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SURVEILLANCE STRATEGIES
Surveillance Method
Human cases
Disease activity
Veterinary cases
Mosquitoes
Sentinel hosts
Dead bird
Time
FIGURE 1-4 Estimated sensitivity for West Nile virus by different surveillance
methods.
SOURCE: CDC (2003).
1-4
manifest aberrations earlier in time would be preferable to waiting until larger
numbers of people develop encephalitis and are admitted to intensive care
units.
One of the more recent national public health concerns in the United States
has been the outbreak of E. coli O157:H7 associated with consumption of raw
spinach. Could a configuration of syndromic surveillance detect a focal or a dispersed outbreak from contaminated food? The E. coli outbreak involved a few
hundred cases across the country (Figure 1-5) (FDA, 2006). Would a focus on
unexplained hemolytic uremic syndrome be a way to complement the impressive
but slow molecular fingerprinting approaches that ultimately carried the day?
The molecular approaches to DNA fingerprinting for outbreak identification
were certainly valuable, but more than 10 days could easily pass between when
a patient develops symptoms and when a case is confirmed and linked with other
cases with the same fingerprint (Figure 1-6). Syndromic surveillance seeks to
narrow the gap.
Another important outbreak scenario to detect is the contaminated water
supply. The infamous Milwaukee cryptosporidiosis outbreak caused hundreds
of thousands of cases of diarrhea, but its nature was such that recognition of
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global infectious disease surveillance and detection
Cases
1-4
5-9
10-14
15>
199 Persons
3 Deaths
26 States
FIGURE 1-5 E. coli O157:H7 spinach-associated outbreak, 2006.
SOURCES: CDC (2006b) and Kelley (2006).
1-5
Patient eats
contaminated
food
Patient
becomes ill
Stool sample
collected
E. coli O157
identified
Public health lab
receives sample
Average time
from patient
becoming ill
to case
confirmation in
current spinach
E. coli outbreak
= 15 days
Cases confirmed
FIGURE 1-6 Time associated with confirming spinach-related illness.
SOURCE: CDC (2006c).
1-6
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59
cryptosporidiosis as the specific cause was quite delayed (MacKenzie et al.,
1994). Most sick people did not seek care. Labs were not testing for the agent
routinely, and many cases were just diagnosed as viral gastroenteritis. Could a
thoughtfully designed syndromic system of systems have led to more prompt
recognition and mitigation of the outbreak? The epidemiology of this significant
public health event should make operators of syndromic surveillance systems
consider how well their systems and the datasets used would pick up a problem
with a municipal water system. For example, this outbreak pointed out how small
a fraction of those affected may actually seek medical care (6.5 percent here),
much less go to an emergency room. How can the morbidity represented by these
individuals not be lost for surveillance purposes? Furthermore, as noted earlier,
many syndromic systems analyze data routinely by residential ZIP code, but how
many routinely group residences based on an appreciation for how water flows
through the municipal water distribution system in their city? In Milwaukee it
was clear that the map of the distribution system would have correlated powerfully with a pattern of attack. The sparing of special populations such as nursing
home residents was reminiscent of John Snow’s observations on the sparing of
the Whatney’s Brewery workers from the cholera outbreak in London in the late
19th century.
Another important scenario to think about is the focused attack against a
high-value site such as the 2001 anthrax letter attacks. Tragically in this attack a
number of people died, but some lives were probably saved by the action of the
hoped for astute clinician. Beyond the astute clinicians, however, what system
configuration would pick up those low-frequency cases that may reflect serious
morbidity as a harbinger of a more widespread exposure? Individual cases were
identified in emergency rooms in this attack. Some were not so quickly recognized and may have taken on a different characterization if appreciated in a larger
epidemiologic context rather than counting on an individual astute clinician to
sense a “big picture” beyond his field of vision. Perhaps rigorous surveillance of
intensive care units (ICUs) for epidemiologically unexpected admissions may be
a critical underdeveloped element of syndromic surveillance for problems such
as this anthrax episode and outbreaks of problems such as West Nile or SARS.
ICU surveillance may permit the time for more detailed epidemiologic characterization of epidemiologically suspect cases, that is, cases that are admitted with
no obvious predisposing reason. Pooling across a municipal region may allow
appreciation of patterns that no single astute clinician could be counted on to
detect, much the same way that unexplained death surveillance may be helpful,
if not too late.
Perhaps the most important scenario to detect is the “failed scenario.” We
know that the worst case scenario of a biological attack would not be easy for
most perpetrators, but that does not necessarily discourage them from trying.
Being able to detect a modest trial run outcome would be a much more useful capability than designing a system for a more obvious worst case scenario.
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global infectious disease surveillance and detection
The first generation of an avian influenza cluster would also be the best time
to appreciate a problem. A goal of surveillance systems should be to not only
detect the classic worst case attack early or the widespread deaths of chickens,
but also to detect what may more often be a botched attempt that falls far short
of the perpetrators’ hopes or the earliest generation avian flu outbreaks. The
unsuccessful 1993 attempts by Aum Shinrikyo to spray anthrax over the city of
Tokyo illustrate this point (Takahashi et al., 1994). Fortunately this incompetent
attempt did not cause a single case, but if it had, even one case could have been
valuable to recognize as a harbinger of future threats. Perhaps the complete
failure of this anthrax attempt caused Aum Shinrikyo to move on and use sarin
in the Tokyo subway. A lesson is that motivated enemies will keep trying and
could get better with practice. A comprehensive surveillance system should set
its sights on detecting a wide range of scenarios to include trial runs or largely
botched low-yield events that may indicate that more effective efforts are in the
offing.
A recent review of abstracts accepted for presentation at the October 2006
International Disease Surveillance Conference in Baltimore, Maryland, showed
that more states than not have started to explore syndromic approaches to disease
detection and management. In addition to the United States, seven foreign jurisdictions also came to the meeting to present systems for syndromic surveillance.
In comparing the datasets represented in systems described at the 2003 meeting
with the 2006 abstracts, implemented systems are still overwhelmingly focused
on emergency rooms and hospital diagnoses—81 percent in 2006 (Figure 1-7
and Table 1-1). Although these data sources are obviously relevant for many
scenarios mentioned and may be the most convenient, they are not necessarily
the answer to all challenges. Other populations and venues may lend themselves
to better classification with respect to person, place of exposure, and time. To get
the most power out of the analytical methodologies being developed, there may
be justification to put the focus on other datasets to illuminate different aspects
of the clinical continuum and work so they contain the most informative fields.
Each of these varied data sources in Table 1-2 may provide a unique perspective on a particular epidemiologic scenario, especially if public health practitioners help shape the characteristics of the data rather than just settling for what
data are readily available. If public health practitioners are on the alert for emerging infections, including bioterrorism, the aim should be to do more than detect
only large unexplained outbreaks, but also to have the ability to detect isolated,
unexpected cases with unusual age, gender, or occupational characteristics. The
need to do this is driven not only by American concerns over bioterrorism, but is
also reflected in visions of the new IHRs. If public health officials are to detect
and contain pandemic influenza, it is doubtful that they will be very successful if they fail to recognize emerging patterns until there is a large unexplained
outbreak.
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61
FIGURE 1-7 Locations of surveillance systems in abstracts for the 2006 International
Society for Disease Surveillance (ISDS) meeting. Countries represented include United
States, Canada, Netherlands, Taiwan, Hong Kong, France, Scotland, and Greece. States
represented include AZ, CA, CT, DC, 1.7
FL,color
GA, IN, LA, MA, MD, NC, ND, NH, NV, NY,
OH, PA, TX, UT, VA, VT.
SOURCE: Kelley (2006).
To summarize, as demonstrated by Figure 1-8, public health surveillance
begins with understanding the questions “who, what, and when” that need to be
asked, and then it seeks the most effective data sources.
A system for public health surveillance, which is what needs to be built in the
move from academic theory to practice, is built on that data foundation, but it also
needs a set of powerful analytic tools and skillful people to use them and interpret
the findings. The skill sets of local public health staff to interpret data of this type
need expansion. Because this is a complex science still under development, perhaps academic partnerships need to be sought for all serious adaptations of these
concepts to specific localities. Few approaches can be just “dropped in” without
an appreciation for local epidemiologic and demographic peculiarities. Perhaps
most in short supply are the resources to do something promptly to respond to
findings. Budgets for surveillance systems should be accompanied by budgets
for a serious response capability. Finally, the underlying population demographic
structures and exposure likelihoods of some localities may make syndromic surveillance a low-yield, cost-inefficient activity. This may not be the destination for
every community. Guidelines for where performance is expected to be lower are
needed as well as insights into where value is likely to be added.
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global infectious disease surveillance and detection
TABLE 1-1 Sources for Syndromic Surveillance, 2003 and 2006 Annual
Meeting Abstracts
2003
2006
Data Sources
# of
Abstracts
% of
Abstracts
# of
Abstracts
% of
Abstracts
Emergency departments
Hospital diagnosis
Office/clinic visits
Over-the-counter drugs
911/emergency medical service runs
Laboratory results
Nurse advice lines
Laboratory orders
School nurse records
Poison control center
Veterinary diagnosis
Health-care employee absenteeism
School absenteeism
School perception of an outbreak
Medical examiners
Thermometer sales
Evacuation shelter primary reports
Local/regional news sources
Web logs
Online obituaries
Medical center parking lot volume
29
7
13
5
6
2
4
1
—
5
3
—
7
1
2
—
—
—
—
1
1
48
12
22
8
10
3
7
2
—
8
5
—
12
2
3
—
—
—
—
2
2
38
17
11
7
6
5
3
1
1
1
1
1
1
—
—
1
1
1
1
—
—
56
25 ↑
16 ↓
10 ↑
9 ↓
7 ↑
4 ↓
1
1
1 ↓
1 ↓
1
1 ↓
—
—
1
1
1
1
—
—
SOURCES: Sosin and DeThomasis (2004) and Kelley (2006).
TABLE 1-2 Potential Sources of Data for Syndromic Surveillance
•
•
•
•
•
•
•
•
•
•
•
Emergency rooms
Over-the-counter drug sales of symptomatic therapies
School and/or work absenteeism
Nurse advice lines
Ambulatory clinics
Laboratory test requests (e.g., fecal ova and parasite)
Prescriptions
Emergency medical systems (911)
Hospital and intensive care unit surveillance for syndromes
Unexplained deaths
Wild and domesticated animal health
SOURCE: Kelley (2006).
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SURVEILLANCE STRATEGIES
Agent,
host,
scenario
A reasonable
question
Operations
research
Analytic
methods
The right
data
Person,
place,
time
Tools
Skills
Information
technologies
Training
ENABLERS
ACTIONS
Data capture
Armchair and
shoeleather
epidemiologic
interpretation
Staff and
infrastructure
Laws; policies;
standard operating
procedures;
Command, Control,
Communications,
Intelligence
Warning and
response
Roles, structures,
and systems
FIGURE 1-8 System requirements for public health surveillance.
SOURCE: Kelley (2006).
SYNDROMIC SURVEILLANCE
1-8 IN PUBLIC HEALTH PRACTICE
Michael A. Stoto, Ph.D.
Georgetown University
Heightened awareness of the risks of bioterrorism since 9/11, coupled with a
growing concern about naturally emerging and reemerging diseases such as West
Nile, severe acute respiratory syndrome (SARS), and pandemic influenza, have
led public health policy makers to realize the need for early warning systems and,
more generally, improved surveillance. The sooner health officials know about an
attack or a natural disease outbreak, for example, the sooner they can treat those
who have already been exposed to the pathogen to minimize the health consequences, vaccinate some or all of the population to prevent further infection, and
identify and isolate cases to prevent further transmission. In addition, improved
surveillance systems should allow for better “situational awareness” and thus help
to manage the response to public health emergencies.
School
of Nursing and Health Studies.
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global infectious disease surveillance and detection
Traditional public health surveillance approaches monitor disease using prespecified case definitions and employ manual data collection, human decision
making, and manual data entry. In contrast, newly developed syndromic surveillance systems employ sophisticated information technology (IT) and statistical
methods to gather, process, and analyze large amounts of data and display the
information for decision makers in a timely way. For example, syndromic surveillance systems assume that during an attack or a disease outbreak, people will
first develop symptoms, then stay home from work or school, attempt to self-treat
with over-the-counter products, and eventually see a physician with nonspecific
symptoms days before they are formally diagnosed and reported to the health
department. To identify such behaviors, syndromic surveillance systems regularly
monitor existing data for sudden changes or anomalies that might signal a disease outbreak. Syndromic surveillance systems have been developed to include
data on school and work absenteeism, sales of over-the-counter products, calls
to nurse hotlines, and counts of hospital emergency room (ER) admissions or
reports from primary physicians for certain symptoms or complaints (Mandl et
al., 2004).
Recognizing that the “ability to gather and analyze information quickly
and accurately would improve the nation’s ability to recognize natural disease
outbreaks, track emerging infections, identify intentional biological attacks, and
monitor disease trends,” the Institute of Medicine (IOM) recently called for more
research on syndromic surveillance and other “innovative systems of surveillance
that capitalize on advances in information technology.” However, because surveillance systems in the United States “remain fragmented and have not evolved
at the same rate as . . . electronic technological advances,” the IOM calls for these
systems to be “carefully evaluated for their usefulness in detection of infectious
disease epidemics, including their potential for detection of major biothreat
agents, their ability to monitor the spread of epidemics, and their cost effectiveness” before widespread implementation (IOM, 2003).
To address the issues identified by the IOM, this paper begins by describing
a framework for evaluating the usefulness of syndromic surveillance in public
health practice. Application of this framework to existing systems identifies a
number of statistical and practical concerns when syndromic surveillance is used
to detect bioterrorist events. The analysis suggests, however, that these systems
may be more useful in detecting natural disease outbreaks (including seasonal
and pandemic influenza) and in the public health response to known disease
outbreaks.
Evaluation of Syndromic Surveillance Systems’ Usefulness
Asking whether syndromic surveillance “works” or not is not particularly
helpful. Rather, just as clinicians need to know the performance characteristics
of screening and diagnostic tests, public health epidemiologists need to charac-
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65
terize the performance of syndromic surveillance detection systems in terms of
the kinds of events that can be detected as a function of the responsible antigen,
outbreak size, timing, and other characteristics. Thus, evaluation of syndromic
surveillance systems’ usefulness involves a number of dimensions.
Evaluations of data accuracy and use, for example, include studies of the
accuracy of electronic records that form the basis of the systems compared with
an independent source, the accuracy of use of standard codes, the accuracy of
data preprocessing, and similar issues. This aspect of evaluation also includes
studies of the appropriateness of methods and protocols for data analysis, data
display, monitoring, and reporting, as well as how these methods are applied and
how they lead to action.
Evaluations of system utility include studies of the costs and benefits of
day-to-day use of syndromic surveillance, relative to existing systems, to identify
communicable or reportable diseases, to increase situational awareness, or to
assist in investigation and management of a disease outbreak. These studies also
assess the costs and benefits to users of identifying and evaluating data anomalies
using the system, as well as flexibility, acceptability, and stability. Finally, evaluation studies characterize statistical properties such as sensitivity, false-positive
rates, and timeliness. As illustrated below, statistical evaluations can be based
on simulation studies and comparisons of syndromic surveillance findings with
known actual events.
Concerns About Syndromic Surveillance in Public Health Practice
Despite the generally recognized promise of syndromic surveillance systems,
there are many practical concerns about the use of these systems in state and
local public health practice. The possibility of earlier detection and more rapid
response to a bioterrorist event has tremendous intuitive appeal, but its success
depends on local health departments’ ability to respond effectively. When a syndromic surveillance system sounds an alarm, health departments typically wait a
day or two to see if the number of cases continues to remain high or if a similar
signal is found in other data sources. Doing so, of course, reduces both the timeliness and sensitivity of the original system. If the health department decides that
an epidemiological investigation is warranted, it may begin by identifying those
who are ill and talking to their physicians. If this does not resolve the matter,
additional tests must be ordered and clinical specimens gathered for laboratory
analysis. Health departments might also choose to initiate active surveillance by
contacting physicians to find out if they have seen similar cases.
The detection of a sudden increase in cases of influenza-like illness (ILI)—
the kind of condition that syndromic surveillance can detect—can mean many
things. It could mean a bioterrorist attack, but is more likely a natural occurrence,
perhaps even the beginning of the annual flu season. An increase in sales of flu
medication might simply mean that pharmacies are having a promotion. A surge
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global infectious disease surveillance and detection
in absenteeism could reflect natural causes, or even a period of particularly pleasant spring weather. Similar problems can occur when changes in local hospital
systems, or even in coding practices, can result in substantial changes that could
raise concern if they are not understood.
Additionally, a syndromic surveillance system that says only that “there have
been five excess cases of ILI at hospital X” is not of much use unless the five
cases can be identified and reported to health officials. For example, if there are
65 cases rather than the 60 expected, syndromic surveillance systems cannot say
which 5 are the “excess” ones, and all 65 must be investigated.
Like all alarm systems, syndromic surveillance detection algorithms have
intrinsic statistical tradeoffs. The most well known is between sensitivity, the
ability to detect an attack when it occurs, and the false-positive rate, the probability of sounding an alarm when in fact there is no attack. The costs of excessive false alarms are both monetary, in terms of resources needed to respond to
phantom events, and operational, as too many false events desensitize responders
to real events. Taking into account the different data types and multiple jurisdictions, thousands of syndromic surveillance systems soon will be running simultaneously in cities and counties throughout the United States. If 1,000 data streams
are being monitored, each with a 0.1 percent false-positive rate (which is very
low), there will be approximately one false alarm per day.
The timeliness of a surveillance system depends on the time it takes to generate and acquire data, analyze it, and take action (Buehler et al., 2003). Even when
the cause and route of exposure are known, the available control strategies—
quarantine of suspected cases, mass vaccination, and so on—are expensive and
controversial, and often their efficacy is unknown. Coupled with the confusion
that is likely during a terrorist attack or even a natural disease outbreak, deciding
what to do could take days to weeks.
With syndromic surveillance, an additional component is the time required
to accumulate enough evidence of an outbreak to trigger a detection algorithm.
To illustrate this point, Stoto and colleagues used a simulation approach to analyze ILI emergency department admissions data from a typical urban hospital. A
hypothetical number of extra cases spread over a number of days were added to
actual baseline data to mimic the pattern of a potential bioterror attack. Figure 1-9
(A and B) indicates the size and speed that outbreaks must attain before they are
detectable, according to four statistical detection algorithms. The solid bar represents an algorithm that uses only one day’s data. The other three detection algorithms, shown with shared bars, average cases over several days. These results
are sobering: Even with an excess of nine cases over two days (the first two days
of the “fast” outbreak), three times the daily average, there was only about a
50 percent chance that the alarm would go off. When 18 cases were spread over
nine days, chances were still no better than 50-50 that the alarm would sound by
the ninth day (Stoto et al., 2004).
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SURVEILLANCE STRATEGIES
A
100%
Probability
of detection
80%
60%
40%
20%
0%
1
2
3
Day of attack
B
60%
Probability
of detection
40%
20%
0%
1
2
3
4
5
6
7
8
9
Day of attack
FIGURE 1-9 Sensitivity of syndromic surveillance (probability of detection by day) for
influenza-like illness at a typical urban hospital emergency room using four detection algorithms, as indicated by shading pattern (see text). A) fast outbreak: 18 cases over three
days, B) slow outbreak: 18 extra cases over nine days.
SOURCE: Stoto et al. (2004). Reprinted with permission from Chance. Copyright 2004
by the American Statistical Association. All rights reserved.
1-9B
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global infectious disease surveillance and detection
Can Performance Be Improved?
Simulation studies such as the one summarized in Figure 1-9 (A and B)
has shown that unless a bioterrorism outlook is exceptionally large, syndromic
surveillance detection algorithms take days to be detected (Stoto et al., 2004;
Jackson et al., 2006; Buckeridge et al., 2006; Stoto et al., 2007). Results like this
naturally lead one to ask whether this performance can be improved. Indeed, there
are a number of approaches; however, although these approaches may lead to better performance for some outbreak types, they are less able to detect others.
Syndromes other than ILI, for example, might be more easily detected
because they are less common, but this only works if a terrorist—or nature—
chooses to use an agent that caused those symptoms. Systems can and typically
are set up to monitor eight or more separate sets of symptoms. Doing so increases
sensitivity simply because more conditions are monitored, but as discussed above,
increasing the number of syndromes monitored will also increase the number of
false positives.
Another possibility is to pool data over multiple data streams, perhaps from
all hospitals in a metropolitan area or state. A number of cities are currently doing
this. If this results in both the signal and the background increasing proportionally, it will result in a more effective system. If, however, there were 18 extra
cases of ILI in a city, but they all appeared at one hospital, this signal would be
lost in the noise of the entire city’s cases. Moreover, such an increase would be
clear without any sophisticated surveillance system. One can analyze the data for
the entire city and for each hospital individually, but with 10 separate analyses,
the number of false positives would also increase.
Finally, the data can be analyzed geographically. If there were 18 extra cases
of ILI in a city, and all lived in the same neighborhood, that would be more informative than 18 cases scattered throughout the city—it would suggest a biological
agent released in that area. This is only effective, however, for a geographically
focused bioattack, and would not work if terrorists chose to expose people in an
office building or at an airport. It is also less likely to detect seasonal or pandemic
influenza, which spreads rapidly before symptoms appear
Alternative Applications of Syndromic Surveillance
Since 9/11, the focus of syndromic surveillance efforts has been on early
detection of bioterrorist events. The most value, however, may ultimately come
from its use in the detection of natural disease outbreaks. More generally, if 21st
century syndromic surveillance means effective use of health information technology in identifying cases before they are formally diagnosed, it can supplement
traditional public health approaches and improve their effectiveness.
One potential use is in detecting influenza outbreaks. In an “ordinary” year,
influenza results in 36,000 or more deaths and more than 200,000 hospitalizations
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69
in the United States alone. In addition to this human toll, influenza-related costs
are more $10 billion a year. A pandemic, or worldwide outbreak of a new influenza virus, perhaps evolving from the H5N1 avian flu virus circulating in Asia,
could dwarf this impact by overwhelming our health and medical capabilities,
potentially resulting in hundreds of thousands of deaths, millions of hospitalizations, and hundreds of billions of dollars in direct and indirect costs. Syndromic
surveillance systems feature prominently in federal, state, and local plans to prepare the United States for pandemic flu (Homeland Security Council, 2005).
The Centers for Disease Control and Prevention (CDC) has a number of
influenza surveillance systems in place (CDC, 2007), yet they do not provide
population-based rates of incidence or prevalence rates on a national level because
many infected persons are asymptomatic or experience only mild illness and do
not seek medical care. Also, laboratory testing is not common and test results
become available late in the course of the illness. Epidemiological characteristics
of both seasonal and pandemic influenza, however, suggest that syndromic surveillance and other surveillance systems are likely to make an important contribution beyond the capabilities of existing surveillance systems, and thus enable a
more effective public health response. Simulation studies have shown that unless
a bioterrorism outlook is exceptionally large, syndromic surveillance detection
algorithms take days to be detected (Stoto et al., 2004; Jackson et al., 2006;
Buckeridge et al., 2006; Stoto et al., 2006). This time frame is longer than some
proponents of syndromic surveillance as a tool to detect bioterrorism suggest is
needed (Wagner et al., 2001). Compared to the current influenza surveillance
systems, however, a one-week lead time would provide valuable information, and
this is likely to be achievable for syndromic surveillance.
Furthermore, a number of studies have demonstrated the potential that syndromic surveillance of ILI offers at the national, state, and local levels. Sebastiani
and colleagues (2006) have shown that children and infants presenting to the
pediatric emergency department (ED) with respiratory syndromes are an early
indicator of impending influenza morbidity and mortality, sometimes by as much
as three weeks. Using data from New York City, Lu and colleagues (2006) have
shown that monitoring both outpatient and ED data can enhance detection of ILI
outbreaks. With similar data, Olson and colleagues (2005) note that age-stratified
analyses of ED visits for fever and respiratory complaints offer the potential
for more precise quantification of the burden of illness, earlier warning of the
arrival of epidemic influenza, and greater sensitivity for detecting the characteristic age shift of pandemic influenza. Comparing unspecified infection cases in
Washington, DC, hospitals using optimal detection algorithms to CDC’s sentinel
physician data for the South Atlantic states for four years in which there was a
discernable influenza outbreak, Stoto and colleagues (2007) found that in two of
those years, the DC syndromic surveillance based on hospital emergency room
data outperformed the other two systems, and in one year it flagged only two days
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global infectious disease surveillance and detection
after the CDC system. Given a built-in delay of about two weeks in the CDC
system, this is a substantial advantage.
In normal flu seasons, laboratory analysis to determine whether a case is
truly influenza, or to identify the viral strain, is rarely done. Testing, however, is
critical for identifying pandemic influenza, in which an antigenic shift results in
a new viral strain to which few people are immune by virtue of previous exposure. Syndromic surveillance of flu-like symptoms might trigger more laboratory
analysis than is typically done and in this way hasten the public health response.
In a normal flu season, Labus (2005) has reported that early identification of
the start of the influenza season using syndromic surveillance in Clark County,
Nevada, enabled the notification of the medical community. Physicians were
encouraged to submit specimens for culture, and the county health department
provided kits to help them do this, which allowed for rapid identification of
the major circulating strain. In 2003–2004 (a period with a marked increase of
early season influenza and deaths in children in other parts of the country) this
syndromic surveillance system allowed for better tracking, and provided data for
daily reports to decision makers and the media.
Because of their focus on the early detection of bioterrorist events, most
syndromic surveillance systems are designed to detect large increases in the
number of people with common symptoms such as ILI. As a result, they cannot
be expected to detect small numbers of cases, even if very unusual. One reason
is that in a small disease outbreak or the early stages of a larger one, each case
will be seen by only one physician. The natural tendency of physicians who see
only one case, however suspicious it may be, is to discount it. After all, physicians are appropriately taught “when you hear hoofbeats, think horse, not zebra.”
Some may fear the embarrassment of reporting a case that may turn out to be a
false alarm.
Modern health informatics systems provide the potential to identify the presence of small numbers of cases of concern before they are formally diagnosed.
For example, automated systems can aggregate data for a metropolitan area, spanning local reporting jurisdictions, to identify, say, cases of rash and fever, which
would suggest smallpox. Systems can also be set up to enable and encourage early
reporting of cases based on symptoms only. For example, the Syndrome Reporting Information System (SYRIS) system, now operating in Lubbock, Texas, and
elsewhere, enables physicians to report suspicious cases to the local health department without waiting for laboratory confirmation, and encourages them to do so
by providing feedback in the form of information about practice guidelines and
other similar cases (Lindley and Ward, 2007). This can be thought of as a kind of
“active syndromic surveillance” or as IT support for astute physicians.
Real-time access to prediagnostic data can also help health authorities
respond to public health threats. If person-to-person transmission of avian flu
virus is documented in Asia, for example, health departments in Europe and the
United States might want to identify and follow up on local cases of people hos-
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SURVEILLANCE STRATEGIES
71
pitalized with flu-like symptoms, and syndromic surveillance systems could be
designed to identify them. If an environmental sensor detects signs of the terrorist
agent tularemia, syndromic surveillance systems can be checked for cases with
appropriate symptoms. This actually occurred in Washington, DC in 2005, and
the lack of cases in area emergency rooms reassured local officials that the alarm
was false. Syndromic surveillance systems can also be queried to determine background rates when it is not clear whether a reported cluster of cases is unusual.
The E. coli O157:H57 outbreak in the New York City area in late 2006
provides an example of how syndromic surveillance could have been used for
case finding. The outbreak came to light on November 17 when the first case
was reported to a local health department in New Jersey. By November 27,
11 cases were reported in that jurisdiction. Three days later the Taco Bell restaurant, where people in 9 of the 11 cases had eaten closed voluntarily. On December 1, a similar case (originally attributed to another cause) was reported to a
local health department in New York state, and it turned out that this person and
three others in that jurisdiction had eaten at a different Taco Bell restaurant. By
December 4, all Taco Bells in the New York metropolitan area were closed, and
two days later a particular food item, green onions, was identified as the likely
source of contamination. By December 9, more than 61 E. coli O157:H57 cases
in at least four states were reported (CDC, 2006d).
Although a number of syndromic surveillance systems were operating at this
time in New York City and the surrounding jurisdictions, there were too few cases
in any location to detect. However, once the outbreak was identified in New Jersey, an advanced syndromic surveillance system could have searched emergency
department admissions for cases of bloody diarrhea and abdominal cramps in the
entire metropolitan area. Cases so identified could have been interviewed to take
a food history, and lab samples obtained to test for E. coli O157:H57. In addition, health departments could have initiated active surveillance by physicians in
the area, searched data from surrounding states to identify additional cases for
follow-up and to confirm lack of cases elsewhere. If these steps had been taken,
it is possible the restaurant chain and green onions could have been identified
and remedial steps taken earlier—either closing the restaurant or removing the
green onions. It is also likely that the additional data from syndromic surveillance
systems could have resolved the uncertainty about what was happening and thus
diminished public concerns.
Using syndromic surveillance—essentially, prediagnostic health information
in existing electronic databases—as these examples suggest requires flexible and
easily accessible IT systems, as well as a relationship between data providers and
health departments that enables the systems to be used when needed. A benefit
of developing these relationships may be improved communications between
health-care providers and public health, which is essential to responding to any
health emergency.
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global infectious disease surveillance and detection
Conclusions
Any careful review of the development of syndromic surveillance in the past
five years would have to conclude that much impressive work has been done with
respect to information technology, including the real-time integration of many
disparate data streams, and analysis—the development of statistical models,
detection algorithms, and methods to visualize syndromic data. From a public
health practice point of view, however, the value of syndromic surveillance for
detecting bioterrorist attacks has not yet been demonstrated. There are two major
reasons for this conclusion. First, in statistical terms, there is a relatively narrow
window between what can be detected in the first few days and what is obvious.
Second, better integration with public health systems is needed before information generated is useful in guiding a public health response. The analysis in this
paper, however, suggests that the most important contribution of syndromic
surveillance to public health practice may be for natural disease outbreaks, such
as seasonal and pandemic flu, and as a tool to monitor outbreaks and guide the
public health response. Realizing this potential will require designing systems
that focus on these uses rather than being optimized for timely detection of
large-scale bioterrorist attacks. Instead of automating the process of detecting
outbreaks with statistical detection algorithms, it might be more useful to build
flexible analytical tools into syndromic surveillance systems so they can monitor
ongoing bioevents and facilitate epidemiological analysis.
IMPLICATIONS OF “REAL TIME” VERSUS
“BATCH REPORTING” FOR SURVEILLANCE
Joseph Lombardo, M.S.
The Johns Hopkins University
Introduction
In the context of disease surveillance, there has been confusion promulgated
by vendors of systems on the requirement for “real-time” data feeds. The Institute
of Medicine requested the author to present material addressing the subject, “Real
Time” Versus “Batched” Reporting for Surveillance. The following discussion is
based on the author’s career of 37-plus years in developing, evaluating, operating,
and improving surveillance systems in different domains. Ten of these years have
been spent on developing and improving the Electronic Surveillance System for
the Early Notification of Community-Based Epidemics (ESSENCE), a disease
Center
of Excellence in Public Health Informatics.
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SURVEILLANCE STRATEGIES
surveillance system being used globally and locally by public health organizations (Lombardo and Buckeridge, 2007).
Definition
The terms “real time” and “batched” for disease surveillance can be used
to mean different things by different authors. Any discussion must begin with
some formal definition of these terms. The Institute of Electrical and Electronics
Engineers’ (IEEE’s) Computer Society Technical Committee defines real-time
systems as those “in which its temporal properties are essential for reliability
and correctness; the example applications include embedded systems, control
systems, monitoring systems, and multimedia systems” (IEEE-TCRTS, 2007).
Real-time computing systems are required for time-critical applications
where the result of a computing process is time critical. Examples with which
most everyone is familiar are video games where a split-second delay could
change the result of an outcome, or the use of antilock brake systems in cars to
provide immediate feedback and response to avoid a collision.
The term “batch” is used in computing much as it is in baking: a set of programs or jobs processed on a computer at one time, like baking a batch of cookies
in the oven. The Encarta (Microsoft Encarta, 2007) definition includes:
• Process items as batch: To process or assemble items as a batch or in
batches.
• Computer programs processed together: A set of programs or jobs
processed on a computer at one time.
Batched reporting of surveillance data, however, can mean a variety of things.
The following are just a few:
• Batched collection of health indicator data;
• Batched processing of indicator data;
• Reporting to health surveillance monitors that one or more rules have been
triggered at a periodic time interval; and
• Sending reports for reportable diseases in a group at some specific reporting interval.
The term “reporting” is used when the provider of the data (e.g., hospital, pharmacy, laboratory) sends data to the site where surveillance is being
conducted. This is usually the first step in the surveillance process. The term
“batched processing” is the processing of several files by applying mathematical
algorithms to derive information from the data. These algorithms can be used to
convert unstructured text data into structured data, for the identification of abnormal trends in the data, or for transforming data and information to be viewed in
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global infectious disease surveillance and detection
a manner that would permit easy interpretation by a variety of users. Batched
reporting is also used to refer to the actions needed to present data and algorithm
outputs to the users of surveillance systems. Collection and processing of data do
not occur at the same time as when data and results are being made available to
the user. Batched health data may be reported to users as soon as it is processed,
or it may be delivered at regular intervals, or accessed on demand.
The term “batched reporting” also has been used in the context of providing
notification of reportable disease to a higher public health authority. Reports of
animal diseases occurred monthly in some jurisdictions for those diseases that
are reportable, but do not pose an immediate threat.
Surveillance Context
Data Acquisition and Archiving
Figure 1-10 presents an example of a generic disease surveillance system.
Data acquisition occurs on the left of the figure. User interfaces are on the right,
and archiving and analytic processes are in the center. Possible sources of early
indicators of population health include 911 calls, emergency medical services,
emergency department chief complaints, over-the-counter self-medications, etc.
Some of the indicator data can be made available in real time while others can not.
Health Condition
Indicator Data
Sources
Emergency
department
chief
complaint
Secure
Communications
Archiving
Signal
Processing
Data
cleansing
Ambulance
calls
School
absenteeism
and nurse visits
Data
archive
Detection
algorithms
Web server
Military data
Text
parsing
Public Health
Information
Network
Messaging
System
FIGURE 1-10 Electronic health monitoring components.
SOURCE: Lombardo (2006).
1-10
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User
interfaces
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Only data that is captured in real time can be made available for surveillance in
real time. When a cashier in a large retail chain scans an item the transaction can
be captured and transmitted to the company’s distribution center. Several large
retailers of over-the-counter medications capture their sales in real time so they
can keep track of inventory in each store. Schools track absenteeism on a daily
basis and not throughout the school day. School nurses could potentially track
every student visit as it occurs. Many hospitals now have automated information
systems based on the Health Level Seven (HL-7) format. These systems provide
a comprehensive framework for the exchange, integration, sharing, and retrieval
of electronic health information. Such information includes the instruction of
orders; clinical observations and data, including test results; admission, transfer
and discharge records; and billing information. HL-7 has become a standard for
the interfacing of clinical data for many large hospitals (Health Data Standards:
The Players, 2007). Monitoring a hospital’s HL-7 message traffic creates a record
of activities within the hospital as information is entered and archived. Monitoring an HL-7 data stream provides hospital record data as close to the time they
are created as possible.
To preserve the timeliness of HL-7 records, many developers and surveillance system users believe the records need to be transmitted to the automated
surveillance system as quickly as they are created. One method for preserving
this timeliness is to provide continuous transmission of HL-7 records between the
hospital and the surveillance system. The use of a virtual private network (VPN)
permits HL-7 records to be transmitted as soon as they appear on the hospital’s
network.
Another popular mechanism for data transmission uses the File Transfer
Protocol (FTP). Records are accumulated and “batched” over some time interval, then sent at a specific time to the FTP site, where they are picked up by the
surveillance system for archiving and processing. The Center for Disease Control
and Prevention’s (CDC’s) BioSense program aggregates HL-7 hospital records
every 15 minutes, and transfers them to CDC using the Public Health Information
Network (PHIN) Messaging System.
Most state and local health departments have varying requirements for the
timeliness in which data are provided for surveillance. Many health departments
believe that receiving data once a day may be sufficient, while others believe
that real time is mandatory. The Department of Health and Human Services for
Montgomery County, Maryland, has implemented its data collection surveillance
component so it can acquire data at higher rates during times when the department is concerned about a possible health risk.
Data Processing
Once the data are acquired and archived by the surveillance system several
processing steps could occur. Initial processing is needed to reduce entry and
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global infectious disease surveillance and detection
transmission errors. The term used in Figure 1-10 to describe these processes is
“data cleansing.” Separate processing algorithms are needed to convert text data,
such as chief complaint, clinical notes, and radiology reports, into a structured
data for use in signal analysis. These processes are referred to as “text parsing”
in Figure 1-10.
Automated surveillance systems employ a variety of algorithms to process
data for early detection of a health event. “Signal processing” is a term frequently
used for these processes. If the datasets are large or diverse, or come from many
different sources, the signal processing steps can require several minutes to hours
of computing time. Certain algorithms, such as those for spatial analysis (e.g.,
attempting to form spatial clusters across hundreds of ZIP codes) are particularly
time consuming; as a result, such cases tend to be processed as batches because
they simply cannot be performed in anything resembling real time. Processing is
initiated and results are provided after well-defined periods, such as every four
hours.
Some surveillance systems are interactive and allow the user to invoke
specific processes to get an immediate result. These systems permit the user
to analyze and view data as they are being received. ESSENCE provides both
options. Data are processed at regular intervals and results available for display,
but they are also available for user-defined analysis as soon as they are received,
archived, and preliminary processes are completed.
User Interfaces
Many advanced disease surveillance systems take advantage of modern
Internet technology. Typically, a user/analyst views a website once a day, but in
the event of an emergent health threat, more frequent or ongoing analysis is possible if data are available.
Most modern disease surveillance systems provide outputs to users as soon
as the signal processing phase is complete. Users log on to the surveillance system and view the alerts or data. The alerts may be in the form of “flags” indicating
that a predetermined “threshold” has been exceeded or an anomalous condition
detected; temporal and spatial data displays; or lists of cases that contributed to
the alert.
“Real Time” Versus “Batched”
Most modern disease surveillance systems have multiple processes that must
be completed before the data are provided to users. Collecting data in real time
while processing it in batch due to the constraints in computing time does not make
An
algorithm is a set of well-defined rules or procedures for solving a problem in a finite number
of steps, or providing an output from a specific set of inputs (Banner Engineering Corp., 2007).
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SURVEILLANCE STRATEGIES
for a real time system. Going through the extra expense of maintaining a VPN to
collect HL-7 hospitals as they are being created makes little sense unless these data
can be processed and made available to the analyst also in real time However, the
question remains whether real time is even needed by public health.
It is hard to conceive of any public health need for the more timely collection of data than that provided by CDC’s BioSense program. This program has
implemented the collection of “batched” HL-7 hospital records every 15 minutes.
The total throughput or time delay of the current BioSense processing steps is not
known to the author, but it can safely be estimated to be greater than 15 minutes.
The BioSense data feed is batched, but more timely than systems claiming to be
real time.
Given constraints on time and resources, one could envision two modes of
operation for electronic surveillance systems: one for the routine monitoring of
public health, and the other to examine a specific threat based on case definition.
For routine monitoring purposes, it will be of paramount importance to keep alert
rates to a manageable level. The focused monitoring of perceived threats should
be a rare occurrence, but essential information should be obtainable in sufficient
time to mount an effective response to an emerging crisis.
Summary
The term “real time” as defined by the IEEE’s Computer Society Technical
Committee is not appropriate for use in describing modern automated disease
surveillance systems. The benefits of real-time data collection are only realized
if all other components of a surveillance system satisfy the real-time criteria.
Receiving and processing health indicator data several times an hour should be
more than adequate for public health needs, even during public health emergencies. The use of the term “real time” is often confused by vendors who misuse the
term in an effort to distinguish their product as being better than someone else’s.
Consumers should attempt to understand the actual system characteristics rather
than relaying the misuse of terms by vendors of surveillance systems.
ONE WORLD—ONE HEALTH:
WILDLIFE AND EMERGING DISEASE SURVEILLANCE
William B. Karesh, D.V.M.
Wildlife Conservation Society
Outbreaks of avian influenza, severe acute respiratory syndrome (SARS),
Ebola hemorrhagic fever, bovine spongiform encephalopathy (mad cow disease),
Director,
Field Veterinary Program; Co-Chair, The World Conservation Union (IUCN) Species
Survival Commission’s Veterinary Specialist Group.
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global infectious disease surveillance and detection
and other emerging diseases are surprising the public, disrupting globalization,
resulting in massive economic losses, and jeopardizing business and diplomatic
relations. These diseases, which are able to cross the Darwinian divide between
animals and people, do not depend on humans for their survival and easily live far
from the reaches of most medical interventions. Their competitive advantage in
this regard demands that we revisit basic strategies for disease control, including
the assumptions from the 1950s declaring the chapter on the threat of infectious
diseases closed. Not only was this narrow, urban human health point of view
premature, but it diverted resources away from preparedness for dealing with the
modern-day world of rapid travel and transportation of both goods and people,
higher human population densities, and a growing dependence on intensified
livestock production.
Although many in the developed world would hardly recognize meat not
wrapped in clear plastic, the vast majority of humans still live in a world like
our great-grandparents’, buying their food fresh, salted, or smoked in open-air
markets, or gathering it themselves. For much of the world, there are no systems
of inspections for these markets, and few people have access to good health care,
education on hygiene, common vaccinations, or antibiotics. The global transport
of animals and animal products, which includes hundreds of species of wildlife
(Karesh et al., 2005), also provides safe passage for their bacteria, viruses, fungi,
and even the prion proteins that cause insidious illnesses such as mad cow disease
and chronic wasting disease of deer and elk. Surveillance of infectious diseases
is most useful when it occurs as close to the source as possible, rather than waiting to measure morbidity and mortality in distant lands. This requires a new
approach, one that engages people around the world to work together in earnest
and share findings in a timely manner.
Currently, no government agency is responsible for, or capable of, the surveillance and prevention of the myriad diseases residing around the world. None
are given the responsibility for robustly pursuing the simplest of concepts—the
health of people, animals, plants, and the environment in which we all live are
inextricably linked. The great gains from specialization in the fields of human
health, public health, livestock health, and wildlife health have unfortunately
resulted in academic hubris and reduced communication across disciplines by the
end of the 20th century. Avian influenza serves as the most recent reminder that,
in fact, there is only “one health.” Over the last decade, the Wildlife Conservation Society (WCS) has been working to engage stakeholders in this concept with
projects and a series of symposia utilizing the One World—One Health theme
in Durban in 2003 (Osofsky et al., 2005a, b), New York in 2004, Bangkok and
Beijing in 2005 (Karesh and Cook, 2005), and Brasilia in 2007. The products
of these meetings as well as guidelines for future efforts such as the “Manhattan Principles” are openly available. This one health concept is gaining wide
See
http://www.wcs-ahead.org and http://www.oneworldonehealth.org.
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acceptance and most recently has been endorsed by both the American Medical
Association and the American Veterinary Medical Association. However, putting
words into action presents the biggest challenge, and the world’s agencies and
academies devoted to human and animal health were built to support separate
sectors rather than to facilitate collaboration.
The U.S. Department of Agriculture (USDA) is mandated and funded to
protect the U.S. livestock industry. Radar screens are set to blink when livestock
are threatened. Even the more recent concerns of agroterrorism have not done
enough to support the global outreach necessary to understanding and reducing
diseases overseas before they reach U.S. shores. The wildlife services branch of
USDA traditionally was focused on wildlife control and eradication in order to
protect livestock. It is rapidly trying to remake itself in a modern world that is
recognizing the cultural, ecosystem, and economic value of wildlife itself. But
developing an effective program, building a reputation and trust among the wildlife community, and developing expertise in wildlife surveillance will take a longterm commitment that may or may not be on the horizon (or appropriate, in all
fairness) for a federal agency focused on agricultural production and markets.
The United Nations’ Food and Agriculture Organization’s (FAO’s) priorities
are the production of livestock and crops, with a focus on the urgent needs of
developing countries. Traditionally, few resources were devoted to exploring the
linkages of the health of wild plants and animals with their domesticated cousins.
This has changed since 2005, and a small program was begun in collaboration
with the WCS to coordinate responses and investigations of highly pathogenic
avian influenza virus in wild birds.
The World Organization for Animal Health (OIE) has a volunteer committee
composed of six people who meet for three days per year to address all of the
world’s wildlife-related disease issues. In the past two years, they have formed a
parallel committee to address zoonotic and emerging diseases but the two committees are not linked to one another. The World Health Organization (WHO)
is directed at human health, but until the change in the International Health
Regulations (IHRs) that took effect this year, they could only respond on official
invitation from a country that may or may not know about, or want to reveal, the
presence of a disease. The changes in scope will allow for gathering of information without going through official channels. This could help significantly in
global response time, but the IHRs are still institutionally entrenched in a world
of human disease. The U.S. Centers for Disease Control and Prevention (CDC)
has the responsibility to prevent human diseases in the United States, and extend
their reach around the world, but also only when invited.
No government agency or multilateral organization is charged with uniting
knowledge and efforts that span the diversity of disease threats to people, domestic animals, and wildlife. No one is ensuring that health solutions are based on the
Office
International des Epizooties.
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global infectious disease surveillance and detection
input of expertise from human, domestic animal, and wildlife health professionals
and equally important, communicated across disciplines in terms that effectively
motivate all stakeholders and demonstrate common goals.
Clearly, there is an urgent need for a new health paradigm that not only
integrates the efforts of disparate groups, but possibly more important, balances
their respective influences to prevent both the gaps and the biases that we are now
coming to recognize. The failure to recognize and aggressively address the broad
range of diseases that have no respect for hundreds of years of earnest scientific
classification, places animals and people in great danger. The immediate effects
of the diseases themselves are often the least of the worries. Infectious diseases
of people and animals are drivers of poverty and associated civil unrest, disrupt
“free” ecosystem services such as drinking water and plant pollination, and can
ruin otherwise well-planned and sustainable economic development efforts.
Analyses indicate that more than 60 percent of the over 1,400 infectious diseases currently known to modern medicine are shared between humans and animals (Taylor et al., 2001). From an anthropocentric point of view, most of these
infectious agents are labeled zoonotic, or diseases of animals that infect people.
Anthrax, Rift Valley fever, plague, Lyme disease, and monkeypox are just a few
examples. Receiving less attention is the other group that moves across species
boundaries, the anthropozoonotic diseases. These infectious diseases are typically
found in humans but can, and do, infect animals. Human herpes virus, human
tuberculosis, and human measles are all transmissible to a variety of animal species, with devastating consequences. This traditional division of infectious agents
into two groups is convenient for teaching purposes, but lacks the broader and
critically important concept that these diseases can move back and forth, and
change characteristics in the process. Avian influenza is but one disease that is
teaching the medical world about the need for a more holistic point of view.
The consensus of scientific opinion on the origin of HIV/AIDS links it to
human consumption of nonhuman primates along with their simian immunodeficiency viruses, estimated to have taken place in Africa late in the first half of
the 20th century (Feng et al., 1999). Recent Ebola hemorrhagic fever outbreaks
in humans in Africa have a similar history. The disease was first recognized by
the western world when it appeared in the Democratic Republic of Congo in
1976, around the Ebola River. The virus infects people, gorillas, chimpanzees,
and monkeys (Leroy et al., 2004). It causes severe internal and external hemorrhaging, and can be extremely deadly, killing up to 90 percent of its human victims. Infection spreads quickly, especially via caregivers and by those who flee
to escape the illness. Outbreaks have been recorded in Sudan, Gabon, Republic
of Congo, Democratic Republic of Congo, Côte d’Ivoire, and Uganda. But it is
clear that both people and nonhuman primates suffer equally from the disease.
Outbreaks have caused declines in lowland gorillas and chimpanzees in Gabon
and the Republic of Congo, and chimpanzees in western equatorial Africa. Other
forest animals, such as duikers—small antelopes—and bush pigs may also be
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affected. When subsistence hunters discover a sick or dead animal in the forest,
they view it as good fortune and bring it home to feed their families and trade
with neighbors. The Ebola virus then easily infects those handling the meat, and
a chain of contacts and infections ensues. Each human outbreak in central Africa
during the late 1990s and the first years of this century was traced to humans
handling infected great apes.
The SARS coronavirus has been associated with the trade in small wild carnivores. This disease first appeared to the world in China’s Guangdong Province
in late 2002. People began complaining of high fever, cough, and diarrhea, and
eventually developed severe pneumonia. It was an unknown disease, and it was
very contagious. Within a matter of weeks, it spread via a hotel visitor in Hong
Kong to five continents. By July 2003, WHO had tallied 8,437 cases, with 813
deaths. Mostly because of a lack of understanding of this “new” disease, global
travel and trade were disrupted as fear spread. A coronavirus (a family of viruses
found in many animal species) was finally discovered to be the culprit, and it
was also detected in masked palm civets that were farmed in the region and sold
for human consumption. Later, evidence of the virus was also found in raccoon
dogs, ferrets, and badgers in the wildlife markets, as well as domestic cats living
in the city and a closely related coronavirus in bats commonly sold in the same
markets. Epidemiological studies have concluded that the first human infections
did indeed come through animal contact, though the exact species has not been
definitively identified (Tu et al., 2004). In the weeks after SARS, the Chinese
government responded by closing down live wildlife markets. Within 10 days,
nearly a million animals were confiscated, many brought in from other parts of
the world with their exotic viruses and bacteria, demonstrating that law enforcement can in fact be used to reduce or control the trade in wildlife and wildlife
products. The animals were mixed and matched, exposed to each other’s wastes
and even fed to each other. If a virus or bacteria was hoping to win the big lottery
of jumping among species, going to the markets of Guangdong would be like
buying a million lottery tickets. The profits from the wildlife trade in China pale
in comparison with the estimated U.S. $50 billion global economic costs resulting
from the brief SARS event of 2003 (Newcomb, 2003).
The inadvertent movement of infectious agents due to wildlife handling
and trade, as well as domestic animal movement, is not limited to human pathogens, but also extends to those that can devastate native wildlife, which serve as
biological linchpins for environmental integrity and provide a range of cultural
and quantifiable economic values (Karesh et al., 2005). In 2005, H5N1 Type A
influenza virus was isolated from two mountain hawk eagles illegally imported
from Thailand in airline cabin carry-on baggage to Belgium (OIE, 2004). Tuberculosis originating from domestic cattle has now infected wild herds of bison in
Canada, deer in Michigan and Wisconsin, and Cape buffalo and lions in South
Africa. Surveillance of these wild populations is now needed not only to assess
risk for humans and livestock, but for the wild animals themselves. In one swift
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global infectious disease surveillance and detection
outbreak of rinderpest, a disease originally introduced to Africa by the importation of domestic cattle, more wild buffalo died in Kenya in 1999 than were killed
by illegal poaching during the previous two decades.
Exact quantification of the global wildlife trade is impossible because it
ranges in scale from extremely local to major international routes, and much is
illegal, or through informal channels. WCS figures compiled from a variety of
sources for just the live wildlife trade indicate that each year, roughly 40,000
live primates, 4 million live birds, and 640,000 live reptiles are traded globally
(Karesh et al., 2005). Daily, wild mammals, birds, and reptiles flow through trading centers where they are in contact with humans and dozens of other species
before being shipped to other markets, sold locally, and even freed back into the
wild with new potential pathogens as part of religious customs such as merit
release or because they become unwanted pets. Conservative estimates indicate
that in east and southeast Asia, tens of millions of wild animals are shipped
regionally and from around the world annually for food or use in traditional
medicine. The estimate for trade and local and regional consumption of wild
animal meat in Central Africa alone is more than 1 billion kg per year (Wilkie
and Carpenter, 1999). In Central Africa, estimates of the number of animals consumed by humans annually vary, but a figure of 579 million has been proposed.
Estimates for consumption in the Amazon Basin range from 67 to 164 million kg
annually, comprising, for mammals alone, between 6.4 million and 15.8 million
individuals (Peres, 2000).
Hunters, middle marketers, and consumers make some type of contact with
each animal traded. Additionally, domestic animals and wild scavengers in villages and market areas consume the remnants and wastes from the traded and tobe-traded wildlife. These numbers combined suggest that at least some multiple
of 1 billion direct and indirect contacts among wildlife, humans, and domestic
animals result from the handling of wildlife and the wildlife trade annually.
In addition to the direct health effects of the pathogens on people and
animals, animal-related disease outbreaks have caused hundreds of billions of
dollars of economic damage globally, destabilizing trade, and resulting in devastating effects on human livelihoods. According to studies performed by BioEconomic Research Associates, the rash of emerging or reemerging livestock
disease outbreaks around the world since the mid-1990s—including mad cow
disease, foot-and-mouth disease, avian influenza, swine fever, and other diseases—has been estimated to have cost the world’s economies more than $100
billion. The costs are rarely borne by the same individuals that profit from the
movement of animals and their pathogens. As mentioned earlier, the cost of SARS
alone to the global economy has been put at more than $50 billion (Newcomb,
2003). Wildlife market traders did not bear the costs of the SARS outbreak. The
rodent importer in Texas did not reimburse government agencies for the millions
of dollars spent on the response to monkeypox in the United States. Hundreds of
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millions of public dollars will be spent in attempting to remove tuberculosis and
brucellosis from wildlife populations infected by domestic animals.
In early 2003, FAO reported that more than one-third of all global meat trade
was embargoed as a result of mad cow disease, avian influenza, and other livestock disease outbreaks. The projected growth of industrial livestock production
in developing countries to meet rising global protein demand will increase both
the economic and the food security impacts of future disease outbreaks, and the
global economic impacts do not adequately reflect the local, direct effects.
Preventing and controlling infectious diseases in the modern world requires
a far broader range of expertise than needed for previously isolated systems in
highly developed countries. The challenges seen in controlling avian influenza in
Asia and Africa are just one example of the multispecies disease dilemma. Most
of these diseases threaten local people directly, as well as their livestock and their
livelihoods. They decimate wildlife and undermine ecosystem stability and services, and with modern travel and transport, they can quickly pose a threat to any
nation. Fear, understandably founded on a lack of information, can drive global
responses and economic reactions far beyond the actual cost of disease control.
Currently, it appears that a few people in some of the most remote places on
earth, many from nongovernmental organizations (NGOs) and many working at
local government levels but unlinked to larger formal networks, are working to
fill the intersectorial gaps in health care as they relate to emerging diseases and
wildlife. WCS’s global health programs are an example of a private-sector effort
linked to governmental and multilateral agencies that bring together stakeholders,
from civil society and a variety of government sectors, to develop surveillance
and information-sharing networks. The work is directed where rare infectious
diseases are least understood and local institutions have the fewest capabilities to
effect prevention and control. Our staff and partners routinely encounter diseases
such as anthrax, avian influenza, monkeypox, and Ebola where they naturally
occur. We build local capacity to conduct surveillance and reporting networks at
very low costs. When attention was being misdirected at wild birds in efforts to
control the current avian influenza outbreaks in Southeast and East Asia, these
new, but informally recognized participants in health discussions, were the first
to point out that migratory routes and seasonal timings did not correspond with
the regional spread of the disease as posited by articles in prestigious scientific
journals—it was the largely uncontrolled movements of domestic birds that were
spreading this disease, not wildlife. Control efforts would be needlessly misdirected without this simple input to decision makers.
Building bridges across disciplines to solve health problems can have simple
but significant synergistic effects. Studies in South America have shown that,
contrary to common opinion, livestock diseases pose more threats to wildlife
than the other way around. In much of the world, reducing disease in domestic
animals would benefit several industries, improve human health and livelihoods,
and help protect wild animals from livestock and other domestic animal diseases.
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In Central Africa, gorillas and chimpanzees have little to no immunity to common
human diseases. Local people and tourists threaten wild populations with these
illnesses, which could be simply avoided by implementation of good preventive health programs and practices in villages. People and wildlife both benefit.
WCS’s work with Ebola hemorrhagic fever in gorillas and chimpanzees has
shown that when investments are made for working not just in the cities but in the
forests, natural resource managers can help to detect the presence of the disease
in wildlife months before the first human cases—providing the lead time to warn
villagers not to hunt or handle the animals that are the source of infection.
Over the past two years, the WCS network of local villagers and hunters,
park managers and staff, government public health officials, and regional laboratories has detected outbreaks of Ebola in great apes and notified local communities. For the first time, known human outbreaks resulting from the disease
in animals have not occurred. This broader, one-health approach is much more
effective and inexpensive than the traditional “quarantine and stamping out”
efforts after an outbreak has begun. A set of guiding concepts on these themes,
called the Manhattan Principles, was developed by human and animal health
specialists in conjunction with wildlife conservation professionals.
Another large-scale example of a worldwide private–public collaborative
effort is the Global Avian Influenza Network for Surveillance (GAINS) of wild
birds. The U.S. Agency for International Development (USAID), CDC, and
USDA are providing support to WCS to develop and administer the wild bird
GAINS program. GAINS is a smart and targeted investment in the U.S. government’s fight against avian influenza, because wild birds around the world can
serve as sentinels for the early detection of the virus’s presence.
Awareness of and interest in the GAINS program continues to grow. Working relationships with local institutions are being built in more than 28 countries,
with many more anticipated. This network of partners builds a “window on the
world” and has helped GAINS bring timely and pertinent information that will
help combat the threats posed by highly pathogenic avian influenza to both
humans and animals.
The GAINS program has made significant progress in its global implementation since receiving start-up funding in summer 2006. Collaborations have
been established between WCS and U.S.-based and international organizations—
including governments, NGOs, and universities—to work together to improve our
understanding of the dynamics of avian influenza, and to evaluate disease risks
for people, biodiversity, and domestic poultry. WCS staff have been in active discussions with colleagues from USAID, CDC, Department of Homeland Security
(DHS), Department of Defense (DoD), U.S. Geological Survey (USGS), USDA,
National Institutes of Health (NIH), Department of State (DoS), WHO, FAO, as
well as university and private-sector experts to address integrated approaches to
See
http://www.oneworldonehealth.org.
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global disease information management issues. Together with FAO, WCS has
conducted training efforts in Eastern Europe, Latin America, and the Caribbean,
and a recent agreement with USDA will expand training and bird monitoring in
Latin America. WCS is providing technical expertise related to health monitoring
of wild birds and capacity-building activities around the world.
GAINS fieldwork also enables the isolation of new viral strains, which can
contribute to vaccine development and help guide preparedness in the United
States and abroad. One of the primary purposes of GAINS is to share international disease information through an interactive, publicly accessible web-based
database, a working prototype of which has already been made available on the
GAINS website. The database is starting to map sample collection sites, flyways, and results of biological surveillance. The goal is to alert decision makers
about disease occurrence rather than waiting for traditional scientific journal
publication.
From Afghanistan to Zimbabwe, field surveillance for avian influenza is currently underway. Our work in Mongolia illustrates the field methodology being
used in many sites. Mongolia has been a hot spot for avian influenza outbreaks
in the past two years and is a country where wild birds appear to be of particular
importance to the ecology of the disease. Last year WCS staff collected more
than 3,500 samples at 42 sites across the country. WCS staff collected an H5N1
strain of avian influenza virus from wild birds that have been selected by WHO
to be used in human pandemic vaccine development and testing. Working with
WCS staff in Mongolia, USGS scientists fitted whooper swans from the region
with satellite transmitters (supplied by FAO) in early August, and some have
been tracked to China, Korea, and Russia. These types of data may shed light on
possible viral transmission routes across Asia.
The early successes with the Wild Bird GAINS program has led to expansion of the program to a broader range of infectious diseases and species. Named
the Wildlife Global Animal Information Network for Surveillance (Wildlife
GAINS), the effort is designed to establish a comprehensive, worldwide wildlife health surveillance system to enhance preparedness for and awareness of
emerging infectious diseases. This nongovernmentally managed network would
connect a wide variety of U.S. government agency partners, multilateral agency
partners, conservation organizations, veterinary and medical schools, and other
national and international partners. The unique strengths and capacities that
NGOs such as the Wildlife Conservation Society have to work with developing
country governments and scientific colleagues must be harnessed to develop
and enhance surveillance mechanisms that are of great importance to human
security and well-being.
Workers in the fields of health and global governance need to find ways to
focus skills and expand resources to make the entire world safer from infectious
See
http://www.gains.org.
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global infectious disease surveillance and detection
disease. The financial costs of disease outbreaks are currently borne by the global
economy and will only serve to slow economic development where it is needed
the most. There is an obvious need to break down barriers among health disciplines to prevent any one of them from restricting funding to their area of interest, and there is an urgent need to build bridges among the government agencies
and the privately operating individuals and organizations around the world that
now take responsibility with only scarce resources. Immediately, before the next
global pandemic, trade in wildlife needs to be dramatically reduced and, like the
livestock industry, properly regulated. Finally, global health will not be achieved
without a philosophical shift from the “expert dictates” paradigm inherent to
both science and medicine, to a broader, multistakeholder approach, based on the
understanding that there is only “one world and one health.”
AGRICULTURAL BIOSECURITY: THREATS
AND IMPACTS FOR PLANT PATHOGENS
Jacqueline Fletcher, Ph.D.10
Oklahoma State University
James P. Stack, Ph.D.11
Kansas State University
Plant Vulnerability to Disease
Plant resources in the United States, including crops, rangelands, and forests,
are vulnerable to endemic, introduced, and emerging pathogens (American Phytopathological Society Public Policy Board, 2002; Casagrande, 2000; Madden
and Wheelis, 2003; Wheelis et al., 2002; Whitby, 2002). An estimated 65 percent
of U.S. crop losses, valued at $137 billion, are attributed to introduced pathogens
annually (Pimentel et al., 2000). Increasing globalization and international trade
activities create a strong likelihood that many other exotic plant pathogens will
arrive in the United States in the coming years.
The vulnerabilities of U.S. agricultural production to emerging diseases
result from a number of factors. Huge acreages are planted with grains and forage crops, or are covered with grasslands or forests. Because it is impossible to
regularly or frequently monitor such extensive areas for disease symptoms, long
periods are likely to pass between the time a pathogen is introduced and when
it is detected. A second source of vulnerability is the lack of genetic diversity
in our plant resources; most of our nation’s production is centered on just three
10 National Institute for Microbial Forensics & Food and Agricultural Biosecurity, and Department
of Entomology and Plant Pathology.
11 Biosecurity Research Institute.
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crops: wheat, corn, and soybeans. Within these and other crop species, certain
genotypes conferring attributes important for yield and quality are preferentially
grown over large areas, increasing the chance that a pathogen detrimental to that
cultivar will have serious impact.
More than 50,000 plant diseases occur in the United States (Madden, 2001;
Madden and Wheelis, 2003), caused by a variety of pathogens, including fungi,
viruses, viroids, bacteria, nematodes, and parasitic plants. These organisms are
disseminated by various means, including wind, water, agricultural equipment,
seeds or propagative plant parts, insect vectors, animals, or farm workers. For any
given region and crop, producers may deal with up to 10 to 15 serious plant diseases that can cause severe economic repercussions (Pinstrup-Andersen, 2001).
About 65 percent of U.S. crop losses are due to nonindigenous (introduced)
pathogens, amounting to an estimated cost of $137 billion annually (Pimentel et
al., 2000). All crop pests (pathogens, arthropods, and weeds) combined caused
preharvest losses of 42 percent and an additional 10 percent loss after harvest.
Of these, 13 percent were due to plant pathogens, 15 percent to arthropods, and
13 percent to weeds. Worldwide, losses for the eight major crops that comprise
half of the global croplands were estimated at $300 billion in 1988–1990 (Oerke
et al., 1994).
A number of pathogens that occur elsewhere in the world are of significant
concern to U.S. plant production, should they arrive. Most past introductions of
plant pathogens to the United States have been unintentional. Many pathogens
not yet in the United States would pose significant threats to our current crops.
Because eradication of plant pathogens is rarely physically or financially feasible,
the only effective approach is to manage the disease so that its impact falls below
an economic threshold—the point at which management costs exceed the profits
associated with production.
The use of microbes, such as the anthrax bacterium, against human targets is a highly visible act with immediate consequences. Directing pathogens
toward agricultural targets may be less visible, and effects may not be apparent
for some time. However, such actions, which effectively target the nation’s food
supply—from its production in the field to its place on the plate—may have
serious and long-range impacts (Adam, 2006). Many plant pathogens can be
acquired readily by those wanting to use them intentionally for purposes of harm.
Furthermore, they may be attractive agents for nefarious applications because
they can be handled, grown, transported, and disseminated with little technical
expertise or equipment, and pose little or no danger to the health of the handler.
The Institute of Medicine (IOM)/National Research Council (NRC) Committee
on Advances in Technology and the Prevention of Their Application to Next
Generation Biowarfare Threats recently concluded (2006) that the increasing
accessibility and simplicity of technological information related to pathogens
increase the likelihood that rogue states or individuals may use such knowledge
in a criminal manner.
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History of Biological Warfare
Biological warfare has been targeted to agricultural systems in the past.
Around the world, state-sponsored programs supported research to enhance the
suitability of microorganisms for use as weapons (Casagrande, 2000; CIDRAP,
2003; Madden and Wheelis, 2003; Wheelis et al., 2002; Whitby, 2002). Before the
Biological and Toxin Weapons Convention outlawed state programs on biological
weapons in 1972 (IOM/NRC, 2006), U.S. research programs had focused on the
pathogens causing anthrax, foot-and-mouth disease, and rice blast. Germany had
bioweapons programs during World Wars I and II, the former Soviet Union during
World War II and the Cold War, and Iraq at the time of the Iran–Iraq War. Islamic
militants in Afghanistan were involved in weaponization of the fungus Puccinia
graminis, causal agent of wheat rust. Canada, France, Japan, and the United Kingdom also considered the use of bioweapons against agricultural targets.
Despite knowledge of such research activity in multiple countries, no
reports of the deliberate use of pathogens against crops or other plants have been
published. Yet, indicators of increasing likelihood of such use point to the need
for preparedness. The United States must develop the capabilities and knowledge to ensure the safety and security of our food at all levels, and at all points
of production—the distribution pathway from farmers’ fields to the consumer.
Rapid action is critical if we are to have these capabilities in place before they
are needed for a devastating incident.
Impacts of Plant Diseases
Past incidences of the impacts of crop diseases on human health and society
may be helpful in illustrating the potential damage of plant pathogens. The Irish
potato famine (1845–1846), caused by the plant pathogen Phytophthora infestans, led to extensive famine and resulted in the deaths of a million people and the
emigration of another 1.5 million Irish, many to the United States (Large, 1940;
Carefoot and Sprott, 1969; Schumann, 1991). During the same timeframe, the
severe impact of a rust fungus on coffee production in Ceylon (now Sri Lanka),
the prime supplier of coffee to Great Britain, forced much of British society to
turn to tea as their primary hot beverage (Large, 1940; Schumann, 1991). Weather
conditions in both the United States and Europe during World War I were favorable for the development of plant diseases in wheat and potatoes, crops essential
for nourishing the troops on both continents. The critical food shortages that
ensued were factors in the movement and strength of the troops and changed the
course of the war. Brown spot of rice contributed to the Great Bengal Famine
of 1943, and in the United States, a 1970 epidemic of corn leaf blight destroyed
about 20 percent of the $1 billion crop (Rogers et al., 1999).
U.S. agricultural infrastructure is strong, diverse, and resilient. Temporary
unavailability or elimination of a certain food product because of plant disease
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is unlikely to result in significant nutritional hardship for Americans. The same
cannot be said for all countries, however; a serious rice disease in Southeast
Asia, for example, could lead to malnutrition and hunger, destabilizing social
infrastructures in affected areas.
Deliberate introductions of plant pathogens to crops and other plant resources
in the United States could have serious non-nutritional impacts (Budowle et al.,
2005a, b; Murch et al., 2003; Fletcher et al., 2006). Likely impacts of crop diseases in the United States include losses in the quality and quantity of our food,
increases in consumer food prices, costs of growing crops that are less desirable,
and costs of management strategies, both short term (crop destruction, pesticide
application, or redirecting use of the crop) and long term (development of resistant varieties) (Casagrande, 2000; Madden and Wheelis, 2003; Wheelis et al.,
2002; Whitby, 2001, 2002). Several plant pathogens can also infect humans; these
are primarily opportunistic pathogens of greatest concern to immunocompromised patients, the very young, or the old. Some plant pathogenic fungi produce
mycotoxins that can pose important health risks for humans, and other species
produce spores that are allergenic. There also can be important indirect impacts
on human nutrition, as well as on the agricultural community, if plant products
used for livestock feed are lost.
The most significant impacts of deliberate plant pathogen introductions,
however, are likely to be economic in nature. Imposition of quarantines and
embargoes on U.S. agricultural products not only affect producers, but have
downstream effects on the commercial enterprises that harvest, store, package,
transport, add value, and market the commodity. Perhaps more importantly, there
could be a loss of trading partners and markets worldwide. Furthermore, knowledge of intentional targeting of the food supply by those intending harm would
lead to a loss of public trust in our food and in the ability of government to ensure
its safety. Ultimately, rural communities that rely on agricultural production may
be destabilized and grower livelihoods threatened.
At the other end of the food system continuum, there has been an alarming
rise in the incidence of foodborne illnesses due to microbial contamination of
fruits and vegetables. A recent survey by the U.S. Food and Drug Administration
(FDA) of samples from major distributors showed that 1.6 percent of domestic
produce was contaminated with human pathogens (FDA, 2001). Recent incidents
of contamination of leafy greens and peanut butter with the human pathogens
E. coli O157:H7 and Salmonella spp. demonstrate the devastating impact that may
result from the introduction of microbes into fresh food plants. Today’s mass food
production operations and national distribution systems have caused a significant
increase in the scope of such foodborne illnesses (Maslanka et al., 2002). Once
primarily local events, with local response, food contamination incidents are now
far more widespread. In the fall 2006 E. coli outbreaks, 205 victims in 26 states
suffered severe disease and 3 died. As a result, consumers changed their buying
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habits, producers of the affected crops suffered significant economic losses, and
downstream enterprises were negatively impacted (FDA, 2007).
High-Consequence Plant Pathogens and Diseases
In 2004, the U.S. Department of Agriculture (USDA) Animal and Plant
Health Inspection Service (APHIS), as designated in 7 C.F.R. Part 331 of the
Agricultural Bioterrorism Protection Act of 2002, first established a list of
plant pathogens of high consequence to be designated as Select Agents 12 (Table
1-3). Although this list is similar in nature to the Select Agent lists for human
and zoonotic diseases, there is one important difference. Plant pathogen Select
Agents are, at the time of their placement on the list, exotic microbes not endemic
or established in the United States. This contrasts with the policy of listing
indigenous human and animal pathogens on their respective lists. The fact that,
by definition, plant Select Agents are not indigenous within the United States
necessitates the imposition of strict regulations, registrations, restrictions, and
security13 on any research or possession of these microbes.
Originally consisting of 10 plant pathogens, the recent removal of 2 pathogens (Plum pox virus and Phakopsora pachyrhizi, the causal agent of soybean
rust) after their arrival and establishment in the United States has left the list with
8 agents. A mandated biannual review and possible revision of the plant Select
Agent list is underway at the time of this writing.
Citrus Canker: A Recent Example of Significant Disease Impact
Florida produces about 80 percent of the citrus grown in the United States,
and most of the state’s fruit is processed for juice. The industry is worth about
$1.4 billion per year. Although Xanthomonas axopogonis pv. citri, the bacterium
that causes the devastating citrus canker disease, is not on the Select Agent list,
it has occurred in Florida citrus-growing areas several times since the turn of the
century, each time causing brown, necrotic, raised scars or cankers on leaves,
stems, and fruit.
Canker is a quarantine disease; fruit from affected areas cannot be moved
across state lines or sold in the world market. Because the disease was not considered established in the United States, an eradication strategy has been in place
for many years. This approach was successful in Florida in the early 1900s and
again in the 1980s. APHIS and the Florida Department of Agriculture and Consumer Sciences adopted that same strategy for the most recent outbreak, which
was first detected in 1995. However, the latter outbreak presented new challenges.
12 See http://www.apsnet.org/online/feature/BioSecurity/ and http://www.cdc.gov/od/sap/docs/salist.pdf.
13 See http://www.aphis.usda.gov/programs/ag_selectagent/index.html.
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SURVEILLANCE STRATEGIES
TABLE 1-3 U.S. Select Agent List for Plants
• Liberobacter africanus
• Liberobacter asiaticus
• Ralstonia solanacearum R3 Bv2
• Xanthomonas oryzae pv. oryzicola
• Xylella fastidiosa
• Peronosclerospora philippinensis
• Sclerophthora rayssiae var zeae
• Synchytrium endobioticum
• *Pathogens not yet established in the United States
• Pathogens recently removed from Select Agent list
• Phakopsora pachyrhizi*
• Plum pox virus
Citrus greening (African)
Citrus greening (Asian)
Potato bacterial wilt
Rice bacterial leaf streak
Citrus variegated chlorosis bacteria
Philippine downy mildew of corn
Brown stripe downy mildew of corn
Potato wart fungus
Soybean rust
Pox of stone fruits
*Also spelled pachyrhizae.
SOURCE: Fletcher (2006).
First, the initial eradication guidelines called for elimination of the diseased tree,
plus any citrus trees within a 125-foot radius of the symptomatic plant. Although
this policy was not popular, it was relatively well accepted. However, in the late
1990s, these measures failed to prevent disease spread. Further research led to
an eradication strategy modification requiring the elimination of all citrus trees
within a 1,900-foot radius of any infected tree. Complicating matters was the
fact that the 1995 outbreak was not confined to commercial groves. It also was
widespread in residential areas of Miami where landowners objected, some filing
lawsuits to stop the eradication campaign. While the legal issues were debated
in court, the disease continued to spread. The eradication plan eventually was
upheld by the courts and the program was reinstated (Gottwald et al., 2002);
overall, $200 million was spent and more than 10 million trees were destroyed
(Brown, 2001). However, the occurrence of several hurricanes in Florida in 2005
spread the pathogen far beyond its previous locations and eliminated hope of
eradication. In 2006, USDA APHIS revised its approach to focus on managing
the disease.
Arrival of Two Plant Pathogen Select Agents
Two plant pathogens on the Select Agent list have arrived in the United
States in the past two years. Were we ready for them?
Soybean rust, caused by the fungus Phakopsora pachyrhizi, affects a major
U.S. crop that is grown over 75 million acres and is worth more than $18 billion
a year (USDA-ERS, 2007). In areas where the rust is endemic, such as Asia and
South America, yield losses commonly range from 10 to 30 percent, but can
be much higher. U.S. producers, who grow 74 million acres of soybeans/year
(accounting for about $15.7 billion), feared that the arrival of the fungus would
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severely impact the industry. U.S. epidemiologists had been monitoring the global
movement of the pathogen for several years in an effort to provide warning for
its inevitable arrival to U.S. territory. The disease was first detected in the United
States in fall 2004 (Schneider et al., 2005). The first diagnosis, in Louisiana, was
quickly followed by detection in several other states, but because the disease
arrived after the soybean crop had been harvested there was no impact on production that year. Indeed, the 2005 and 2006 growing seasons were characterized by
weather patterns unsupportive of P. pachyrhizae infection and disease, so actual
losses have not yet approached the damaging levels anticipated. This has been
good news for producers, but ironically, has prompted a sense of security that
may be unfounded in future years when conditions may be more conducive to
pathogen establishment.
Regardless of the seriousness of soybean rust to date, the fact that the pathogen was distributed widely—again likely by hurricane winds in 2005 (Stokstad,
2004)—and the fact that it establishes easily and overwinters in a variety of hosts,
including an extremely invasive vine called kudzu, means it is now considered
to be established in the United States (Pivonia and Yang, 2004). Since the plant
Select Agent list contains only exotic pathogens, APHIS removed P. pachyrhizae
from the list in 2006. “Delisting” has several implications, both positive and
negative. Federally mandated response to, and management of, a Select Agent is
extremely expensive for both federal and state agencies. In addition, the extensive
and expensive policies, certifications, permits, and containment requirements for
scientific research on Select Agents are significant disincentives for plant pathologists to work on the pathogens of greatest concern. The removal of P. pachyrhizi
from the list will facilitate research, but it also changes the responsibility of
federal agencies in their response to the disease.
The bacterial pathogen Liberobacter asiaticus, a Select Agent that causes a
disease officially known as “huanglongbing,” or citrus greening, was discovered
in Florida in fall 2005 (APHIS, 2007). Its possible arrival had been a concern for
at least two years, after it was learned that its insect vector—the citrus-feeding
Asian citrus psyllid, Diaphorina citri—had arrived in the state and would be
likely to spread the pathogen quickly should it arrive. Like citrus canker, huang
longbing was more damaging than anticipated because it, too, occurred during
the 2005 hurricane season, when extensive wind dissemination of inoculative
vector insects quickly resulted in the pathogen becoming endemic in the state.
The question of whether L. asiaticus will or should be removed from the Select
Agent list is complicated by the fact that, although the bacterium may be established in Florida, it is not yet known to occur in citrus-growing regions of Texas,
California, and other southern states.
Components of a Strong Plant Biosecurity Strategy
A robust system of preparedness for threatening exotic or emerging plant
diseases will require the following elements:
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• Early detection and diagnostic systems
• Epidemiological models for predicting pathogen spread
• Reasonable but effective strategies and policies for crop biosecurity
• Distributed physical and administrative infrastructure
• A national system for strategic planning and response coordination
• Microbial forensic capability: validated technology and investigative
capability
Before 2001, our national capability in plant disease diagnostics and recovery
was fragmented, poorly supported. and of limited effectiveness due to declining
resources. In the past five years, however, significant improvements in infrastructure will help to ensure preparedness for a serious plant pathogen introduction
event. In 2004, President George Bush issued Homeland Security Presidential
Directive 9 (HSPD-9), which mandated a National Plant Disease Recovery System (NPDRS). The USDA Office of Pest Management Policy, assigned by the
Secretary of Agriculture to develop the NPDRS, has worked to develop specific
Recovery Plans for each of the Select Agents as well as for several other plant
diseases of high consequence. Their approach, which is well underway at this
time, has been to bring key experts from federal agencies, private industry, and
academia together for the development of each plan, and to partner with the
American Phytopathological Society (a 5,000-member professional society dedicated to plant health) to ensure broad-based community input and participation.
Another important initiative has been the establishment—by USDA-Cooperative
State Research, Education, and Extension Service (CSREES)—of the National
Plant Diagnostic Network, an interconnected system of diagnostic laboratories
affiliated with land grant universities and/or state departments of agriculture in
each state (Stack et al., 2006).
At this writing, it is clear that many individual improvements and initiatives
have enhanced our nation’s ability to prevent and prepare for emerging plant
diseases and pathogens. Individual efforts within federal agencies concerned
with agricultural biosecurity (USDA APHIS, CSREES, and Agricultural Research
Service [ARS]; Departments of Defense and Homeland Security; Environmental
Protection Agency; and Food and Drug Administration) also have enhanced our
preparedness. However, significant gaps remain.
Preparedness for events involving intentional introductions of plant pathogens, whether for purposes of bioterror or biocrime, must include a strong
national security plan that encompasses microbial forensics and criminal attribution. However, U.S. crop producers, consultants, and agricultural scientists,
unaccustomed to considering the possibility of intentional pathogen introduction,
traditionally focus disease management strategies on prevention, rapid eradication, or long-term management. A recent study (Fletcher et al., 2006) assessed
currently available information, technologies, and resources, developed for peaceful applications, which can be utilized for plant pathogen forensics. The authors
also prioritized activities and resource expenditures needed to enhance our plant
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pathogen forensics capabilities. Strategies needed for a comprehensive national
microbial forensic capability, to determine the source of the pathogen and provide evidence for attribution, include (1) assuring high stringency of investigative technologies (validation, confidence, statistical significance, consistency);
(2) tracing pathogen origin and movement; (3) identifying the timing and site
of initial introduction; (4) identifying the perpetrators; (5) collecting evidence
for criminal attribution; and (6) forming linkages with the law enforcement and
security communities.
One of the most pressing gaps, because it impacts all the others, is the
need for greater communication, cooperation, and coordination between and
among federal agencies, academic institutions, and industry. Each of the agencies and entities contributing to national agricultural security has a unique mission and specific goals for which it is accountable to its stakeholders, and each
is responsible for different elements of an outbreak response. Currently, there is
no single entity, such as the Centers for Disease Control and Prevention (CDC)
or a national center, to ensure strategic planning for future preparedness and the
most effective and efficient response to a plant pathogen emergency. To be effective, this coordinating function should be established at a level above individual
agencies. The coordinating entity would not duplicate or unnecessarily overlap
the diverse elements of a robust national biosecurity plan because most of these
responsibilities are charged to existing components of government. It would focus
on strategic planning, program reviews, and coordination of activities among
federal agencies, private entities, and academia; prioritization of research and
education needs for allocation of limited resources; database and pathogen collections; and coordination of public relations.
Conclusions
Our nation’s agricultural industry is strong and our food supply is among
the safest in the world, but vulnerabilities do exist. Recent initiatives in various
branches of government, academia, and industry have enhanced the security of
our plant resources, but gaps and needs remain. Fortunately, the actions needed
to sustain and protect our plant resources from intentional pathogen introduction,
and to recover from deliberate plant disease outbreaks, will also enhance the effectiveness and productivity of normal U.S. agricultural enterprises. For example, in
addition to the threat of intentional introductions of exotic plant pathogens and
pests, new pathogen species or races emerge naturally. Globalization of markets,
unprecedented international travel, and changes in climate from various causes
all contribute to an increased likelihood that pathogens will move across national
borders and employ adaptive strategies in response to exposure to new environments. Let us use the opportunities provided by these challenges to strengthen our
agricultural production systems, and ensure that our nation continues to lead the
world in providing food that is abundant, reliable, nutritious and safe.
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SURVEILLANCE STRATEGIES
PLANT BIOSECURITY INFRASTRUCTURE FOR
DISEASE SURVEILLANCE AND DIAGNOSTICS
James P. Stack, Ph.D.14
Kansas State University
Jacqueline Fletcher, Ph.D.15
Oklahoma State University
Introduction
The vital role of plants in society is not well understood by the general population or by most policy makers. Healthy plant systems are a prerequisite to the
health and welfare of human and animal systems, and are essential to the economies of developed nations. Human, animal, and plant systems are intricately
linked; the intersection of these three systems forms the basis of our economy,
our culture, and our standard of living. The emerging one-medicine concept of
holistic health that encompasses animal and human systems is rational and obvious when we consider the value inherent in these systems and the impact that
zoonotic diseases have had over the past 50 years (Dudley, 2004; Karesh and
Cook, 2005; Potter, 2004). However, we must expand that holistic one-medicine
concept to include plant systems.
When we assess value within our primary living systems, it is appropriate
that human systems have the most value, animal systems second, and plant systems third. However, plant systems are the foundation of all three. Plants generate
the oxygen we breathe. They are the food we consume directly and the feed we
provide to the animals we consume. They are the fibers that clothe us and the
timber that shelters us, and they are becoming the fuels that power the technologies associated with our high standard of living. They stabilize our ecosystems
and beautify our landscapes. Plants have great aesthetic value and great economic
value. Healthy plant systems are vital to our national economy and consequently
to our national security. The stability of societies and economies depends on the
health of plant systems (Diamond, 2005). Therefore, we must protect our natural
and agricultural plant systems to ensure the sustainability of our food production
systems and ultimately our society.
A Biosecurity Framework
A national strategy for plant biosecurity must be comprehensive with respect
to science and policy and must address issues of infrastructure, technology, and
14 Biosecurity
Research Institute.
Institute for Microbial Forensics & Food and Agricultural Biosecurity, and Department
of Entomology and Plant Pathology.
15 National
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education. One conceptual approach to the development of plant biosecurity infrastructure is based on a simple outbreak model. In its simplest form, this model
includes the following components: the source of the outbreak agent; the introduction of the agent into some new environment; the detection of that agent at some
point after the introduction event; the accurate diagnosis of the new agent at some
point after the detection event; the response to the outbreak; and the resolution of
the outbreak. Each component requires a unique strategy for preparedness: potential introductions require a prevention strategy; detection requires a surveillance
strategy; diagnosis requires a technology strategy; response requires a communications and mitigation strategy; and resolution requires a recovery strategy.
Prevention
The U.S. Departments of Agriculture (USDA) and Homeland Security (DHS)
share responsibility for preventing the introduction of new plant pathogens and
insect pests that threaten our plant systems. This is accomplished through the
activities and programs of Customs and Border Protection (CBP) and USDA’s
Animal and Plant Health Inspection Service Plant Protection and Quarantine
(USDA-APHIS-PPQ). Due to the extremely large and increasing volume of
imports of plants and plant products, port and border inspections can never be 100
percent effective in preventing the accidental or intentional introduction of new
agents. The increase in Internet-based commerce further adds to this challenge
by providing a means to circumvent the inspection and quarantine process associated with interstate and international trade. Consequently, we must anticipate
the introduction of agents that threaten our plant systems, whether accidental due
to global trade, intentional due to terrorism or crime, or natural due to weather
events (e.g., hurricanes).
A prevention strategy should include the capability to intercept those agents
with a high probability of introduction and establishment. Several lists of highconsequence pathogens and pests have been generated by government agencies
and scientific societies. One such list identified more than 500 plant pathogens
and nematodes and over 700 insects and mites that pose threats to U.S. plant
systems (Huber, 2002). We lack the resources necessary to develop specific plans
for over 1,200 organisms. Because there is no defining set of characteristics
to determine which threat agent will become established and cause significant
damage, a prioritization process is needed to identify those high consequence
agents with the greatest potential to cause persistent, wide-scale damage such
that specific interception protocols are required. For example, if a new race of a
pathogen emerged with the potential to destroy over 50 percent of the U.S. wheat
crop, its characteristics indicate that the pathogen will establish and spread, there
are no effective management tools, and pathways for pathogen introduction exist,
then a comprehensive preparedness, response, and recovery strategy should be
developed for that specific pathogen.
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97
Surveillance, Detection, and Diagnosis
An Institute of Medicine study identified six critical elements necessary to
a food safety system (IOM, 1998). These same six elements would provide the
framework for biodefense against threats to national food security (King, 1999).
Among those elements was a comprehensive surveillance and monitoring system. This element is as important for plant-based systems as it is for human and
animal systems.
For the purposes of this paper, surveillance is the process of searching,
detection is the process of finding, and diagnosis is the process of determining
and/or verifying what is found. The National Plant Diagnostic Network (NPDN)
was established by USDA in 2002 to provide the necessary critical infrastructure
to facilitate early detection and rapid diagnosis of disease and pest outbreaks in
natural and agricultural plant systems (Stack et al., 2006). This is accomplished
through the primary mission areas of building infrastructure for diagnostics and
communications and through training and education programs that target first
detectors and diagnosticians.
Surveillance and detection We should assume that introductions will continue to occur as a result of global trade and the increasing threats of intentional
introductions due to bioterrorism and biocrime. If the projections for increased
trade and climate change are accurate, it is quite possible that the frequency and
severity of introductions will increase.
Our current surveillance and detection systems vary significantly according
to plant system, target pathogen or pest, and geographic region. Funding for
surveillance of plant systems is most often allocated for specific target agents;
consequently, those programs are executed only in areas at risk. Because of limited funding, general surveillance at the field level is minimal. For some plant
systems, industry has implemented very effective surveillance programs, and the
data are provided to APHIS. Mechanisms to share data are being explored.
Among the major limitations to an effective surveillance system is not having enough trained personnel in the field. Unlike human and animal systems, in
which doctors and veterinarians are distributed throughout rural and agricultural
areas, few plant doctors with diagnostic expertise operate at the local level with
plant-based systems. NPDN, in collaboration with Cooperative State Research,
Education, and Extension Service (CSREES), APHIS, the Extension Disaster
Education Network, and the Regional Integrated Pest Management (IPM) Centers, has developed a training and education program targeting first detectors at
the local level. Its registry of trained first detectors may serve as a resource for
outbreak management.
Diagnosis NPDN was established to provide a triage system for the rapid
and accurate diagnosis of introduced plant pathogens and insect pests. Because
of a decline in national and local support for plant diagnostics over many years,
state labs varied tremendously in diagnostic infrastructure and experience. With
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global infectious disease surveillance and detection
funding from USDA, NPDN has rebuilt and enhanced much of that infrastructure
and implemented programs to train diagnosticians in the latest diagnostic technologies (Stack et al., 2006).
Morse identified three elements for an effective early warning system; clinical recognition, epidemiological investigation capability, and laboratory capacity
(Morse, 2002). NPDN has become an integral component for early warning and
NPDN labs provide surge diagnostic support during outbreaks.
NPDN has created a national database for the diagnostic data collected at the
network labs. An NPDN epidemiology group is developing data analysis tools
that include syndromic analysis. Many of the issues and challenges associated
with syndromic surveillance in human systems (Stoto, 2005; Stoto et al., 2004)
also apply to plant systems. Because there are many natural introductions in plant
systems, syndromic surveillance might prove to be a useful approach. Coordination and communication among all the disciplines will be important.
Response
Response to plant disease outbreaks resulting from new pathogen introductions is a responsibility of USDA APHIS. For most introductions, APHIS provides the leadership for a coordinated response that often includes APHIS-led
rapid deployment teams, state departments of agriculture, industry, and in some
cases, land grant university diagnostic labs. An elaborate structure exists within
APHIS for the development of response plans to high-consequence pathogens
and pests.
NPDN, in partnership with APHIS and state departments of agriculture, has
developed and implemented a training exercise program to facilitate preparedness for outbreak response. All 50 states have participated in at least one exercise
involving local, state, and federal governments, as well as state, regional, and
national diagnostic labs. The exercise scenario makes clear the roles and responsibilities of all participants. After the exercise scenario, action reports are analyzed
to identify areas in need of improvement.
Recovery (A Superficial Treatment)
Recovery, which follows response, is the strategy by which to return a system
to the preevent mean or to a new, but stable, mean. An effective recovery strategy
will be comprehensive in nature and include short-term plans that address the
transition from response to the new system mean, while long-term plans will need
to address prevention and recovery from subsequent introductions. The scope
of recovery plans vary as a function of the scale of the outbreak and the ripple
effects throughout the national and global economies. While response revolves
around outbreak delineation, containment, eradication, and management, recovery is focused on local and system-level issues, including ecological impacts,
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SURVEILLANCE STRATEGIES
production shortfalls, effects on transportation systems, impacts on trade agreements, market reentry strategies, and replacement markets or systems.
Mandated by Homeland Security Presidential Directive 9 (HSPD-9), the
National Plant Disease Recovery System (NPDRS) was established within the
USDA Agricultural Research Service. NPDRS has involved other federal agencies (e.g., APHIS and CSREES), state departments of agriculture, scientific
societies, and universities in the development of national response plans for the
Select Agents and other high-consequence pathogens.
Among the challenges of an effective plant disease recovery strategy will
be to find cost-effective solutions for low profit margin systems. Deriving a
cost–benefit premium that achieves sustainable plant systems without significantly raising the percentage of the U.S. income spent on food or without causing
irreversible ecosystem damage will be challenging. One goal for such a strategy would be establishing mechanisms for national cooperation among public
and private sectors and international cooperation that facilitates collaboration
without compromising trade. The true cost of risk reduction is not known. More
effective predictive models for invasiveness, impacts, and recovery outcomes
will be needed.
To date, NPDRS has focused on response plans. The challenge for NPDRS
will be to transition into the development of recovery strategies in the face of
increasing introductions that call for more response plans.
Challenges
The Select Agent Paradox
The Select Agent program includes a requirement for the identification of
high-consequence plant pathogens and toxins having a reasonable potential to
cause significant ecological or economic damage and the potential for deliberate
introduction. Once a pathogen is designated as a Select Agent, strict laws regulate
its possession, handling, and dissemination. Responsibility for managing a plant
disease outbreak caused by a Select Agent resides with APHIS. If it is suspected
or determined that the introduction was intentional, then the Federal Bureau of
Investigation would share primary responsibility.
The original Select Agent list for plant pathogens included 10 pathogens
(see Fletcher and Stack earlier in this chapter). Since its adoption, at least four
of these agents have been introduced into the United States either accidentally
as a result of trade (Ralstonia solanacearum, Liberobacter asiaticus, Plum pox
virus) or naturally as a result of a weather event (Phakopsora polysora) (Stokstad,
2004). Two of those agents are now considered to be endemic and were removed
from the Select Agent list. Once removed from the list, the management of the
threat agent shifted from primarily a federal responsibility to primarily a state
and local responsibility.
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global infectious disease surveillance and detection
The utility and effectiveness of the Select Agent program should be reviewed.
At best, it reduces the potential for an accidental escape from a domestic lab and
impedes the illicit acquisition of a viable culture or toxin preparation from a
domestic lab or commercial culture collection. At worst, it precludes achieving a
state of preparedness at the state and local levels. Pathway analyses indicate that
for most of the Select Agents, there is an equal or greater probability of being
introduced accidentally or naturally than intentionally. If these agents are truly
the organisms of greatest concern, we should be encouraging many of our scientists to conduct the research necessary to ensure that we can detect them quickly,
diagnose them correctly, and respond effectively to minimize the potential negative impact. If working with these agents is too difficult for U.S. scientists then
we will not be building the necessary expertise for the organisms that pose the
greatest threat to the country. A reevaluation of the goals and effectiveness of the
Select Agent Rule should be executed with specific reference to the unintended
consequences that impair preparedness and response.
Animal and Plant Health Inspection Service
The authority for regulating high-consequence plant pathogens and insect
pests resides within APHIS. Responsibilities include providing emergency
response to outbreaks; issuing permits for interstate transport and international
importation of pathogens and pests; coordinating national and regional pest surveys; providing training programs; and developing and validating diagnostic protocols. Most of these tasks are time sensitive and resource intensive, sometimes
with significant legal ramifications. Yet, among the USDA agencies, APHIS has
historically received the least funding. Its level of support seems disproportionate
to its responsibility. If we are to develop and maintain a national state of preparedness in the face of increasing plant pathogen and pest introductions, increased
support within USDA for APHIS and increased support within APHIS for plant
programs will be necessary.
Sampling
Sampling underpins the successful implementation of every strategy on
which a successful biosecurity program depends. A sampling protocol depends
on the characteristics of the target agent, the environment in which it exists, and
the matrix from which it is to be sampled. Consequently, much effort should be
applied to the development and validation of the methods deployed. However,
the extremely large number of potential threat agents in plant systems precludes
implementation of a comprehensive sampling strategy for each agent. Therefore,
more general sampling strategies are needed that increase the probability of
interception for a wide array of agents.
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Formulating and implementing a national strategy for recovery from single
or multiple introductions to plant systems is a challenge beyond the mission
of any single agency or department. It will require the coordination of several
government departments at the local, state, and federal levels; public and private
educational institutions; and the many industries that support plant systems in the
United States. As has been identified for zoonotic disease surveillance (Dudley,
2004), a central body with responsibility for plant disease health that would
develop a national strategy does not exist.
Summary
There are many challenges to achieving plant biosecurity within the United
States and across the world. The success of U.S. agriculture has made possible
a high standard of living with a safe, inexpensive, and dependable food supply
system. But it has also left us complacent with respect to food production. Educational programs are needed to increase awareness among the general population
and among policy makers regarding the interdependence of plant, animal, and
human systems. Appropriately, human systems have the greatest value in society
and require the greatest investment of our time and resources. Sustenance of
healthy human and animal systems requires healthy plant systems. Having less
value does not mean having little value.
The world at the beginning of the 21st century is vastly different than it
was at the beginning of the 20th century. Among the challenges to sustainable
living systems are globalization, climate change, population growth, and bioterrorism/biocrime. There is neither a single strategy nor a single technology that
will ensure the security of our living systems. The benefits of globalization are
tremendous, but so too are the risks if we do not prepare for the consequences
with respect to emerging diseases of humans, animals, and plants. Consequently,
all nations must be secure if any nation is to be secure. Through modern transportation systems and international commerce, some of the natural barriers (e.g.,
oceans) to the dispersal of pathogens have been circumvented or eliminated.
Most plant pathogens once took decades to disperse naturally around the world.
Through normal commerce it may now take only a few days to a few weeks.
Two introductions of the Select Agent Ralstonia solanacearum r3b2 in 2003 and
2004 from Kenya and Guatemala, respectively, are good examples. The threat of
intentional introduction could reduce that dispersal interval to one day.
Historically, pathogens have moved naturally and accidentally among nations
around the world. However, the rate of their border crossings has increased dramatically, resulting in drastically reduced time to prepare for an introduction.
International cooperation is essential to achieve plant biosecurity. The importance
of global management of disease outbreaks to minimize large-scale impacts was
justified effectively for animal and human diseases (Karesh and Cook, 2005).
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The same case can be made for plant diseases. Many of the plant pathogens that
have caused epidemics in North America over the past 150 years were introduced
from Africa, Asia, Europe, and South America. Intuitively, the health and stability
of plant production systems in the United States depends on good plant surveillance systems in other parts of the world. Improved cooperation among nations
is required for prevention and rapid outbreak intervention.
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Surveillance Networks
OVERVIEW
As several of the contributors to this chapter note, clinical surveillance of
infectious disease is inadequate in much of the developing world due to limited
funding for public health infrastructure. Because many impoverished regions are
also at high risk for emerging disease threats, alternative methods of surveillance
are crucial to global health. The papers collected in this chapter describe a variety
of electronic surveillance networks, designed to gather and integrate information
on infectious disease from a variety of nontraditional sources (e.g., Internet sites,
news outlets, observers with little or no medical training) and to disseminate
alerts broadly and rapidly.
The chapter begins with a description of the first infectious disease surveillance network, ProMED-mail. Stephen Morse, one of the network’s founding
members, provides a brief history of the free, nonprofit, noncommercial, moderated e-mail list that today serves over 37,000 subscribers in more than 150 countries, as well as anyone with Internet access. Since it began as an experimental
system in 1993, ProMED-mail has helped to demonstrate the power of networks
and the feasibility of designing effective, low-cost global reporting systems. It
has also encouraged the development of additional electronic surveillance networks—such as the Global Public Health Information Network (GPHIN) and
HealthMap, described in subsequent contributions to this chapter—and the World
Health Organization’s (WHO’s) “network of networks,” the Global Outbreak
Alert and Response Network, or GOARN (see Summary and Assessment).
The chapter’s second paper, by presenter Abla Mawadeku and coauthors from
GPHIN, offers descriptive comparisons of that network along with ProMED-mail
107
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global infectious disease surveillance and detection
and the European Commission’s Medical Intelligence System (MedISys), which
is available only to European Union member states. GPHIN, a primary source of
electronic surveillance for WHO, also serves a host of government institutions,
nongovernmental agencies and organizations, academic institutions, and private
companies, who pay between 30,000 and 200,000 Canadian dollars per year in
subscription fees, depending on the specific services provided.
HealthMap is a freely accessible, automated network that collects information from multiple web-based data sources on infectious outbreaks (currently
news wires, Really Simple Syndication (RSS) feeds, ProMED mailing lists, and
EuroSurveillance and WHO alerts). The network then organizes and displays this
information in real time as graphic “maps” featuring geography, time, and infectious disease agent. In their contribution to this chapter, workshop presenter John
Brownstein of Harvard Medical School and his colleagues at Children’s Hospital
Boston discuss their efforts to evaluate the HealthMap system with reference
to four characteristics that have been used to evaluate syndromic surveillance
systems: data acquisition; information characterization; signal interpretation; and
dissemination. The authors’ preliminary evaluation of HealthMap according to
these criteria appears to demonstrate that the aggregation of multiple sources of
data—each potentially biased or otherwise flawed—increases the sensitivity and
timeliness of alerts while reducing false alarms.
The concluding paper of the chapter describes a different sort of electronic
surveillance network: one powered by cell phones, enabling observers in some
of the world’s most remote and impoverished communities to report disease
outbreaks. The authors are workshop speakers Pamela Johnson of Voxiva, a
company that provides information technology to establish surveillance networks
in low-resource settings, and David Blazes, of the U.S. Naval Medical Research
Center Detachment in Lima, Peru, which used an Internet- and cell phone-based
electronic system developed by Voxiva to support disease surveillance by the
Peruvian navy along that country’s coast and remote rivers. This experience is
presented as a case study in surveillance and evaluated according to the Centers
for Disease Control and Prevention (CDC) guidelines for public health surveillance systems. The authors also share lessons gleaned from six years of building
surveillance systems, based on cell phones and other cost-effective information
technologies, for use in low-resource environments.
Workshop participants raised a series of issues in response to the presentations upon which the papers in this chapter are based. A detailed account of this
discussion appears in the Summary and Assessment section, “Considerations for
Surveillance Networks.” Discussants were especially concerned about the potentially devastating economic consequences to a country—particularly a developing
country—of being labeled (accurately or inaccurately) as harboring a feared infectious disease. In his contribution to Chapter 4, speaker Will Hueston assesses the
tradeoff between health and development inherent in the release of surveillance
information such as HealthMap’s geographic depictions of outbreak reports.
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GLOBAL INFECTIOUS DISEASE SURVEILLANCE AND EARLY
WARNING SYSTEMS: PROMED AND PROMED-MAIL
Stephen S. Morse, Ph.D.
Columbia University
A number of emerging infections have appeared throughout the world
in recent years (Morens et al., 2004; IOM, 1992, 2003; Morse, 1995). Or, in
the words of Marci Layton (New York City Department of Health and Mental
Hygiene), we must learn to expect the unexpected. It is widely agreed that one of
the most important measures for both emerging and existing infectious diseases
is an effective early warning system, that is to say, global infectious disease
surveillance. Here, I will discuss ProMED, the nonprofit international Program
for Monitoring Emerging Diseases, and its best known progeny, ProMED-mail
(PMM). ProMED itself was founded in 1993 to design and help implement
global surveillance systems that could detect both known and emerging infections
(Morse et al., 1996).
A Brief History of ProMED and ProMED-Mail
ProMED had its roots in the same Institute of Medicine (IOM) report that
led to the development of the Forum on Microbial Threats (IOM, 1992). The
Committee that developed the 1992 IOM report was chaired by Joshua Lederberg
and the late Robert E. Shope. After the report was released, there was considerable concern about maintaining the momentum. Many of the original Committee
members (including me) believed the problem required long-term attention. In
addition, for specific reasons the charge to the IOM Committee and consequently
the report were limited to the United States. However, there was a clear need
to consider these infections as global threats that would require international
solutions. In an attempt to fill what many (including this author) saw as the
fragmentation of disease surveillance systems and the lack of global capacity,
ProMED was begun in 1993 under the auspices of the Federation of American
Scientists (FAS).
Several years earlier, I had been asked by Barbara Hatch Rosenberg, then
chairing a working group on biological nonproliferation issues at FAS, to provide
technical advice for her working group. After the 1989 National Institutes of
Health (NIH) meeting on emerging viruses and the 1992 IOM report, Rosenberg
and I discussed the possibility of developing an initiative for global infectious
Mailman
School of Public Health.
article on the early history and activities of ProMED is available at http://www.fas.org/faspir/
pir1293.html, with an update at http://fas.org/promed/announce.htm. Additional materials are available at http://fas.org/promed/.
An
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global infectious disease surveillance and detection
disease surveillance, with start-up resources from FAS. Dorothy Preslar served
as the project staff at FAS.
The group held a small initial organizational meeting in February 1993 at
The Rockefeller University in New York. In addition to Rosenberg, and myself
as Chair, among those present at that meeting were Ruth Berkelman (then at the
Centers for Disease Control and Prevention, or CDC), Scott Halstead (then at the
Rockefeller Foundation), D. A. Henderson (then at Johns Hopkins and the U.S.
Department of Health and Human Services), James M. Hughes (then at CDC),
John LaMontagne (then at NIH’s National Institute of Allergy and Infectious
Diseases, or NIAID), and Shope (then at Yale). At that time, it was decided that a
conference would be held in Geneva in fall 1993, that the group’s purview should
include animal and plant diseases in addition to human disease (a view especially
advocated by Berkelman), and that the group should be named ProMED (Shope
suggested the name).
The next activity was a conference, cosponsored by FAS and the World
Health Organization (WHO) and held on September 11 and 12, 1993, at WHO
headquarters in Geneva. Part of the challenge at that time was that the thenDirector General of WHO did not believe that surveillance for infectious diseases
was part of the organization’s core responsibilities. Unfortunately, many clinicians and most of the lay public naïvely believed otherwise, and thought that
WHO was already doing it.
The September 1993 ProMED meeting, co-chaired by Francis Nkrumah of
Ghana and myself, was held in the WHO Executive Board Room, and included as
speakers a number of people who had been influential in WHO affairs, including
Jan Kostrzewski, a former chair of the WHO Executive Board, Henderson, and a
number of members of the World Health Assembly. At that event, 60 prominent
scientists and public health officials working on human, animal, and plant health
from all parts of the world met, unanimously endorsed the concept of global
surveillance, and formed ongoing working groups to assess present capabilities
and develop and implement plans for a suitable global program that could address
both known and emerging infections. We also invited John P. (Jack) Woodall
(then at WHO) onto the Steering Committee, and James LeDuc (then at WHO,
seconded from CDC) agreed to serve as a special consultant.
One would think it should be fairly simple to strengthen and network regional
centers of excellence to augment official systems and develop mutual cooperation, whether through WHO (preferably) or through regional intergovernmental
organizations. On the other hand, if diseases can emerge anywhere, how can one
get early warning from literally everywhere? The latter seemed the harder task,
so we decided to try tackling what everyone considered the easier one first. At
meetings in Geneva and elsewhere, we recommended developing a coordinated
The
list of the early Steering Committee members can be found at http://fas.org/promed/about/
steering.html.
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system of regional centers and a minimum set of capabilities to identify and
respond to unusual disease outbreaks. A plan was subsequently published (Morse
et al., 1996), in part elaborating on the system Henderson had proposed at the
1989 NIH/NIAID meeting on emerging viruses (Henderson, 1993). The strategy
developed was vigilance for unusual clinical presentations of special concern
(e.g., encephalitis or acute respiratory distress with fever in adults); a minimum
set of microbiological capabilities at each site to identify common diseases; and
a system to refer unidentifiable samples to successively more sophisticated reference laboratories, through the network, for possible identification. The plan also
included epidemiologic capacity, which could be provided rapidly through the
network if needed (Morse et al., 1996).
The effort continued with meetings at other places. At a Steering Committee
meeting in June 1994 at Airlie House in Virginia, we realized that our members
from all over the world had no reliable means to communicate with one another.
Nkrumah of Ghana, for example, had a Telex, which in any major American city
usually required a trip downtown to a special office building to send, but no fax
machine. In Russia, they had fax machines but no fax paper because of a lack of
money. We decided to try to put everyone on a common communications system. Charles Clements, then at a nonprofit organization called SatelLife, which
specialized in inexpensive e-mail connections for remote and underserved areas
through satellite radio links, had been invited to the meeting. I appointed Woodall
as head of a new Communications Task Force. By the end of the meeting a plan
had been developed to connect everyone by e-mail. SatelLife provided connectivity for places without e-mail connections, for example (at that time) in Africa,
China, and Russia. The rest of us learned how to use the existing e-mail systems
at our institutions (quite an ordeal in those days). Thus ProMED-mail was born.
Although only about 10 years ago, it was another era technologically.
As the system developed and people started using e-mail for communications, we realized it could also be used as an international outbreak reporting
system. (So much for deferring those “more challenging” goals, such as how
to get reports from everywhere.) Woodall and I served as the initial moderators
(or “editors”), a time-consuming task. Woodall deserves tremendous credit for
his dedication and enormous contributions to the subsequent development of the
system. Since 1995, the system has been available on the Web, as well as by
e-mail subscription. The partnership between ProMED and SatelLife continued
fruitfully until 1999, when the ProMED reporting network was transferred to
the International Society for Infectious Diseases (ISID), headquartered at
Harvard’s Channing Laboratory in Boston. The communications network was
renamed ProMED-mail, to distinguish it from other ProMED activities then
underway.
See
http://www.promedmail.org.
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global infectious disease surveillance and detection
ProMED-Mail: A Prototype Infectious Disease Reporting System
Many people think of PMM as synonymous with ProMED, as it has taken on
a robust life of its own. PMM was designed as an open reporting and discussion
system. It is a nonprofit, noncommercial e-mail list that now has some 40,000
subscribers, with over 165 countries represented. Not all of them, of course, send
in reports because the editors would be overwhelmed, but many subscribers do
read the e-mails on a regular basis. Although numbers vary, incoming e-mails
(roughly 100 a day) generate an average of 7 to 10 reports every day.
The e-mail listserv is moderated, which means that messages coming in
are first read by people with scientific or medical expertise. Originally this
was Woodall and at times me until I left for government service in 1996. As
the list grew, a number of other moderators were recruited in various specialty
areas, and the system is fortunate to have a number of distinguished experts as
moderators.
In principle, subscribers send in reports and information. Rapporteurs take
additional responsibility to report regularly in their own geographic or special
interest areas. Rapporteurs report from Russia, China, and a number of other
places as well as within the United States. When someone sends in a report
from somewhere (one of the earliest reports of Ebola in Kikwit, Zaire, now the
Democratic Republic of Congo, came from a medical missionary who had a radio
e-mail link), the report is assigned by the editor-in-chief or someone acting in
that capacity, to the appropriate moderators for editing and, if appropriate, posting to the list. The moderator reads the report for scientific plausibility. If the
report looks credible, the moderator edits and formats as needed, probably adds
comments to put the item in context, and send it out as a posting to the list. All
subscribers are free to comment or add information after reading the posting.
In addition to the full list, which includes outbreak reports and discussions
on human, veterinary, and plant diseases, there are several sublists for those
who want only certain parts of this information. It is possible to subscribe to the
animal and plant disease lists separately. The human disease list includes both
human and animal disease. This causes occasional complaints from physicians,
but we have believed strongly from the beginning that it is essential to improve
the connections between animal and human health. Justifying this is the fact that
many emerging infections are zoonotic. Those who are interested in getting only
the breaking news, without the ensuing discussion, can subscribe to the Emerging
Disease Reports (EDR) sublist. I get EDR on my BlackBerry wireless device.
In recent years sub-lists have been developed in Portuguese, Spanish, and
Russian, and there is interest in developing other foreign language lists as well.
Some of the regional reports of wide interest are translated into English.
The PMM architecture is simple. Technically, the e-mails are 7-bit ASCII
text, the most basic format. When the system was started in August 1994, people
in developing countries had very limited bandwidth. It is amazing how much
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113
this has changed in the past decade, with broadband Internet cafes now even in
remote areas.
The editors also search the Web and press reports, an increasingly important source of information. This strategy was originally adopted by GPHIN (the
Canadian government’s Global Public Health Intelligence Network), which is
described in another chapter. GPHIN was started in 1999 and is based largely on
news sources from the Web. Unfortunately such material was not available when
PMM was started. Since then, the explosive growth of the Web and of improved
methods for searching have made such strategies very effective.
Perhaps one of the most important value-added features of PMM is the distinguished and hard-working team of moderators or editors (for this chapter, I am
using these two terms interchangeably). Although they are essentially volunteers,
all are subject-matter experts. The moderators also have their own e-mail lists and
personal networks for follow-up, which demonstrates the power of networking.
Larry Madoff is the current editor-in-chief of PMM, while Woodall (now associate editor) remains as active and involved as ever. He has had a critical role in
developing PMM into what it is today. Eduardo Gotuzzo, in addition to being a
member of the IOM Forum, is Chair of the PMM Policy Committee.
All this is probably obvious to anyone who has read PMM. Anyone can contribute; data come from clinicians (those proverbial astute clinicians in the field
all over the world), public health officials and epidemiologists, lab scientists, or
medical missionaries, but also journalists and interested laypeople.
There was a concern initially that the method of obtaining data would give
rise to many rumors that health authorities would then have to verify, expending
valuable resources. This has not turned out to be a major problem. Of course,
sometimes information is incorrect, but in general the reliability turns out to
be more than 95 percent, according to figures that Madoff tabulated. However,
PMM has developed several mechanisms to deal with the possibility of erroneous reports. One is personal follow-up by moderators. The moderators, experts
in their fields and generally well connected, can use their own personal networks
to try to get more information to include. Second, an uncertain report could also
be posted as a request for information (RFI), an inquiry which is simply a way
of asking people if they have more information they can contribute. Others on
the network may also spontaneously add to or correct a posting if they have
additional facts.
Subsequently, WHO, in response to information from PMM and GPHIN,
developed a very effective mechanism of its own, called the Outbreak Verification List. WHO sends this list out regularly to a limited group of public health
officials and scientists to try to follow up on various outbreak reports. It is a sign
of WHO’s increasing capacity and interest that the reports increasingly are coming from WHO’s own country and regional representatives. WHO has developed
its own network of networks, the Global Outbreak Alert and Response Network
(GOARN), which includes a number of formal and informal sources. It should
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global infectious disease surveillance and detection
be noted that the situation at WHO has greatly improved in the last few years,
thanks to the concerted efforts of a number of people, including James LeDuc in
the early days, and notably David Heymann more recently.
One particularly interesting aspect of a system like PMM is that it can be
used to compare reports from a number of places. In addition to outbreak reporting, it provides the ability for people to recognize that what they are observing
may be happening elsewhere, too. An initial report may encourage others to
contribute local information that may help to estimate the extent and numbers of
an infectious disease outbreak, and to monitor spread. One example was a 1995
outbreak of meningococcal meningitis occurring simultaneously in several states
and in the United Kingdom. The outbreak became evident when the reports from
various places appeared on PMM.
PMM has been available on the Web since the Ebola outbreak of 1995 in
Kikwit, when it partnered with and later incorporated an independent effort
called “Outbreak.” As the Web itself grows, the website has had an increasing
presence. If one prefers not to receive e-mail alerts, it is a simple matter just to
search the website and read any of the reports. The Web archives include some
of the earliest reports, such as the first reports of Ebola in Kikwit. Among other
PMM “firsts” was Venezuelan equine encephalitis, coincidentally in Venezuela.
It was originally denied by the government; when it was verified it led to the
resignation of the health minister. West Nile virus in 1999 was another event
PMM extensively covered. During this period, Ian Lipkin generously wrote in
to offer reagents for people internationally. Other firsts include reports of H5N1
influenza in Indonesia in November 2003 and fatalities in China in 2005 attributed to Streptococcus suis.
The first report of severe acute respiratory syndrome (SARS) that appeared
on PMM was a rumor about an unusual outbreak in south China with unexplained
deaths. Steve Cunnion picked this up, and information was posted on February
10, 2003. Shortly after that, China officially reported the disease, and WHO was
able to release information officially. By that time, China reported 305 cases.
SARS had actually been infecting people for at least several months (IOM, 2004).
SARS then spread to Toronto, where it was originally called “atypical communityacquired pneumonia” and was reported on PMM.
Madoff has tabulated the PMM disease reports over the past 10 years. Dengue, which is quite common, is one constant, as are a number of others. Many are
known conditions, but at least 209 are not. Some will eventually be added to the
known category. There have also been reports of CDC Category A agents, normally more closely associated with bioterrorism or biowarfare. However, anthrax
exists naturally throughout the world in livestock. In developing countries, there
may be thousands of cases of gastrointestinal anthrax from contaminated meat.
More than 200 cases of anthrax in livestock were reported on PMM before the
intentional anthrax attacks of fall 2001. Botulism and tularemia are also natu-
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rally occurring diseases, which reminds us that many of the classic bioweapons,
including the Category A agents, are zoonotic agents.
PMM was developed as a prototype, and continues to evolve. There have
been increasing efforts since then. GPHIN and WHO’s GOARN have already
been mentioned. A later paper, by Pamela Johnson, will discuss Voxiva, which
uses the power of networks with another technological base, the cell phone
network.
PMM has also elicited some kind comments. Henderson referred to CNN
and PMM as the major sources of information for infectious diseases. Steven C.
Joseph (formerly New York City Health Commissioner, Dean of the Minnesota
School of Public Health, and Assistant Secretary of Defense for Health Affairs)
referred to PMM as “the CNN of infectious diseases” (Personal communication,
S. C. Joseph, June 1995). Perhaps the most intriguing characterization comes from
Steven Johnson, in his book The Ghost Map, about cholera in Victorian London.
A sentence in the book caught me by surprise as I was leafing through it:
The popular ProMED-mail e-mail list offers a daily update on all the known
disease outbreaks flaring up around the world, which surely makes it the most
terrifying news source known to man (Johnson, 2006).
For an infectious disease surveillance system, that seems high praise indeed.
Since PMM was started as an experimental system more than a decade ago, it
has helped to demonstrate the power of networks and the feasibility of designing
widely distributed, low-cost reporting systems, and it has encouraged the development of additional systems using additional technologies. All these efforts help
to begin building the heavily networked surveillance systems that will be needed
to deal with threats in an increasingly globalized and unpredictable world.
Acknowledgments
Sincere thanks to Jack Woodall and Larry Madoff for their hard work and
helpful discussions, and to all the editors/moderators and funders of ProMEDmail for their dedication and good work. Stephen S. Morse is supported by
CDC cooperative agreements A1010-21/21, U90/CCU224241 (Centers for Public
Health Preparedness), and U01/CI000442, the Arts & Letters Foundation, and
by NIH/NIAID cooperative agreement 5U54AI057158 (Northeast Biodefense
Center RCE).
A
list of current PMM personnel is at http://www.promedmail.org; click on “Who’s Who.”
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GLOBAL PUBLIC HEALTH SURVEILLANCE: THE ROLE OF
NONTRADITIONAL SURVEILLANCE TOOLS
Abla Mawudeku, M.P.H.
Public Health Agency of Canada
M. Ruben, M.D., Ph.D.
Public Health Agency of Canada
R. Lemay, B.Sc., M.B.A.
Public Health Agency of Canada
Introduction
In a world deeply interconnected by traveling and trade, the spread of infectious agents is inevitable. Regions once isolated are now integrated into the global
community and have the risk of being exposed to infectious agents that they previously were unexposed to, as well as sources of old and new agents, and even
new pandemics. Therefore, there is global concern about surveillance and control
of diseases (particularly infectious diseases) around the globe.
Any global surveillance system has to overcome several challenges; basically,
it requires a good system for communications to and from the field to get timely
collection, analysis, and dissemination of data, and to be able to force political
decisions and allocation of resources. However, susceptibility to infectious diseases and increased risks of infection are usually associated with poverty, and
poverty is more frequent in those countries where epidemiological and laboratory
surveillance is defective or nonexistent (Heymann and Rodier, 2001). In addition,
while several countries, particularly in the Western world, have already national
surveillance systems to monitor for potential public health threats, in many circumstances these systems are inadequate, fairly erratic, or too disease specific
to identify new diseases early (Butler, 2006). Also, countries have been reluctant
to report outbreaks due to the perception of a negative impact of such news on
the country’s economy (trade and tourism). Public alarm, sometimes fueled by
the press, has resulted in many occasions in important losses for the countries,
which then try to hide or delay the recognition of the presence of human or animal
diseases (Cash and Narasimhan, 2000). Nevertheless, the electronic era, in which
press reports and the Internet keep societies informed and interconnected, have
begun to break down all attempts of “secrecy.”
Currently there is no comprehensive global public health surveillance system. The World Health Organization (WHO) is the only organization that has the
mandate to monitor and respond to global public health threats, as established
Chief.
Scientist.
Senior
Surveillance Officer.
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SURVEILLANCE NETWORKS
in the International Health Regulations (IHRs). WHO not only uses information
gathered from traditional surveillance systems but also uses information from
nontraditional surveillance systems to leverage in order to capture a more comprehensive outlook of the situation about potential public health threats occurring
worldwide. The use of nontraditional surveillance systems has contributed to the
improvement of epidemic intelligence used for the early detection of potential
public health threats. This has enabled WHO and other public health organizations such as the European Center for Disease Control (ECDC) to better assess,
investigate, and respond to events of concern (Figure 2-1).
A revised version of these regulations, IHR 2005, will be implemented in
June 2007. These new IHRs will strengthen WHO’s authority in surveillance and
response because they include more demanding surveillance and response obligations and apply human rights principles to public health interventions (Baker
and Fidler, 2006). The new regulations require that member countries report to
Event-based surveillance
EWRS
MS
DSNs
EWGLI
Enternet
EISS…
BSN
EMEA, EFSA
MedISys
GPHIN
WHO-OVL
ProMED
OIE
FAO
…
Indicator-based surveillance
Report
Data
Capture
Filter
Verify
Collect
Analyze
Interpret
Signal
Assess
Disseminate
Public health alert
Investigate
Control measures
DSNs
BSN
Laboratory network
EWRS
MS
Commission
Other healthrelated EU
agencies
WHO-IHR?
FIGURE 2-1 Epidemic intelligence framework.
EWRS = Early Warning Response System; MS = messaging system; DSN = disease surveillance network; EWGLI = European Working Group for Legionella Infections; EISS
= European Influenza Surveillance Scheme; BSN = Basic Surveillance Network; EMEA
= European Agency for the Evaluation of Medicinal Products; EFSA = European Food
and Safety Authority; WHO-OVL = Outbreak Verification List; OIE = Office International
des Epizooties (World Organization for Animal
2-1 Health); FAO = Food and Agriculture Organization; EU = European Union; and Enter-net is an established and thriving EU-wide
network for the laboratory-based surveillance of human Salmonella and Verocytotoxinproducing Escherichia coli (VTEC) infections.
SOURCE: Based on Kaiser et al. ��������
(2006).
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global infectious disease surveillance and detection
WHO “all events which may constitute a public health emergency of international
concern” (i.e., unexpected or unusual public health events that might include
communicable and noncommunicable disease events, whether natural, accidental,
or intentionally created). IHR 2005 also requires from member countries (if practicable) to report to WHO all public health risks identified outside their territories
that might cause international disease spread (Baker and Fidler, 2006). They also
give WHO more autonomy from the governments of member countries; WHO
can now use nontraditional surveillance information (i.e., data from the news
media) and ask the countries about “rumors” of circulating infectious agents.
Several innovative nontraditional surveillance systems leverage the advancements in modern Internet and information technologies to efficiently and rapidly
gather information about events of public health concern. The Global Public
Health Intelligence Network (GPHIN), the Program for Monitoring Emerging
Diseases (ProMED), and Medical Intelligence System (MedISys) are examples of
such systems that are commonly used by the public health community. All these
surveillance systems disseminate relevant reports to the public health community
in a timely manner.
Global Public Health Intelligence Network
GPHIN is an early warning system that takes advantage of existing information technology to continuously scrutinize news media sources through news
aggregators who have contracts with newspapers around the world, as well as
with health and science websites. The multilingual system gathers information
by monitoring global media on a 24/7 basis and in nine languages, including
Arabic, Chinese (simplified and traditional), English, Farsi, French, Russian,
and Spanish. More recently, Portuguese has been added. In addition, and with
the help of automated translation software, non-English articles are translated
into English, and English articles translated into French, Portuguese, Spanish,
Russian, Chinese (simplified and traditional), Farsi, and Arabic. The translations
give the essence of the news report.
The system, which has automated and manual components, searches for
information on disease outbreaks and other emerging and reemerging public
health threats (e.g., contaminated food and water, bioterrorism, chemical or
radiological threats, natural disasters) and then generates timely alerts (Figure
2-2). The automated process helps to organize and prioritize the relevant news
media reports that are reviewed and analyzed by a team of analysts who are
multilingual and multidisciplinary (Figure 2-2). The analysts work in shifts and
provide analytical coverage on a 24/7 basis. The analysts have the responsibility
of identifying events that may have serious public health consequences, and of
flagging them as alerts following preestablished criteria. The analysts also review,
periodically, the items kept in the database as irrelevant, to ensure that none of
these items represents a potential alert. In addition, the analysts are responsible
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SURVEILLANCE NETWORKS
Data collection
Advanced analytics:
Automated processes
Duplicate
elimination
Automated
gathering of
multilingual
news media
sources
Multilingual real-time intelligence
rendering
En
Fr
Metadata
insertion
Fa
Categorization
Ru
(Taxonomy )
100
Automatically published
85
1.Publish
Es
or
2. Publish with
alerts
Ar
Translation
Manual
gathering of
multilingual
news media
sources
Relevancy
score
or
Zhs
Zht
Manual analysis by
analysts
3. Irrelevant
30
Irrelevant
0
FIGURE 2-2 Global Public Health Intelligence Network (GPHIN) flow of information.
SOURCE: Public Health Agency of Canada.
for identifying trends or relationship of events, checking clarity of machine translations, and updating search syntaxes
2-2 and keywords used to monitor and gather
relevant news media reports. The users are also able to interact with the analysts
to request assistance or to provide feedback.
GPHIN is currently one of the primary sources of information for WHO.
Other GPHIN users include government institutions, nongovernmental agencies and organizations, as well as academic institutions and private companies that conduct public health surveillance worldwide. Users have access to
GPHIN through a password protected website and also receive e-mail alerts
(Mykhalovskiy and Weir, 2006).
ProMED-Mail
ProMED
offers a free public website and an e-mail list that has subscribers
from around the world (currently more than 37,000 subscribers from over 150
countries). Its mission is “to provide early warning, 7 days a week year around,
of outbreaks of emerging infectious diseases and episodes of acute toxicity, and
the spread of antibiotic and disease vector resistance, worldwide, free of charge
by e-mail” (Woodall, 2001; Woodall and Calisher, 2001). The system distributes
information about outbreaks often early on, before it is confirmed by WHO;
ProMED-mail,
International Society for Infectious Diseases, http://www.isid.org.
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global infectious disease surveillance and detection
therefore, it complements the global surveillance done by WHO and countries
(Woodall, 2001).
It allows communications by e-mail all over the world, and includes sublists
of reports in Spanish, Portuguese, and Russian, with some of the most interesting
local reports translated into English. ProMED publishes media reports, personal
reports, and summaries; it presently covers not only human diseases, but also
animal and plant diseases, and it is also available on the Web (Woodall, 2001).
Most data published by ProMED comes from individuals (clinicians, public
health officers, epidemiologists, laboratory scientists, and lay individuals) or from
academic or official organizations worldwide.
ProMED has several moderators who cover their own geographic areas (e.g.,
Russia, China) and search the Web and press reports for relevant news. These
moderators are subject-matter experts and provide their expertise as volunteers
(Mykhalovskiy and Weir, 2006); they also have their own e-mail lists and personal networks to follow up the reports, and they frequently add their comments
and their knowledge to the news.
MedISys
MedISys is a near real-time news alert automated system managed by the
Directorate General Health and Consumer Affairs of the European Commission.10
MedISys covers emerging and reemerging public health issues related to communicable diseases and bioterrorism. It monitors on a 24/7 basis approximately
800 Web sources (news and medical sites) daily in 25 languages, including the
languages of European Union (EU) member states, Arabic, and Chinese. Access
to MedISys is limited to EU member states.
Conclusions
The continuous proliferation of emerging and reemerging pathogens able
to infect humans, domestic animals, plants and wildlife seems to have increased
in the past years, helped by the increased and faster movement of people and
goods. This has generated international concern and increased efforts to improve
the early warning capacity to detect potential public health threats worldwide in
order to control and prevent the spread of diseases (Heymann and Rodier, 2001;
Formenty et al., 2006).
Today’s advancements in communication technology (e.g., blogs, wikkies),
and information technology are used liberally by the news media and the public;
this makes possible the rapid dissemination of worldwide news about events of
public health concern. Such proliferation of information has made it challenging for the public health community, with limited resources, to be aware of and
10 See
http://medusa.jrc.it/medisys/homeedition/all/home.html.
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121
analyze all the data available in an efficient and effective manner. Current early
warning tools, such as GPHIN, MedISys, and ProMED also find it challenging to
keep abreast of all the sources of information available. Therefore, the most feasible and cost-effective solution would be to establish a network of nontraditional
early warning surveillance systems in order to leverage the expertise provided by
each system. GPHIN, MedISys, and ProMED, which are complementary, could
then strengthen the mutual abilities of monitoring, gathering, analyzing, and disseminating information about events of public health concern.
In such a collaboration, ProMED’s team of experts would provide reports
of relevant events; GPHIN’s would add a team of multilingual, multidisciplinary
analysts plus its technical capacity to process high volumes of disparate multilingual data; and MedISys would add its capacity to monitor the Internet for news in
more than 20 languages, improving the gathering of information about potential
public health threats in remote areas. In addition, this collaboration would make
possible the dissemination of synthesized information (from the numerous news
sources) about relevant events, highlighting major points and strengthening epidemic intelligence. Furthermore, visualization features, like the ones provided by
the Geographic Information System (GIS), could also facilitate the epidemiological analysis of public health threats.
For such a comprehensive and ambitious network to be effective, and to reach
the entire planet, it would also need the support of the public health community
and wildlife, animal, and agricultural experts, when possible (Jebara, 2004; Butler,
2006). It also would need technologic and economic support from the private sector. It is expected that a network like this could adapt to the needs of the different
customers, and provide support to all countries, worldwide, to strengthen their
surveillance systems and be able to accomplish the mandate of the IHR guidelines.
These guidelines anticipate that each member state should assess its capability to
strengthen and maintain core surveillance capacities by 2009 and develop a plan
to accomplish this (Hardiman, 2003; Baker and Fidler, 2006).
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global infectious disease surveillance and detection
HEALTHMAP: INTERNET-BASED EMERGING INFECTIOUS
DISEASE INTELLIGENCE
John S. Brownstein, Ph.D.11
Harvard Medical School
Clark C. Freifeld, B.S.12
Children’s Hospital Boston
Ben Y. Reis, Ph.D.13
Children’s Hospital Boston
Kenneth D. Mandl, M.D., M.P.H.14
Children’s Hospital Boston
Although many developed countries are strengthening their traditional clinically based surveillance capacities, the required health information infrastructure
is lacking in parts of the world that may be most vulnerable to emerging health
threats. At the same time, an enormous amount of information providing situational awareness about infectious diseases is found in web-accessible information sources, such as Internet-based discussion sites, disease reporting networks,
news outlets, and blogs. These data also exemplify unprecedented potential for
increasing public awareness on public health issues prior to their widespread
recognition. Despite the growing use of these unstructured information sources
for monitoring emerging infectious diseases, there has been little, if any, formal
evaluation of their utility, accuracy, coverage, or timeliness. Building on established evaluation approaches for public health surveillance systems, we present
a surveillance framework that defines important challenges and critical research
questions that define a research agenda. The framework is informed by evaluation of the performance of HealthMap, a freely accessible, automated system for
real-time monitoring of online information about emerging diseases. This chapter
highlights the value of a robust research agenda, continued organic evolution of
existing and new technologies, and scrutiny through a rigorous evaluation framework to help ensure that the global public health enterprise maximally leverages
11 Instructor, Department of Pediatrics, Harvard Medical School, Children’s Hospital Boston, 1
Autumn St, Room 541, Boston, MA 02215. Phone: 617-355-6998. Fax: 617-730-0267. E-mail:
[email protected].
12 Research Software Developer, Children’s Hospital Informatics Program at the Harvard–MIT
Division of Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave.,
Boston, MA 02115.
13 Instructor, Children’s Hospital Informatics Program at the Harvard–MIT Division of Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave., Boston, MA 02115.
14 Associate Professor, Children’s Hospital Informatics Program at the Harvard–MIT Division of
Health Sciences and Technology, Children’s Hospital Boston, 300 Longwood Ave., Boston, MA
02115.
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SURVEILLANCE NETWORKS
new electronic sources for surveillance, communication, decision making, and
intervention.
Introduction
Real-time public health surveillance represents a critical tool for controlling
infectious diseases, an effort that requires a timely and global approach addressing the complex and dynamic interactions among infectious agents, animals, and
the environment (Heymann and Rodier, 1998, 2001; Woodall, 2001). Although
many developed countries are strengthening their traditional clinically based
surveillance capacities, the required health information infrastructure is lacking
in parts of the world that may be most vulnerable to emerging health threats
(Butler, 2006). The existing network of traditional surveillance efforts by health
ministries, institutes of public health, multinational agencies, and laboratory and
institutional networks has gaps in geographic coverage and often suffers from
poor information flow across national borders.
At the same time, an enormous amount of information providing situational
awareness about infectious diseases is found in web-accessible information
sources, such as Internet-based discussion sites, disease reporting networks, news
outlets, and blogs (Heymann and Rodier, 2001; Grein et al., 2000; M’Ikanatha et
al., 2006). Even web-based clickstream and keyword searching aggregated across
Internet users can provide important insights (Eysenbach, 2006). These resources
provide valuable and highly local information about disease outbreaks and related
events, even from areas relatively invisible to daily global public health efforts
(Woodall, 1997). In fact, the majority of outbreak verifications currently performed by the World Health Organization’s (WHO’s) Global Outbreak Alert and
Response Network (GOARN) initially begin as reports from informal electronic
data sources such as mailing lists and local news media (Heymann and Rodier,
2001; Grein et al., 2000).
While these web-based data sources can facilitate early detection of outbreaks, they may also support increasing awareness of public health issues prior
to their formal recognition. Through low-cost and real-time Internet data mining combined with open-source and user-friendly technologies, participation in
global disease surveillance is no longer limited to the public health community
(Keystone et al., 2001; Petersen, 2005). Furthermore, the availability of webbased media across national borders greatly ameliorates the potentially suppressive effects of political influence on the spread of information.
The HealthMap Project
Though valuable, electronic sources of emerging infectious disease news are
not well organized or integrated. We sought to develop HealthMap, a freely accessible, automated approach to organizing data about infectious outbreaks accord-
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global infectious disease surveillance and detection
ing to geography, time, and infectious disease agent (Figure 2-3) (Holden, 2006;
Larkin, 2007; Captain, 2006). HealthMap is a multistream real-time surveillance
system that aggregates multiple Web-based data sources (currently news wires,
Really Simple Syndication (RSS) feeds, ProMED mailing lists, and EuroSurveillance and WHO alerts). Information is acquired automatically through screen
scraping, natural language interpretation, text mining, and parsing to obtain disease name and geocode the location of the outbreak. HealthMap also addresses
the computational challenges of integrating multiple sources of unstructured
online information in order to generate robust meta-alerts of disease outbreaks.
Through this approach, we achieve a unified and comprehensive view of current
global infectious disease outbreaks in space and time.
System Challenges
Despite the success of Internet-based surveillance systems such as HealthMap,
important technological and methodological challenges remain. Four principal
development and deployment issues are as follows:
(1) Value. Though there is an abundance of disparate electronic resources,
none is comprehensive. Each has gaps in coverage of certain geographic areas,
population sectors, medical expertise, and availability.
(2) Standards. No universal standards exist for capturing, processing, reporting, interpreting, or sharing structured data. Such standards would greatly facilitate
the communication and use of information by computationally based systems.
(3) Performance. Metrics for systematic evaluation of these data sources and
the performance of these systems are still needed. Though there has been some
description of individual data sources (M’Ikanatha et al., 2006; Cowen et al.,
2006), there is still limited understanding of their value for spatial and temporal
detection and monitoring of disease outbreaks.
(4) Accessibility. Important issues require attention to system ownership,
target audience, restrictions, cost, and sustainability.
Surveillance Framework
A good starting point for design of a surveillance framework is the one
currently used for the syndromic surveillance systems that have evolved over
the past eight years (Mandl et al., 2004a; Buehler et al., 2004; CDC, 2000). The
anthrax attacks of 2001 gave rise to large-scale surveillance efforts directed at
early detection of an outbreak, prior to confirmed diagnosis (Perkins et al., 2002).
These novel surveillance systems also use data that are not diagnostic of a disease, but that might indicate the early stages of an outbreak, often earlier than
might otherwise be possible with traditional public health methods. The ideal
syndromic surveillance system has the following traits: it acquires data automati-
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FIGURE 2-3 Screenshot of the HealthMap system.
SOURCE: http://www.healthmap.org.
2-3
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global infectious disease surveillance and detection
cally; collects ongoing data in real time or near real time; electronically stores
and transmits data to an analytic module; has sufficient demographic, geographic,
and temporal coverage to support anomaly detection; captures data in standard
formats across data sources; protects private information and patient confidentiality; and scans for outbreaks, correctly distinguishing an abnormal pattern from
a normal or expected one (Mandl et al., 2004a). While Internet-based surveillance represents a paradigm shift from indicator-based to event-based sources of
information, the existing framework is designed to support the evaluation of all
public health surveillance systems. The standard set of evaluation metrics used
to interpret data quality and signal detection should apply across both traditional
and Internet-based surveillance approaches (Mandl et al., 2004a, b; Buehler et
al., 2004; Wagner et al., 2001). Both Internet-based surveillance and traditional
syndromic surveillance require four stages: (1) data acquisition, (2) information
characterization, (3) signal interpretation, and (4) dissemination and alerting
(Figure 2-4).
Here we present a summary of initial evaluation efforts based on this surveillance framework. To help inform our evaluation, we analyzed the HealthMap alert
data stream, over a 20-week period (October 1, 2006, through February 17, 2007),
FIGURE 2-4 Framework for Internet-based surveillance.
SOURCE: Brownstein (2006).
2-4
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applying standard evaluation metrics (volume, geography covered, diseases captured, timeliness, sensitivity, and specificity). Over this period, HealthMap found
3,194 news reports of infectious disease outbreaks (a mean of 22.8 per day, 95
percent confidence interval, 20.6–25.0).
Data Acquisition
Data can be acquired by search either of the open Web or of specific restricted
or open websites. The choice of data sources has critical implications for early
outbreak detection and disease monitoring across all metrics. Here data sources
are evaluated across three dimensions: quality, cost, and availability.
Data Quality
The ideal information sources would be sensitive to even the smallest aberrations. However, as in all surveillance activities, there is an inherent tradeoff
between the timeliness and specificity of a system. For example, local news
sources may report on strange incidents involving a few cases that would not be
picked up at the national level. However, local news reports may be less reliable,
reporting stories without adequate confirmation. Information is not always validated, and the credibility of the sources is not always vetted. Thus, without proper
filtering, these local news sources may be responsible for substantial noise in
the system and increasing the overall false alarm rate. Furthermore, other biases
may be introduced for political reasons, resulting either in disinformation (false
positives) or censorship (false negatives). In the case of ProMED, its hierarchical
curation structure helps minimize false positives. However, while expert review
does increase specificity, the required manual processing delays alert reporting.
Data Cost
Internet-based surveillance data have been limited largely to automated
mining of information from news aggregators. An important question is whether
paid subscription sites provide more value than freely available information. For
example, news aggregators such as LexisNexis®, Factiva®, and Magenta News®
may all be useful sources of information, especially for local news in a substantial
number of languages. However, free online news aggregators, such as Google
News and Yahoo News, potentially integrating up to 10,000 sources, may have
almost equal value.
The use of free data means that these systems may be provided at minimal
cost to the public and to countries that lack the resources to pay high subscription rates. For paid data, cost-effectiveness of various data sources becomes an
important issue. Data for HealthMap are acquired strictly through free news
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global infectious disease surveillance and detection
sources. Whether these data sources differ substantially from paid sources is the
subject of future evaluation.
Data Availability
The time interval at which these sites are updated can have critical implications for the efficacy of the public health response. Ideally the source should
provide timely reports. In reality, media reporting may be guided by external
factors such as a weekly health/science section or unrelated news events that
might delay reporting. For example, news volume is strongly affected by day of
the week, with high volume on Fridays and low volume on Sundays.
News media reports may also be subject to bias about which diseases are
covered. Our evaluation found that the richness of pathogen reporting across
news sources was substantial, with 66 unique infectious diseases reported through
Google News in the 20-week period (Table 2-1). However, we found that distribution of reports across pathogens (or pathogen evenness) was low, with a
substantial skew toward reporting of outbreaks of avian influenza and norovirus.
The more skewed distribution in the news sources is expected given the tendency
for the media to focus and sustain reporting on stories of public interest. We also
TABLE 2-1 Top Infectious Disease Alerts from the
HealthMap System, October 1, 2006–February 16, 2007
Disease Reported
Total Number
of Reports
Avian influenza
E. coli
Norwalk-like virus
Salmonellosis
Influenza
Dengue fever
Herpes
Cholera
Undiagnosed
Gastroenteritis
Pertussis
Rift Valley fever
C. difficile
Staphylococcal disease
Diarrhea
Legionellosis
Tuberculosis
Malaria
Chickenpox
Measles
661
492
242
217
169
133
118
81
78
46
52
46
33
32
29
28
28
26
25
25
SOURCE: http://www.healthmap.org.
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found that news outlets often picked up more common seasonal and endemic
conditions (e.g., epidemic influenza, dengue, E. coli, Salmonella). This is in
contrast to the ProMED system that explicitly avoids reporting on endemic infections—such as tuberculosis and HIV—or vaccine-preventable diseases (Madoff,
2004).
Geographic coverage of data sources also merits quantitative evaluation (Figure 2-5). During the evaluation period, 88 countries had reports of infectious
disease outbreaks, with the greatest reporting from the United States (n=1,346),
Canada (n=235), and the United Kingdom (n=226). Given that the analysis
included only English-language news sources, the skew toward English-speaking
countries is not surprising. However, it is also clear there is a bias toward reporting from countries with larger populations (e.g., China), numbers of media outlets,
public health resources, and availability of electronic communication infrastructure (approximated by number of Internet hosts).
Future Work in Data Acquisition
Gaps in population and geography covered by news sources need to be
understood and adjustments need to be made. For example, important gaps in
media reporting exist in tropical areas, which also have the greatest burden of
infectious diseases. Monitoring other Internet-based sources such as blogs, discussion sites, and listservs could complement news coverage. In particular, the
use of clickstream data and individual search queries is a promising new surveillance source (Eysenbach, 2006). Ultimately, informal news-based sources should
be considered as part of a comprehensive multistream surveillance system that
provides an integrated view of global health information.
Characterization
Although free and unrestricted websites have large quantities of useful information about infectious diseases, the information is not well organized. News
media output usually comes as unstructured free text, making analysis of the
geographic and temporal relationships between different reports and data sources
difficult. Automated disease and geographic location grouping is usually accomplished through natural language interpretation and automated text mining and
parsing. Search criteria can include disease names (scientific and common),
symptoms, keywords, and phrases. Once gathered, automated approaches for
initial filtering often require human verification.
Classifying Information
Extracting a pathogen name from a free text report presents a number of
formidable challenges. In HealthMap, we draw from a continually expanding
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FIGURE 2-5 HealthMap geographic coverage, October 1, 2006–February 16, 2007.
SOURCE: Brownstein (2006).
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dictionary of pathogens (including both human and animal diseases) to organize
unstructured and semistructured disease outbreak alert information. Locations are
extracted by matching geographic names with a master table of latitude and longitude coordinates of centroids of certain geographic areas, including countries,
provinces/states, and cities. In addition to reasonable performance and scalability,
a key advantage to this pattern dictionary approach is that it is translated relatively
easily to other languages: A different dictionary can be plugged in easily to the
existing architecture. A language expert is needed to perform the initial translation, refine the pattern library, help with capitalization and punctuation subtleties,
and provide other adaptations, but the basic approach can be re-applied without
major changes to the system. Furthermore, the language expert needs to have
minimal technical knowledge with respect to natural language syntax or software
development to contribute to the library.
Although effective for rapid matching, a number of hurdles need to be overcome. First, in the case where a word may have multiple spellings, for example,
diarrhea (common in the United States) and diarrhoea (common in the United
Kingdom), we stock the dictionary with multiple patterns for a single pathogen.
While look-up time does not increase substantially with the addition of patterns
to the dictionary, the disadvantage of the dictionary approach is that it requires a
priori knowledge management and allows identification only of locations and diseases already present in the database. Similar challenges exist for identifying the
precise geographic location of an outbreak, as geographic names and borders are
subject to change. The expansion and editing of the database requires extensive
and careful manual data entry. Another limitation of the look-up engine is that
it ignores pattern context. A good illustration is the use of “plague” in reports—
often news articles use it metaphorically, such as “Problems continue to plague
New Orleans cleanup effort.” If the look-up engine matches the word “plague”
alone, it will mark this alert as an outbreak of Yersinia pestis in Louisiana. We
mitigate this problem by including “to plague,” “a plague,” and other similar
strings as null patterns in the library so that the classifier will mask them.
Rating Information
Clearly, the article text contains the best indicators about the locations and
diseases of the event in question. However, blindly searching the text, while
increasing sensitivity, leads to excessive false positives. To mitigate this problem,
we process the input in stages: If the classifier cannot identify location and disease from the initial input provided by the feed, namely the modified headline, it
can request more text from the feed. For example, in the case of the Google News
aggregator, the system examines the headline, then the description, which usually
consists of the first one or two sentences of the article, and finally the publication name. Frequently, a publication in one area refers to events in another area,
making the publication name and location an unreliable source for the location
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of the alert. However, articles that do not refer to a well-known location, such
as “Suburban school closed after flu outbreak,” generally refer to a location near
the publication headquarters. By processing the input in stages, we reduce the
false positives of the first case while including more of the true positives of the
second case.
Future Directions in Data Characterization
Future work must focus on improving natural language processing capability to clearly identify the pathogen, filter nonpertinent reports and duplicates,
and enhance the spatial resolution of location. Ideally improvements in how
the source information is reported would vastly enhance characterization. For
example, structured annotation on the attributes of an outbreak by the article
author or source publication would remove the problems inherent with natural
language processing. However, given that data standards for news reporting are
not likely to be implemented in the short term, advanced text processing methodologies such as fuzzy matching and neural networks could have an important role
in enhancing current systems. Furthermore, reliance on an external geocoder with
consistently updated databases of geographic locations may be a better solution
(Croner, 2003). Although machine learning techniques are undoubtedly important, human analysis still has tremendous value, as exemplified by the Global
Public Health Intelligence Network (GPHIN) (Mawudeku and Blench, 2006)
and ProMED (Madoff and Woodall, 2005). The success of Wikipedia has shown
that leveraging collaborative human networks of trained public health professionals (such as ProMED subscribers and international groups of experts) could
be an ideal mechanism for classification, severity assignment, conflict resolution,
geocoding, and confirmation of reports on outbreaks of rare or even infectious
diseases of unknown identity (Giles, 2005).
Interpretation
While issues of acquisition and characterization have been addressed by many
systems, methods for interpreting these data are for the most part underdeveloped.
Current systems aggregate Internet-based news resources, but are limited in terms
of analytical tools available to the user. Development has been geared toward
knowledge management, where news on infectious disease is aggregated and
reorganized. Because of the magnitude of information collected, users could, over
time, become overwhelmed with an increasing number of false alarms. Thus, there
is a need to move from simple knowledge reorganization to an analytic approach
for disseminating timely yet specific signals. A number of strategies are available
to reduce the false alarm rates in these inherently noisy data sources.
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Multistream Interpretation
False alarms often can be reduced by thorough aggregation and crossv alidation of reported information on a particular disease outbreak. The motivation for such a meta-alert is based on the idea that multiple sources of information
on an incident can provide greater confidence in the validity or reliability of the
report than any one source alone. In HealthMap, the severity of a meta-alert is
calculated as a composite score based on: (1) the reliability of the data source
(e.g., increased weight to WHO reports and less weight to local media reports);
and (2) the number of data sources, with increased weight to multiple types of
information (e.g., discussion sites and media reports on the same outbreak).
For evaluation of multistream surveillance to be effective, basic characteristics such as sensitivity, specificity, and timeliness of different news source types
need to be quantified (Wagner et al., 2001; CDC, 2001; Reis and Mandl, 2003a;
Brownstein et al., 2005b; Bloom et al., 2007). In our evaluation, we used officially confirmed outbreaks obtained from WHO Outbreak News, available in the
public domain, as a “gold standard” indicator of an infectious disease outbreak
(WHO, 2007). We measured key detection characteristics of Google News reports
for 12 focused outbreaks over the 20-week period. Mean timeliness for Google
News, defined as the time between detection by the surveillance source and report
by WHO, was 12 days. However, actual timeliness varied widely from 102 days
earlier to 59 days after the WHO report. For example, a diarrheal outbreak in
Ethiopia was detected by the media nearly three weeks before the WHO report.
In contrast, a plague outbreak in the Democratic Republic of the Congo and a
Chikungunya outbreak in India were only reported in the media once the official
WHO report was released. Sensitivity, defined as the proportion of WHO alerts
detected by news data, was moderate, with 58 percent of the alerts reported in the
news. In contrast, we identified 267 unique alerts (country–disease pairs) from
Google News, revealing a high volume of reporting. Given that only a subset of
outbreaks is posted to WHO Outbreak News, the specificity of news data could
not be calculated given the current data sources. Without a better gold standard
of validated outbreaks, assessing false positives is difficult.
Statistical Interpretation
The value of news reports can be measured similarly to traditional surveillance data sources used for outbreak detection, where the goal is to distinguish
an abnormal pattern from a normal or expected one. Statistical methods for
outbreak detection include temporal pattern models such as statistical process
control (SPC) (Hutwagner et al., 1997) and autoregressive moving average models (ARIMA) (Reis et al., 2003), spatial models for geographic cluster detection
(Kulldorff and Nagarwalla, 1995; Brownstein et al., 2002; Olson et al., 2005),
and spatiotemporal patterns for detecting space-time interactions (Kulldorf et
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al., 2005). To apply these to monitoring Internet news sources, we must define
the baseline patterns and thresholds of reporting for which no action is required.
In this case, we expect a baseline level of random noise in news media reports
generated by case definitional issues, surveillance bias, and overreporting. The
generation of statistical signals therefore can be based on a set threshold of report
volume defined by modeling this baseline. Models can include factors such as
cyclical patterns (day of week, month, seasonal effects) and autocorrelation (Reis
and Mandl, 2003b; Brownstein et al., 2005a), as well as geographic and temporal biases of news reporting. Thresholds would be set by evaluating the tradeoff
between signal quality and timeliness.
Future Directions in Data Interpretation
Future work in modeling and data integration should also be directed at
improving risk assessment. For example, signals from unstructured online information sources can be integrated with other health indicator data to provide a
broader context for the alert. Pertinent datasets include mortality and morbidity
estimates, population density and mobility, and pathogen seasonality and transmissibility (Wilson, 1995; Altizer et al., 2006; Dowell and Ho, 2004; Grassly and
Fraser, 2006; Fraser et al., 2004). With the increasing importance of vectorborne
and zoonotic diseases (Gratz, 1999; Dobson and Foufopoulos, 2001; Brownstein
et al., 2004), consideration also should be given to inclusion of ecological data
such as distribution of arthropod vectors and animal host reservoirs, as well as
environmental predictors including climate and vegetation (Brownstein et al.,
2003; Colwell et al., 1998; Kitron, 1998). Combining these informal sources with
clinical and laboratory surveillance data should also be an important next step.
Such integration could yield a relevancy score for the report, define populations
at risk, and predict disease spread.
Dissemination
An important final consideration is how information from Internet-based systems should be disseminated. Clearly a critical audience is public health officials
interested in real-time updates of infectious disease status in their geographic
region. However, whether these systems should be freely available and open to
the public is an area of active debate. Travelers, for example, may have a keen
interest in up-to-the-minute knowledge about infectious disease activity at their
destination. For the general population, obtaining integrated real-time coverage
of a disease emergency is particularly challenging given disparate news and alert
sources. An unrestricted sentinel system dedicated to the aggregation and geographic display of current outbreaks could fill this information gap.
On the other hand, unrestricted access to this information could have severe
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economic impacts on the countries affected by the disease alerts. The risk is
especially elevated with fully automated systems that may not have the benefit of
informed human judgment. However, even with careful controls, any system can
generate spurious alerts. User restrictions may be the only way to guard against
unwarranted damage (Cash and Narasimhan, 2000). Furthermore, an open access
model might not be economically sustainable. GPHIN depends on subscription
fees to make any necessary improvements to the system. In contrast, HealthMap is
based on freely available data and is open to the public. However, a tiered approach
such as the one used by MedISys (Medical Intelligence System) where general
information is provided to the public based on free resources and more detailed
information pertinent to public health officials (including geographic detail) is
provided by paid subscription may represent a reasonable compromise. Information
access is a key consideration for the future development of these systems.
Another critical question is who ultimately should oversee these systems and
manage the information collected, especially given that issues of trust and reliability are paramount. At the moment, systems are being developed by international organizations, governments, and academic institutions. The current linkage
between surveillance by GPHIN and public health response by WHO’s GOARN
presents a very appealing approach. An initiative at Google.org, called the International System for Total Early Disease Detection (INSTEDD) project, aims to
develop a system that increases the number of languages and data sources available through GPHIN (Delamothe, 2006). INSTEDD could become a transparent
and publicly available resource independent of any government agency. How such
a system would be linked with existing public health infrastructure should be an
area of active consideration.
Conclusions
The growing use of informal electronic information sources highlights an
important paradigm shift in disease surveillance, expanding beyond traditional
public health systems. Although Internet-based informal sources on outbreaks
are becoming a critical tool for global infectious disease surveillance, important
challenges still need to be addressed. In particular, an unavoidable pitfall of a
system-of-systems approach is that it is inherently subject to the limitations of
the primary data collected by the individual component systems. Our preliminary
evidence-based evaluation of HealthMap suggests that aggregation of multiple
sources may counter this limitation by increasing sensitivity and timeliness while
reducing false alarms, in that assessments are not based on any single news outlet
alone. Because many of the places with the least technological adoption also carry
the greatest infectious disease burden, future system development should also
specifically address the digital divide to achieve more uniform and comprehensive
global coverage. A robust research agenda, continued organic evolution of existing and new technologies, and scrutiny through a rigorous evaluation framework
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global infectious disease surveillance and detection
will help ensure that the global public health enterprise maximally leverages
new electronic sources for surveillance, communication, decision making, and
intervention.
Acknowledgments
This work was supported by R21LM009263-01 and R01LM007970-01 from
the National Library of Medicine, the National Institutes of Health, and grant
number 200510MFE-154492 from the Canadian Institutes of Health Research.
USING CELL PHONE TECHNOLOGY FOR INFECTIOUS DISEASE
SURVEILLANCE IN LOW-RESOURCE ENVIRONMENTS:
A CASE STUDY FROM PERU
Pamela R. Johnson, Ph.D.15
Voxiva
David L. Blazes, M.D., M.P.H.16
Naval Medical Research Center Detachment
Summary
Basic routine health surveillance has been largely unachievable in most of
the developing world because of inadequate funding and public health training,
especially in resource-limited parts of Africa, Asia, and Latin America. Considering that many emerging diseases with pandemic potential first occur in the
developing setting (e.g., severe acute respiratory syndrome, or SARS and H5N1
avian influenza), enhanced surveillance systems in these countries must become
high priorities for safeguarding global public health. This presentation reports
on an innovative model using a cell phone- and Internet-based reporting system
that has been developed and tested to extend disease surveillance by the Peruvian
Navy along the coast and remote rivers of Peru. Alerta DISAMAR—the name
given to the system refers to the Health Department of the Peruvian navy—has
been fully operational in Peru since 2003. More than 600 individuals have been
trained and have used an Internet- and cell phone-based electronic system developed by Voxiva to report routinely from 42 land-based sites and 19 ships. More
than 80,000 cases and 31 outbreaks have been reported. Alerta DISAMAR represents a sustained, large-scale effort that leverages cell phones and related tech15 Co-founder
16 Director,
and Executive Vice President.
Emerging Infections Program, Lima, Peru.
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nological innovations to strengthen disease surveillance. Because mobile phone
networks are expanding so rapidly across the developing world, this model has
important lessons for strengthening disease surveillance in other low-resource
environments.
Background
The low-resource environments of most developing countries pose a particular challenge to global efforts to establish effective infectious disease surveillance
and detection. There is little question that these countries are important to global
surveillance. “Out of every 100 persons added to the population in the coming
decade,” Zlotnik wrote, “97 will live in developing countries” (Zlotnik, 2005).
Figure 2-6 shows countries sized in proportion to their populations. It shows how
significant the share of the world’s population is in China, Brazil, Nigeria, subSaharan Africa, and other countries in the developing world.
Infectious disease is disproportionately represented in these countries. Many
new and emerging infectious diseases—including SARS, H5N1, HIV/AIDS—
trace their origins to these often densely populated environments. However,
despite their demographic and epidemiologic significance, most developing countries, where microbial threats to global health are most likely to emerge, also
possess the weakest surveillance systems. The Government Accountability Office
(GAO), in a global review of surveillance systems, noted that:
Developing country systems are a weak link in the global surveillance framework. Surveillance systems in industrialized and developing countries suffer
from a number of common constraints, including a lack of human and material resources, weak infrastructure, poor coordination, and uncertain linkages
between surveillance and response. However, these constraints are more pronounced in developing countries, which bear the greatest burden of disease and
are where new pathogens are more likely to emerge, old ones to reemerge, and
drug-resistant strains to propagate. Weaknesses in these countries thus substantially impair global capacity to understand, detect, and respond to infectious
disease threats (GAO, 2001).
Over the past decade, a number of important efforts have been made to use
information technology to strengthen surveillance systems. Most have taken place
in developed countries where computers and Internet connectivity are readily
available. In addition, e-mail and the Internet have had a major impact in facilitating the growth of global networks such as the World Health Organization’s
(WHO’s) Global Outbreak Alert and Response Network (GOARN), ProMEDmail, and a number of global disease-specific surveillance networks (Heymann
and Rodier, 2004).
Despite the evident importance of information technology (IT) in these
Copyright © National Academy of Sciences. All rights reserved.
broadside
FIGURE 2-6 Distribution of the earth’s population.
SOURCE: Worldmapper (2007). See http://www.worldmapper.org.
Reprinted with permission. © Copyright 2006 SASI Group (University of
2-6
Sheffield) and Mark Newman (University of Michigan).
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examples, IT has yet to realize its full potential for strengthening the surveillance systems of countries in the developing world. Even where computers exist,
inadequate power and lack of Internet coverage outside major towns and cities
has meant that in most developing countries routine surveillance systems are still
largely paper based, and transmission is slow. Health officials in capital cities and
towns may be easily linked to global networks and colleagues in other major cities, but communicate less easily with health facility staff in their own countries.
Until recently, there was no practical, measurable way to bridge the digital
divide between the cities and the poor and rural areas in these countries, where
most of the population lives. Nonetheless, a major recent review of disease
priorities led by The World Bank holds out a vision of the future of disease
surveillance:
Public health agencies, ministries of finance, and international donors and organizations need to transform surveillance from dusty archives of laboriously collected after-the-fact statistics to meaningful measures that provide accountability
for local health status or that deliver real-time early warnings for devastating
outbreaks. . . . Information technology and informatics can help in attaining
this vision . . . technology can facilitate the collection, analysis, and use of
surveillance data, if data standards are developed and compatible systems are
established. . . . technology such as cell phone-based systems could accelerate
collection of key data (for example, occurrence of a viral hemorrhagic fever
outbreak) (Nsubuga et al., 2006).
The explosive growth of mobile telephone networks in the developing world
is already a dramatic success story. According to the International Telecommunications Union (ITU), Internet connectivity is growing at a good pace, but the
reality is that cell coverage is growing much faster. In the developing world there
are 1.2 billion phones and a million new mobile phone subscribers every day.
Approximately 80 percent of people who live today are within reach of a mobile
phone signal, according to the ITU. Half of all households will have phone access
in the next decade, and 90 percent of the world will be covered by 2010. In Latin
America, there are more than 270 million mobile phone users today. The industry
estimates that within the next 3 years, 75 percent of people in Latin America will
own a cell phone. Africa shows the most dramatic growth. Over the past 5 years,
growth has averaged nearly 60 percent a year, with nearly 76 million subscribers
at the end of 2004.
Voxiva was founded in 2001 to find practical ways of using information technology for health and development in low-resource environments. We reviewed
a variety of pilot projects that were seeking to extend the benefits of the Internet
using a variety of individual devices, including personal digital assistants (PDAs)
and satellite dishes. However, we did not find any practical, measurable, and
sustainable strategy to support data collection and communication with points
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global infectious disease surveillance and detection
of service. It was and in many countries remains a paper-based world, with few
benefits of IT reaching large scale.
Voxiva’s founders recognized the potential of the growth of cellular networks
to develop a measurable, sustainable approach that could support public health
and development. Working with a variety of public health agencies, including
health officials in the U.S. and Peruvian navies, Voxiva developed innovative software that allows health professionals to enter and access data using the Internet,
a cell phone, or other devices. The software makes it possible to write a survey
and to make that survey available in multiple formats so users can use the tools
they have and the most convenient, cost-effective means to respond.
Figure 2-7 illustrates the approach that Voxiva has taken to optimize the
use of the existing infrastructure of personal computers (PCs), Internet, cell
phones, fixed phones, pay phones, PDAs, smart phones, and paper to create networked data collection and communications surveillance systems in low-resource
environments.
Over the past six years, we have learned a number of lessons for building IT
systems for use in low-resource environments, leveraging cell phones and other
forms of information technology.
Building on Available Infrastructure
The global mobile phone network is increasingly the most important globally
deployed communications infrastructure that covers the developing world. As fast
growing and highly successful local businesses, telecommunications companies
provide global infrastructure for data transmission and communication that is
inherently sustainable. As a result, the health sector no longer needs to build and
maintain its own infrastructure to transmit data and support communication with
its network of health facilities.
Hardware is also increasingly available. Health ministries, states or provinces, and increasingly districts have computers and at least intermittent Internet
access. In addition, the dramatic expansion of mobile phone usage has put a
simple “terminal” within the reach of many if not most health workers—one that
can be used to enter data, respond to surveys sent by text messages, and send and
receive alerts. Providing a toll-free number that people can call with their own
mobile phones is a quicker and cheaper approach to expanding a surveillance
network than buying, equipping, maintaining computers, and paying for power
and Internet access for all health facilities.
By building on this global telecommunications infrastructure and available
hardware, it is possible to rapidly create large-scale integrated networks that can
do basic reporting without large-scale new investments in acquiring, installing,
and maintaining technology. Over time, the infrastructure will grow—but most
countries already have enough hardware to begin.
As one example, Voxiva was able to support the national scale-up of
Copyright © National Academy of Sciences. All rights reserved.
Cell
phone
PDA/
smartphone
Phone
Pay
phone
Paper
Local
applications
Copyright © National Academy of Sciences. All rights reserved.
FIGURE 2-7 Being able to enter and access data from any available communications channels can optimize the use of existing infrastructure.
SOURCE: Voxiva. Reprinted with permission of Voxiva.
PCs/
Internet
SAMPLE DATA
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Rwanda’s national HIV/AIDS program with a monitoring system that allows
health facilities to report program indicators and register new patients. Without
any new investment in hardware, Rwanda was able to rapidly increase its electronic reporting system from 12 facilities to 146 sites. Ninety percent of the sites
report program indicators and register patients using the phone. They use their
own cell phones, call a toll-free number—the first in Rwanda—log in using their
password, and enter basic data digitally using the keypad. Over time, more and
more sites will get computers and Internet connectivity, but the program was able
to reach national coverage rapidly without waiting.
Multiple, Redundant Technologies
We have found that no single solution or hardware works in all environments, for a variety of reasons. Power is a major constraint, especially in the most
remote environments and poorest countries. The cost of connectivity remains
high in many countries. Maintenance and support for computer hardware and
software are costly and in short supply. Actual needs for bandwidth and analytic
power vary depending on how users are using the data collected. For many needs,
paper records will be the base system. Having the choice of different electronic
devices means that one can optimize the use of available hardware and allows
health professionals to enter and access data using the access means they have.
This also creates redundancy: If the Internet is not available, it is still possible to
do basic reporting via the phone.
Electronic Data Capture at the Source
Paper systems rely on copying information at the source, relaying it, then
entering and aggregating information at higher levels; this system of data transmission is error prone and makes it difficult to trace data and cases back to their
source. If data can be entered and confirmed at the source, this in itself can
enhance quality. If data can be transmitted to a central database, reviewed and
approved at higher levels (e.g., at the district level), and also be made rapidly
available to others who need it, the burden and risks associated with entering data
multiple times are reduced.
Rapid Transmission of Data
Most surveillance systems rely on physical transmission of data via mail
or “sneaker net” with people bringing the forms to a monthly meeting or on a
periodic visit. More urgent information is transmitted via individual phone or
radio calls and recorded centrally. Electronic transmission data can cut the time
and cost required for transmission dramatically. Although this is important for
routine surveillance, it is even more vital for an event, such as a serious outbreak
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or pandemic, when the situation on the ground could change rapidly. Electronic
submission of data in near real-time information could help decision makers
make much better decisions about allocation of resources in a situation of rapid
change.
Shared Database, Role-Based Access
If data are collected at the source and transmitted to a core database, organizations can make that data available to authorized users according to the specific
roles they play. For example, the same set of data could be viewed in a variety
of ways:
• Health staff can get confirmation that their report has been received,
notification of cases of interest from neighboring locations, and results of a case
investigation;
• A district health official could see reports from health clinics and posts
immediately—then edit or approve them;
• Senior health officials could review aggregate data;
• Surveillance officers could get lists of nonreporting sites; and
• Outbreak investigation teams or vaccination teams could get short message service (SMS) or e-mail alerts about suspected cases of measles or potential
outbreaks.
Data, collected once and transmitted to a central database, can be used many
times. Furthermore, data can be presented in standard templates, basic reports,
and maps or exported for additional analysis.
Communication Plus Feedback
An extended electronic network can also facilitate communication and feedback that is vital to the supervision and motivation of a distributed network.
Automated messages can be sent by multiple means—e-mails, text messages,
voice mails, alerts—and accessed through the available technology.
Build Human Capacity
Information technology alone is no silver bullet. Building a surveillance
system in any environment requires an investment in the training staff at all levels. Well designed information systems can help, with tools such as validation
rules, reminders, and online access to guidelines and training materials. Such
tools could be even more helpful in situations where health staff are not well
trained. However, the best designed system cannot detect disease or respond to
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an outbreak without the right processes and people; at its core, a surveillance
system will always be about the people who use it. The role of technology should
be to empower networks of clinicians, nurses, and other health workers to fully
participate in this important enterprise of global disease surveillance.
The same technological approach leveraging cell phone technology is being
used for a variety of purposes. It has been used for syndromic surveillance in
schools in San Diego and Washington, DC. It has been tested in the Canete
Valley in Peru and in Baghdad and Basra, Iraq, and is being developed with
the Ministry of Agriculture in Indonesia to create a system to strengthen animal
surveillance. In Latin America, it is being used to monitor national HIV/AIDS
programs, track adverse events, and support public safety (Olmsted et al., 2005;
Curioso et al., 2005).
Alerta DISAMAR: A Case Study in Infectious Disease Surveillance
Background
In fall 2001, at a time when other events in the world raised awareness of
microbial and other threats, there was an outbreak of P. falciparum malaria at a
remote naval base in the Amazon jungle basin of Peru that led to several deaths.
As in some other countries, the existing surveillance system was underdeveloped
and primarily paper based; it was not unusual for reports to take a month to get
to authorities in Lima.
Primed by these events, the Peruvian navy, the U.S. Naval Medical Research
Center Detachment in Lima, and the Peru-based office of Voxiva developed a
joint project. In January 2003, they initiated Alerta DISAMAR, a novel electronic
disease surveillance system. This experience in implementation has been exciting
to observe from the ground up, and this case study describes some of the lessons
learned during deployment of this surveillance system in Peru.
Pandemics by definition involve the global dissemination of disease. Military
populations historically have been involved in the dissemination of a number of
infectious diseases, including their well-documented role in the spread of H1N1
influenza in 1918–1919 (Oxford et al., 2005). There are also examples from
antiquity of troop movement roles in the spread of smallpox, cholera, measles,
syphilis, and plague (McNiel, 1977). More recently, high rates of HIV infection
have been seen in sub-Saharan African militaries, and this population certainly
contributes to ongoing transmission (Whiteside and Winsbury, 1996). Despite the
known risks of disease transmission among highly mobile armed forces, these
groups remain among the most poorly tracked populations in many developing
nations. The combination of undersurveilled military populations and dangerous
transmissible diseases seems the perfect recipe for a pandemic.
Military personnel are a very good population to place under surveillance for
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emerging infectious diseases (Chrétien et al., 2007). They serve as ideal sentinel
populations due to their expeditionary mission, their frequent travel to remote
locations, and their interactions with local populations.
A number of challenges exist in implementing an electronic disease surveillance system, some cosmopolitan and some unique to resource-limited settings.
The dubious observer may even ask if conducting surveillance in a resourcelimited setting is even feasible when the potential pitfalls and challenges often
seem insurmountable. The first challenge is to create a system that is complementary and not duplicative of existing surveillance systems. Creation of parallel
surveillance systems can paradoxically lead to the failure of both the established
and the new systems because limited funds and effort can be diluted between the
two systems with neither functioning effectively (Nsubuga et al., 2006). Second,
one must convince the stakeholders in the population under surveillance that their
efforts are useful and their valuable time is not wasted. To accomplish this, one
must make sure that meaningful data are returned to the end users of the system,
and in a timely fashion so that consequential action may be taken to limit the
effect of a disease or condition. An example might be the timely detection of
an influenza outbreak in a closed facility where case isolation, enforcement of
hand/cough hygiene, and antiviral chemoprophylaxis may limit the spread of this
contagious illness.
Additionally, a disease surveillance system in the developing setting must
be cost-effective, with few recurring expenses in order to assure sustainability.
Many countries in the developing world have limited funds to spend on public
health, and these are often exhausted in responding to crises rather than invested
in preventive strategies. Finally, a disease surveillance system in the developing
setting must be able to function in remote locations and austere conditions.
With regard to the situation in the Peruvian navy, we focused our attention
on a population that was not under surveillance, and applied novel technology in
the attempt to create a model that could be disseminated to other resource-limited
settings worldwide. Furthermore, in establishing this surveillance system, we
have attempted to change the culture within this population to approach disease
characterization and transmission from a broader perspective, that of epidemiology and public health.
The System
The Alerta electronic disease surveillance system uses a countrywide network of health-care facilities that encompasses more than 95 percent of the
population of the Peruvian navy and its civilian dependents in most regions of
Peru (over 120,000 people). Some of these sites are tertiary care facilities in the
capitol city of Lima, but the majority are smaller, more remote, and less capable
clinics that exist throughout the country. Figure 2-8 shows a typical clinic site in
one of the austere areas where this system functions.
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FIGURE 2-8 Health-care personnel collect data.
SOURCE: Jose Quispe, Peruvian Navy. �������������������������������������
Reprinted with permission from NMRCD.
2-8
The network consists of 43 fixed sites throughout Peru and 19 ships both on
the coast and on rivers in the jungle (Figure 2-9). The sites use a diverse range
of reporting techniques, with 12 sites routinely reporting by radio relay, 27 by
telephone, 15 by Internet, and 8 by telephone or Internet.
Data flow from individual clinics to the central operations hub in Lima. The
actual data flow from the field is described in Figure 2-10. Data are collected on
standard clinical forms during patient encounters, then entered into the system by
nurses or physicians via cell phones, toll-free public telephones, or by Internet if
accessible. Several extremely remote sites are beyond the cellular footprint, and
in these, the Peruvian navy personnel use a radio phone to relay data to the next
nearest site that has either a cell phone or access to public phones or the Internet.
Occasionally, satellite phones are used if they are available to enter data through
the toll-free telephone system.
The data collected through this system are often the only systematic representation of the epidemiology of diseases within the Peruvian navy. This has
allowed baseline levels of disease to be set, and allocation of scarce resources to
be assigned based on rational data rather than assumptions. The system collects
rates of the 29 reportable illnesses for the Peruvian Ministry of Health (MoH) as
well as some militarily relevant cases such as training-related injuries. The data
generated by this system are invaluable to both the Peruvian navy and the MoH
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147
FIGURE 2-9 Alerta network.
SOURCE: Dr. Carmen Mundaca, Naval Medical Research Center Detachment (NMRCD).
Reprinted with permission from NMRCD.
because they report disease rates from areas2-9
of the country where the MoH does
not have a significant presence.
The data are captured and displayed in real time on a web-based platform.
Several automated outputs are generated so that feedback is given almost immediately to the stakeholders in this process, either by electronic mail or short message service (SMS) messaging to cellular phones. Features include automated
outbreak detection via algorithms, graphical representation to assist clinicians,
and baseline trends.
Copyright © National Academy of Sciences. All rights reserved.
Copyright © National Academy of Sciences. All rights reserved.
Mobile cell phone alerts
Data available in real time
2-10 broadside
Outbreak detection
Evaluation of the system
Enter data by phone, Internet, or radio daily and
biweekly according to the disease
FIGURE 2-10 Data flow from the field.
SOURCE: Dr. Carmen Mundaca, NMRCD. Reprinted with permission from NMRCD.
Baseline trends
Automated reports
generated
Health-care personnel collect data
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Discussion
A complete evaluation of the ALERTA surveillance system was performed
for the period from January 2003 to November 2006, and is the subject of a separate publication (Mundaca et al., 2005). This evaluation focused on three phases:
implementation (first year), consolidation (second year), and expansion (third and
fourth years). The methods for this evaluation are based on the Centers for Disease Control and Prevention’s (CDC’s) Updated Guidelines for evaluating public
health surveillance systems (CDC, 2001). The tasks involved in evaluating this
system are adapted from the steps in program evaluation in the Framework for
Program Evaluation in Public Health (CDC, 1999), as well as from the elements
in the original guidelines for evaluating surveillance systems (CDC, 1988). This
assessment was based on information from several data sources, including the
main database generated by the system platform, quarterly morbidity reports from
the Peruvian navy, outbreak reports, information from Voxiva personnel, focus
groups, training evaluations, and surveys applied to stakeholders. Highlights of
this evaluation are included below, and include usefulness, sustainability, stability, and flexibility.
The Alerta system has been invaluable to the Peruvian navy. Since its implementation through November 2006, 80,747 events have been reported, including
3,789 in 2003; 9,454 in 2004; 25,246 in 2005; and 42,258 through November
2006. The Peruvian navy has embraced Alerta DISAMAR and the culture of
epidemiology surrounding it. As one example, the Peruvian military leadership
asked all the services for the number of cases of dengue fever in the past year.
The navy was the only group that could provide a number and distribution within
the week. They searched Alerta DISAMAR’s database and were able to provide
the information rapidly. Since this incident, the other branches of the Peruvian
military have decided to implement Alerta. Reports such as these have allowed
baseline levels of disease to be determined, and for the first time have identified outbreaks of disease in a timely fashion so that diagnoses can be made and
interventions enacted.
One of the most important questions to ask in evaluating a system is whether
that system is doing what it was intended to do. Over the past four years, we
have detected more than 31 outbreaks, including diarrhea, dengue, influenza,
and tuberculosis. The outbreak of diarrhea depicted below is an example of an
outbreak reported using the system (Figure 2-11), and there have been several
outbreaks of acute respiratory infections that have initiated outbreak responses at
recruit training camps. One of these identified outbreaks (mumps) led the Ministry of Health (MoH) to conduct active community surveillance that uncovered
an ongoing outbreak in the civilian population that mirrored that found in the
Peruvian navy.
Timely detection of outbreaks of disease allow accurate laboratory diagnoses to be made, and with a firm diagnosis, a viable response can be fashioned
Copyright © National Academy of Sciences. All rights reserved.
Copyright © National Academy of Sciences. All rights reserved.
21
26
31
36
41
Oct
46
Nov
51
Dec
Jan
4
Feb
9
Mar
14
Apr
19
May
24
Jun
Epidemiological week
0.0
16
Sep
0
11
Aug
40.0
6
Jul
40
1
Jun
80.0
49
May
80
44
Apr
120.0
39
Mar
120
34
Feb
160.0
Jan
160
Nov Dec
200.0
Oct
Monthly incidence
200
Sep
Weekly number of cases
2-11 broadside
FIGURE 2-11 Outbreak of diarrhea as reported by the system.
SOURCE: Dr. Roger Araujo, NMRCD. �������������������������������������
Reprinted with permission from NMRCD.
Number of cases
ADD Ancon Base
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Incidence x 1,000 inh x month
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151
that hopefully will attenuate the outbreak. The Naval Medical Research Center
Detachment (NMRCD) has been able to marry Alerta to molecular and microbiologic diagnostics in a number of these outbreaks, including the use of rapid
antigen detection testing for influenza.
In addition to outbreak response, we have also provided training in basic
epidemiology and more advanced field epidemiology. We have trained more than
600 public health personnel in the Peruvian navy in basic epidemiology and the
use of this electronic disease surveillance system. Throughout South America, we
have also trained more than 1,300 epidemiologists in the basics of outbreak detection and management. The objectives for these courses and the entire curriculae in
Spanish and English are available at no cost on the Web (Lescano et al., 2007).
The following attributes of the Alerta system were included in the evaluation process:
• Simplicity: Description of the data flow; estimated time for the reporter
to collect information and analyze the data; staff training requirements; and time
spent on the maintenance of the electronic platform.
• Flexibility: Number of reporting sites added per year; cost and time
required to add new sites; ability to add new diseases to the reporting template.
• Data quality: Reporting rate (percentage of sites that report per total
number of sites); percentage of complete reports; error rate (number of errors/
number of reports); error rate per site (number of errors/total number of sites per
week).
• Acceptability: Personnel surveys after training courses; number of personnel who report per site; mean time after training to achieve a timely report.
• Representativeness: Coverage (percentage of Naval population covered
by the system); characteristics of the population.
• Timeliness: Percentage of sites that report on time and percentage of
outbreaks detected on time; average of days to report.
• Stability: Number of system failures; percentage of time that the system
is fully operational; actions involved with repairs in the system.
• Sustainability: Joint responsibilities; relationship with the Peruvian navy;
incentives; costs assumed by each part; problems and requirements to sustain the
system.
Overall, the Alerta electronic disease surveillance system has been embraced
by the Peruvian navy and has transformed public health preparation and response
in this population. Both the Peruvian navy and the NMRCD laboratory have
contributed personnel, resources, and significant time to ensure optimal performance. The implementation of this system has not been without pitfalls, and
many challenges persist. However, the significant progress illustrates how horizontal partnerships and small projects can generate measurable improvements in
epidemiologic capability.
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global infectious disease surveillance and detection
This quote from a U.S. navy physician sums up the experience in Peru:
The introduction of Alerta has led to early outbreak identification/response, timely
case management, and increased review of clinical procedures within reporting
units. . . [It is a] working model for similar larger scale international programs
Alerta is a simple, near real-time disease surveillance model for countries in all
stages of communications technology development (Lescano et al., 2003).
Clearly, to respond to and control a potential pandemic, all regions of the
world need fully functional public health systems. These systems require careful
networking of many components, including reliable disease surveillance, accurate
local diagnostics, rapid medical response capability, and fluid cooperation and
communication among local and international partners.
Some components of successful public health strategies are present in
the U.S. Department of Defense Global Emerging Infections Surveillance and
Response System (DoD-GEIS). This system is a decade-old DoD program initiated in response to President Clinton’s directive in 1996 that mandated the development of a global system to track, control, and respond to potential pandemic
infections. It generated, among other things, the electronic disease surveillance
system described above (White House, 1996). GEIS serves as just one component
of a growing network of public health assets that are increasingly being used to
control infectious diseases with pandemic potential, complementing many global
public health community efforts (Chrétien et al., 2006).
The Alerta model implemented in Peru has a number of dimensions that
have contributed to its success:
• Committed leadership in all parties;
• A regulatory regime that specified reporting requirements;
• A practical use of information technology that maximized the use of available telecommunications and computing infrastructure;
• Real-time data collection from points of service and automated reports
and notification;
• Live database for continuous analysis and investigation;
• Links to laboratory and investigation capacity;
• Training and support of a distributed network of clinicians and other
health workers; and
• Mobile technology accessible to virtually everybody in Peru—if not individually then through a Navy command with cell phones and Internet access.
The approach that was developed and tested in Peru is now being expanded
with support from the U.S. DoD Southern Command to five neighboring countries: Bolivia, Colombia, Ecuador, Paraguay, and Uruguay. In addition, Voxiva is
part of a public–private partnership with the GSM Association, the largest asso-
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ciation of mobile phone operators (more than 650 mobile phone operators and
2 billion subscribers worldwide) to extend the benefits of this network in service
to public health. Hopefully this can provide not only a model of working in the
field, but also a model of cooperation between public and private entities.
Acknowledgments
The results reported derive from the common vision and hard work of a
number of individuals in the Peruvian and U.S. navies and Voxiva as well as
the support of the DoD-GEIS program. Key individuals include Drs. Carmen
Mundaca, Roger Araujo, Tanis Batsel, Rafael Elgegren, Ernesto Gozzer, Patrick
Kelley, Andres Lescano, Monica Negrete, and Mario Ortiz.
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V. Espitia, R. Imtiaz, D. Sosin, D. F. Stroup, R. V. Tauxe, M. Vijayaraghavan, and M. Trostle.
2006. Public health surveillance: A tool for targeting and monitoring intervention. In Disease
control priorities in developing countries. 2nd ed., edited by D. T. Jamison, J. G. Breman,
A. R. Measham, G. Alleyne, M. Claeson, D. B. Evans, P. Jha, A. Mills, and P. Musgrove. New
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3
Detection and Diagnostics
OVERVIEW
Workshop presentations on infectious disease detection and diagnostics surveyed current capacity, needs, and challenges; anticipated forthcoming developments; and imagined a future in which diseases can be diagnosed prior to the
appearance of symptoms (see Summary and Assessment).
Diagnostics for Developing Countries
The session began with a reminder from Mark Perkins of the Foundation for
Innovative New Diagnostics (FIND) that while emerging diseases and bioterrorism threaten public health, infectious diseases such as tuberculosis and malaria
have long imposed a severe burden on the developing world. In their contribution
to this chapter, Perkins and Peter Small of the Gates Foundation discuss the need
for rapid, accurate, inexpensive, robust diagnostics in developing countries—a
need that could be met by recent advances in genomics, proteomics, and materials
science if there was a profitable market. To fill this gap, FIND guides the development and adoption of novel diagnostic products for diseases of the developing
world in much the same way as public–private partnerships have been established
to produce drugs and vaccines for low-resource settings. With FIND’s support,
companies that produce low-cost diagnostics for use in developing countries
realize sufficient cost savings (in manufacturing, approval procedures, and marketing) to sustain profits.
158
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Rapid Diagnostics
Soldiers at risk of contracting infectious disease—either from the natural environment or from bioweapons—need diagnostics that are rugged, rapid,
and easy to use, according to speaker Mark Wolcott of the Diagnostic Systems
Division at the U.S. Army Medical Research Institute of Infectious Diseases
(USAMRIID). In their contribution to this chapter, Wolcott and co-authors discuss the rationale, design, and development of rapid diagnostic assays for infectious diseases. They offer brief, comparative descriptions of a variety of platform
technologies that in the future may be combined to produce comprehensive, integrated diagnostic systems—perhaps in the guise of miniaturized “labs on chips”
that process samples, perform assays, and automatically report their results. “As
technologies mature and new technologies are developed, rapid infectious disease
diagnostics will become available and practical,” the authors predict.
Rapid diagnostic tools are also improving infectious disease surveillance
in animals. Workshop presenter Alex Ardans, who directs the California Animal Health and Food Safety Laboratory System, described the development of
polymerase chain reaction-based (PCR-based) assays to screen for diseases that
have caused devastating outbreaks in livestock, such as exotic Newcastle disease
(END) in poultry and foot-and-mouth disease (FMD) in cattle. California also
developed a highly efficient tuberculosis testing program after the disease was
detected in several of the state’s large dairies.
Based on such experiences, Ardans argued that the state’s laboratory system
plays its most crucial role when recognizing and responding to unusual disease
events. For example, following a recent END outbreak among fighting cocks,
whose handlers worked in and spread the disease to commercial poultry operations, the laboratory optimized an existing real-time PCR assay for END that
was used to perform more than 85,000 tests (Crossley, 2005). Such emergencies
present unique opportunities to improve disease diagnosis, Ardans said, although
not necessarily with the latest technology. He noted that laboratory researchers, in
pursuit of the source of E. coli O157:H7 following a recent outbreak in spinach,
discovered that a gauze swab used to sample irrigation waters for contaminants
performed better than newer concentration devices.
Emerging Diagnostics
Although Koch’s postulates remain diagnostic standards, adapting them to a
vastly expanded understanding of disease states has become increasingly problematic, observed presenter Ian Lipkin and co-author Thomas Briese of Columbia
University’s Jerome L. and Dawn Greene Infectious Disease Laboratory. Their
paper discusses contemporary problems in proving causality, and illustrative case
studies that reveal how these challenges are shaping pathogen surveillance and
discovery. The authors also provide a taxonomy and comparative guide to proven
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and proposed methods for characterizing infectious agents without recourse to
cultivation, including two platforms of their own creation: MassTag PCR and the
GreeneChip. In the future, Lipkin and Briese predict, substantial advances against
chronic disease will occur “not from technical improvements but from investments in prospective serial sample collections and an appreciation that many
diseases reflect intersections of genes and environment in a temporal context.”
Pre-Symptomatic Diagnosis
Imagining a future in which bioterrorism agents are continually reengineered
to elude standard detection and diagnostic methods as well as therapeutics,
speaker and Forum member Stephen Johnston offers a model of diagnosis for
exposure to a pathogen before symptoms appear: a host-based detection system,
capable of analyzing hundreds to thousands of components in samples of blood,
sputum, or urine, and thereby capable of detecting any type of engineered or
natural threat agent. In the final paper of this chapter, Johnston discusses the
feasibility of developing such a system and its potential not merely to detect
biothreats, but to “convert standard health practice from one that treats symptoms
to one that detects disease very early—even presymptomatically.”
PARTNERING FOR BETTER MICROBIAL DIAGNOSTICS
Mark D. Perkins, M.D.
Foundation for Innovative New Diagnostics
Peter M. Small, M.D.
Bill and Melinda Gates Foundation
Timely and accurate diagnosis is critical to the global efforts to prevent and
treat infectious diseases. And yet, those on the front lines of this battle struggle
to make do with inadequate and antiquated testing technology. For example, a
100-year old test is used to diagnose tuberculosis, a disease that kills someone
every 16 seconds, and precious new antimalarial drugs are being rolled out with
the same diagnostic imprecision that currently mistreats several hundred million
cases every year. The tragic reality is that diagnostic uncertainty exacts a huge toll
in morbidity and mortality. Reliance on underperforming diagnostic technologies
limits the control of the world’s greatest killers, especially in settings with high
Reprinted with permission from Nature Biotechnology. Copyright 2006 Nature Publishing Group.
Perkins MD, Small PM. 2006. Partnering for better microbial diagnostics. Nature Biotechnology
24(8):919-921.
Chief Scientific Officer.
Global Health Program.
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human immunodeficiency virus (HIV) prevalence. We contend that innovative
mechanisms are needed to produce, develop and deploy new and better diagnostic
tools for infectious diseases in developing countries.
Global Public Health Goals at Risk
Acknowledging the impact of the global tuberculosis epidemic in the early
1990s, the World Health Assembly of the World Health Organization (WHO;
Geneva) declared tuberculosis a global emergency and ratified goals for case
detection and cure under the DOTS (directly observed therapy shortcourse)
strategy by the year 2005. Although important successes in fighting tuberculosis
have been achieved in recent years, reliance on weak diagnostic tools has slowed
progress. Case detection targets for smear-positive tuberculosis have not been
met, and fewer than 25 percent of all cases are now detected and reported as
smear positive (WHO, 2004). The data available suggest that the Millennium
Development Goal of halving tuberculosis prevalence by 2015 also cannot be
achieved universally without improved methods for diagnosing tuberculosis (Dye
et al., 2005).
The weaknesses of standard diagnostic tests for tuberculosis are well documented. Even in controlled research settings, the average sensitivity of sputum
microscopy for pulmonary tuberculosis is only 60 percent in immunocompetent
populations, and it is substantially lower among people infected with HIV. Conventional culture methods are so slow that testing often loses clinical relevance,
and the poor predictive value of the tuberculin skin test renders it essentially
worthless in disease-endemic areas. The weaknesses of the available diagnostic
technologies are only amplified in high-burden countries, which typically have
insufficient infrastructure and inadequate staffing.
Reliance on inadequate diagnostic tools cripple TB control efforts. Because
of limited access to diagnostic services and the low sensitivity of conventional
testing, patients in many high-burden countries remain undiagnosed for three to
six months (Madebo and Lindtjørn, 1999; Liam and Tang, 1997). These delays
result in increased morbidity and mortality, mounting costs combined with loss of
work, and continuing tuberculosis transmission to families and communities.
Unlike tuberculosis, which requires months of treatment to cure, malaria
can be treated with a few doses of unsupervised treatment. This dramatically
reduces the motivation to confirm the diagnosis. Microscopy for malaria is
notoriously difficult, and experienced microscopists give substantially different
results on up to a third of all slides. In most settings where malaria is endemic,
quality microscopy is poorly available and malaria treatment is given by default
to almost all patients with fever. Fever is an exceedingly common symptom in
the tropics, and an estimated 800 million malaria treatments are given each year
for fevers, the great majority of which are not caused by malaria (Amexo et al.,
2004). This massive mistreatment of hundreds of millions of people results in
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global infectious disease surveillance and detection
the fatal under-treatment of other diseases, such as pneumonia and sepsis, which
present with similar symptoms.
Having watched at least two generations of malaria medicines fall to mounting drug resistance, the international malaria community has called for greater
diagnostic accuracy before treatment, especially as expensive artemisinin-based
therapies are introduced. In 2004, the WHO recommended that malaria should be
confirmed by parasitologic examination before treatment in all patients older than
five years of age. In this setting, the development of simple and rapid diagnostic
tests (RDTs) that can detect circulating Plasmodium antigens in a drop of fingerprick blood is a key recent development.
The success of RDTs in improving the targeting of drug therapy, and their
acceptance in malaria management by remote health workers and patients, will
depend on the reliability and accuracy of the tests. There are now more than three
dozen manufacturers of such tests, many of which show inadequate sensitivity,
thermostability and geographic applicability. Though RDTs are now in wide use
in some areas, the lack of true performance data on most of these tests, the variability in published performance of others and the lack of a global quality assurance mechanism has generated chaos and confusion with regard to test selection
and has resulted in many end-users rejecting test results in favor of presumptive
treatment.
The lethal convergence of these diseases and HIV exacerbates the negative
impact of weak diagnostic tools. The rise of HIV in tuberculosis-endemic settings dramatically increases tuberculosis incidence, the number of symptomatic
individuals and the pressures on already overburdened health systems. HIV
coinfection decreases the sensitivity of microscopy for TB at the same time that
it increases the urgency for rapid diagnosis and treatment. From South Africa
to Brazil (Pronyk et al., 2004; Gutierrez et al., 2002), 30 to 50 percent of HIVinfected people die with undiagnosed tuberculosis, and Mycobacterium tuberculosis is now a leading cause of bacteremia in febrile patients visiting emergency
rooms in sub-Saharan Africa (Archibald et al., 1998). Fever in HIV endemic
areas cannot be assumed to be benign if nonmalarial. Thus, for many countries
burdened by HIV, the need for improved diagnostic tests is increasingly urgent.
New Opportunities
Recent trends in science and technology, and in the diagnostics industry,
indicate that there may be important new opportunities to improve diagnostic
tests suitable for developing countries. Availability of the complete genomic
sequence of M. tuberculosis allows a comprehensive assessment of potential
diagnostic targets. Massive investment in biodefense has generated a range of
diagnostic technologies intended for front-line use. The growing diagnostics
industry can develop new diagnostic tests at a fraction of the cost and time needed
to bring drugs and vaccines to licensure.
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Motivated primarily by the small but significant market in industrialized
countries, the tuberculosis diagnostics industry has produced several new tests
in recent years. For example, shortcuts around the slow growth of M. tuberculosis using phage-based or molecular methods allow tuberculosis detection and
screening for rifampin resistance within 48 hours (Albert et al., 2002; Johansen
et al., 2003). Other new tests exploit tuberculosis-specific proteins to detect latent
infection with much improved specificity, especially in BCG (BacilleCalmette
Guérin)-vaccinated populations (Lalvani et al., 2001; Mori et al., 2004). Likewise, for malaria diagnosis, several rapid immunochromatographic tests detecting
Plasmodium antigens in blood have been developed over the past 15 years, and
they now reach a market of some 25 million people.
Forging a Public–Private Initiative
Market forces alone, however, will not yield the diagnostic tools needed to
improve global health. Private companies often avoid developing products that
will primarily be used in developing countries out of skepticism about the return
on their investment. Developing countries have little capacity to pay the higher
prices typically attached to new products, even when these costs result in overall
savings to health care systems. The processes by which these countries license,
purchase, and distribute products are often inadequately developed and poorly
understood by industry.
The drive to develop new diagnostics for the developing world is unlikely
to succeed without the private sector, with its expertise in product development,
manufacturing capacity, product distribution and quality control. Unless measures
are put in place to address current market dynamics, the number of companies
engaged in diagnostics development will likely remain limited, and most will
continue to tailor their products to markets in industrialized countries. The resulting products, such as the molecular amplification systems and automated systems
for early detection of mycobacterial growth—which have markedly improved
the diagnosis of tuberculosis in industrialized countries—may be little used in
developing countries and thus have no impact on the global tuberculosis problem.
Most of the companies manufacturing rapid malaria tests are small and do not
have the resources to redevelop their assays to address important deficiencies in
sensitivity and shelf life, especially at tropical temperatures.
Goal-driven public sector action is needed across the development pathway
to forge a strong and sustainable partnership with industry to generate new
diagnostics (Figure 3-1). Public sector actors must be prepared to sponsor basic
research, partner equitably with industry on product development, evaluate products in a regulatory-quality fashion (Small and Perkins, 2000), demonstrate the
efficacy of implementation, change technical and financial policies to foster new
diagnostics, and actively facilitate the latter’s distribution and use. In pursuit of
these goals, the public sector should explore such innovative approaches as the
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3-1 Broadside
FIGURE 3-1 Product development path for microbial diagnostics.
164
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165
creation of novel financing mechanisms and distribution strategies to increase
industry confidence that a viable market will exist in resource-limited settings.
There are many examples of innovative public–private partnership for the
development of drugs and vaccines. Few are, however, focused on diagnostics.
The Foundation for Innovative New Diagnostics (FIND; Geneva, Switzerland; of
which Mark D. Perkins is Chief Scientific Officer), is one such entity. Launched
in 2003, FIND aims to develop a model for public sector action to drive the
development of diagnostic products for diseases of the developing world, using
the search for new diagnostics as the test case for the model’s development.
FIND seeks to identify the most promising product candidates and accelerate
the process of development, testing, approval, distribution and incorporation
into routine public health policy. Although motivated by the desire to create new
public goods, FIND has many of the attributes of a private company, pursuing
a clear business plan and using rigorous scientific criteria to identify priority
product candidates.
RAPID INFECTIOUS DISEASE DIAGNOSTIC ASSAYS
Mark J. Wolcott, Ph.D.
U.S. Army Medical Research Institute of Infectious Diseases
Randal J. Schoepp, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
David A. Norwood, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
David R. Shoemaker, Ph.D.5
U.S. Army Medical Research Institute of Infectious Diseases
Rapid disease diagnostics (“serving to identify a particular disease or pathogen”) for many infectious agents are not as well developed as other laboratory
technologies. Laboratory tests for many infectious agents still rely on decadesold technologies and techniques. Culture remains the gold standard for identifying organisms, but not all pathogens can be cultured, making alternative tests
necessary.
When culture is difficult or not available (virus cultures in field laboratories),
serological diagnosis of the antibody response to the organism is typically used.
Opinions,
interpretations, conclusions, and recommendations are those of the authors and are not
necessarily endorsed by the U.S. Army. Funding was provided in part by the Defense Threat Reduction
Agency, Joint Science and Technology Office for Chemical and Biological Defense (JSTO-CBD).
Diagnostic Systems Division.
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global infectious disease surveillance and detection
However, a problem with both traditional culture and immunodiagnostics is the
time required to obtain results. Culture may take several days and immunodiagnosis is limited by the time required to mount an antibody response, often a week
or more (Figure 3-2). Current efforts in rapid diagnostics are shifting the window
of detection closer to the point at which clinical disease symptoms become evident. Ultimately, future rapid diagnostics will shift the window to a point soon
after exposure, giving the clinician the greatest opportunity to intervene in the
disease process.
Orthogonal diagnostic testing is the key to improving the reliability of rapid
diagnostic technologies. Orthogonal testing refers to tests that are statistically
independent or non-overlapping but, in combination, provide a higher degree
of certainty of the final result. Although orthogonal testing is not a standard
perspective in the clinical diagnostic industry, the concept and its application
are paramount when investigating some infectious agents. Any single detection
technology has a set of limits with regard to sensitivity and, most importantly,
specificity. Orthogonal testing seeks to overcome the inherent limitations of individual test results with the strength of data combinations (Henchal et al., 2001).
The application of orthogonal diagnostic testing uses an integrated testing strat-
Infection/response time course
Detect exposure
Acquired immunity (Late response)
Clinical disease
Detect agent
IgG serodiagnostics
IgM serodiagnostics
Antigen/nucleic acid methods
Culture methods
Innate immunity
0
5
10
Time
15………120 days
FIGURE 3-2 Infection and response time course. Various detection methodologies have
highly different entry points in their use on human disease. As the time points extend out,
the ability of medical interventions have less success. The earlier the time of medical
intervention, the more successful the prognosis is for most diseases.
SOURCE: Wolcott (2006).
3-2
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DETECTION AND DIAGNOSTICS
egy where more than one technology, technique, or biomarker is used to produce
diagnostic results, which are then interpreted collectively (Figure 3-3).
The Department of Defense has an acquisition program to acquire quality
diagnostic products that satisfy the needs of commanders with missions to support the warfighter. This acquisition program is designed to be timely with fair
and reasonable associated costs. The acquisition program includes design, engineering, test and evaluation, production, and operations and support of defense
systems (Table 3-1). To simplify and expedite the acquisition timeline for the
fielding of a rapid diagnostic system, commercial off-the-shelf technology is
evaluated and a formal selection process is used to select a system for further
development and fielding. The Joint Biological Agent Identification and Diagnostic System (JBAIDS) acquisition program was formally launched in September
2003 with the award of the first phase, a molecular diagnostic system, in fall
2005 (Figure 3-4).
Classical
microbiology
Nucleic
acid
detection
(agent/host)
Clinical
diagnosis
or
medical
intelligence
Antigen
detection
(agent/host)
ANSWER
Animal
testing or
other
advanced
technologies
(EM/Mass
Spec/etc.)
FIGURE 3-3 Orthogonal diagnostic testing. Although each method provides an independent assessment, together the power of the diagnostic becomes large. The failure of any
one independent assessment does not fail the system.
3-3
SOURCE: Wolcott (2006).
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global infectious disease surveillance and detection
TABLE 3-1 Department of Defense (DoD) Acquisition Program for
Diagnostic Devices
Predevelopment
Advanced Development
Basic
research
Technology
evaluation
Demonstration
and validation
New
technologies
Technology
demonstrations
Prototypes
Engineering
and
manufacturing
development
PMA/510K
approval
Initial
operational
testing
Procurement Operations
and Support
Procurement
and
deployment
Operations
and
support
Final
production
Follow-up
evaluation
NOTE: The acquisition process moves from left to right through defined operational activities. Each
activity is designed to provide a value-added service and ensure that DoD obtains the product needed
at a reasonable cost investment for the country.
SOURCE: Wolcott (2006).
FIGURE 3-4 Acquisition program—evolutionary strategy. The acquisition process for
developing and fielding a rapid infectious disease diagnostic assays system is designed
around an evolutionary strategy. By leveraging commercial technologies that currently
exist in the commercial market, and furthering development on those platforms, the final
field-deployable system will be quicker and cheaper than trying to obtain the final product
up front.
3-4
SOURCE: Wolcott (2006).
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Current molecular diagnostic technologies are based on the amplification of
specific DNA sequences from extracted nucleic acids, DNA or RNA. Amplification techniques take tiny amounts of nucleic acid material and replicate them
many times through enzymatic reactions, some that occur through cycles of
heating and cooling. These include methods that involve target amplification
(e.g., polymerase chain reaction [PCR], reverse transcriptase–PCR [RT-PCR],
strand displacement amplification, transcription amplification), signal amplification (e.g., branched DNA assays, hybrid capture), probe amplification (e.g., ligase
chain reaction, cleavase-invader, cycling probes), or postamplification analysis
(e.g., sequencing the amplified product or melting curve analysis as is done in
real-time PCR).
Nucleic acid-based methods are generally specific and highly sensitive and
can be used for all categories of microbes (Christensen et al., 2006; Emanuel
et al., 2003a). Amplification methods can identify minute traces of the genetic
material of an organism in a specimen, avoiding the need for culture. These
techniques are particularly useful for organisms that are difficult to culture or
identify using other methods (e.g., viruses, obligate intracellular pathogens),
or are present in very low numbers. Results can be provided more rapidly than
through most conventional methods, especially culture. However, because amplification methods are so sensitive, false positives from trace contamination of the
specimen or equipment can easily occur. In addition, because these techniques
depend on enzymatic activity, false-negatives also occur when a sample contains
contaminants that inhibit enzyme activity (Hartman et al., 2005). Nucleic acidbased tests are also limited in that they do not provide information on the viability
of the detected organism.
Immunodiagnostics is the standard against which many agent detection,
identification, and diagnostic technologies are compared. Antibody-based assays
continue to serve as preliminary and confirmatory diagnostic formats for many
infectious and noninfectious diseases. These assays are typically rapid, sensitive, specific, reliable, and robust. Immunodiagnostic technologies are relatively
unsophisticated, making them available to nearly any laboratory.
Hand-held assays (HHAs) are immunoassays that are based on immunochromatography or lateral flow assay format. Generally, a sample is applied to
the testing unit and by flowing along a membrane, an indicator line forms where
antibodies to the analyte of interest are bound. The presence of a line indicates
the presence of the analyte, while the absence of a line denotes a negative result.
Applying a sample solubilizes the tagged antibodies and initiates the first binding
of the target by the tagged antibodies. As the sample continues migrating down
the filter paper, the analyte of interest encounters a set of antibodies bound to the
membrane and an antibody-analyte-antibody sandwich is formed. While early
HHAs incorporated enzymes as labels to yield a visible signal, advances have
done away with the multistep enzyme immunoassay format and have incorporated reporter molecules such as colloidal gold or colored latex spheres that yield
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a direct signal. These physical signal generators rely on the aggregation of a large
number of tags to enhance signal visualization by the naked eye. HHAs, like all
analytic systems, have inherent limitations in their use and interpretation; they
require a relatively large amount of sample, their sensitivity is limited, and they
have a potential for false positives as a result of “dirty” environmental samples
that form a confounding “dirt” line in the antibody capture zone. Although HHAs
have limitations, their overall ease of use and quickness make them useful in
certain situations.
Time-resolved fluorescence (TRF) is an immunoassay application that
employs the basic immunoassay analyte sandwich capture format, but with
detector antibodies that are directly labeled with a lanthanide chelate, such as
europium, samarium, terbium, and dysprosium. The strengths of TRF are its
increased sensitivity and the potential for multiplexing. TRF uses the differential fluorescence life span of lanthanide chelate labels compared to background
fluorescence. The long-lived fluorescence signal and the difference in wavelength
between absorbed and emitted light results in a very high signal-to-noise ratio and
excellent sensitivity (Hemmila et al., 1984; Soini and Kojola, 1983). The long
fluorescence decay time allows the measurement of immunoassay fluorescence
after any background fluorescence has decayed. By pulsing the excitation light
repeatedly, in 1 second the fluorescent material can be excited more than 100
times with an accumulation of the generated signal that improves both the overall
signal and the reduction of background signals. TRF assays are particularly useful
in clinical immunoassays, but have limitations with environmental samples where
europium or other lanthanides naturally occur. The contaminating compounds
behave much like labeled lanthanides, prolonging the background fluorescence
and lowering TRF sensitivity.
Electrochemiluminescence (ECL) is immunoassay technology in which a
detector antibody is tagged with a chemical that emits light (luminescence) when
it is excited by an electrical stimulus. There are several electrochemiluminescent
chemical moieties, but ruthenium is the most common. Ruthenium, in the form
tris (2,2’ - bipyridine) ruthenium (Ru), is relatively small, allowing easy conju
gation to antibodies. The technology relies on two components: the ECL-label
(Ru) coupled to an antibody and tripropylamine (TPA) present in the reaction
buffer. When an electrical current is applied to an electrode, both components
are activated by oxidation. The oxidized TPA is transferred into a highly reducing
agent, which reacts with activated Ru to create an excited-state form of Ru. This
form returns to its ground state with emission of a photon at 620 nm wavelength.
An advantage of the Ru-TPA methodology is that the measurement of a single
sample can be repeated multiple times because the electron-transfer photonrelease reaction regenerates the Ru resulting in signal amplification. Although
ECL assays are simple, rapid, and sensitive (Kijek et al., 2000; Smith et al.,
2001), the sample matrix can affect the assay sensitivity. The sample matrix will
influence the sensitivity by varying positive cut-off values; therefore, matrix-
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s pecific positive and negative control samples are used to establish standard
curves and cutoff values.
Several diagnostic systems are using a technology to analyze microspherebased multiplex protein assays. The advantage of multiplex assays is that multiple results are available from one sample without individual testing. Up to 100
different biomolecules (proteins, peptides, or nucleic acids) can be analyzed in
a single test. A microplate platform allows the automated analysis of a 96-well
plate in 30 minutes yielding a throughput of 1,920 assays in a 20-plex system.
Currently kits for simultaneous quantitative measurement of up to 25 to 30 proteins are available, including cytokines, phosphoproteins, growth factors, kinases,
and transcription factors. Several investigators are using these systems to develop
multiplexed assays for biological warfare agents. One system was evaluated by
the U.S. Army with extremely good results, but the equipment is currently not
rugged enough for use by the warfighters.
The key to future rapid diagnostic systems is the development of a completely and fully integrated system. Previous diagnostic research efforts were
only concerned with the development of an assay technique and failed to address
the full spectrum of an integrated system. To fully address an integrated system,
protocols, sample processing, reagents, assays, platforms, and evaluations need
to be completely explored. Protocols are equivalent to an intended-use statement.
Without addressing how and why the assay or system is to be used, misapplication will result in incorrect and potentially serious testing reliability issues.
The single most important aspect of rapid testing is sample processing.
The sample is the most important component in a system, and an inappropriate or improperly handled sample will jeopardize an otherwise robust assay.
For example, detection of Bacillus anthracis is highly problematic. The spores
of Bacillus anthracis are very refractile to easy and rapid sample preparation.
Alternate methods are required to produce the highest quality sample, which
include concentrating the sample (if possible) and methods to release either the
nucleic acids or specific proteins from the spore. These include techniques such
as germination, sonication, or mechanical disruption (“bead-beating”). Another
consideration of sample preparation, especially for many molecular methods, is
the removal or neutralization of inhibitors of amplification.
Systems consist of more than just assays (Figure 3-5). Developers need
to be cognizant of all the details. While most commercial manufacturers have
appropriate production systems and quality manufacturing practices in place for
producing consistent, reliable, and appropriate reagents that are compliant with
Food and Drug Administration (FDA) requirements, research-derived systems
often fall short. In addition, integration of assays with various platforms is often
overlooked in initial system development. While some assays perform well on
multiple platforms, many assays suffer optimization issues when moved from
one platform to another. Unless provisions are made for multi-platform development, and shown to be equally effective through validation, platform equivalency
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global infectious disease surveillance and detection
Diagnostic System Architecture
Validation/field testing
Protocols
Platforms
Reagents
Sample processing
Assays
FIGURE 3-5 Diagnostic system architecture. Systems-based architecture needs to include
the full gamut of functions from protocols through validation.
SOURCE: Wolcott (2006).
3-5
should not be assumed. Another consideration in system development for systems
developed by professional scientists working in modern laboratory facilities is
the inherent expectation that assays and systems will work in the hands of less
trained personnel outside of the pristine laboratory facilities. Often, this is not the
case. Field evaluation, under conditions of actual employment, is critical before
assays and systems can be confidently deployed and used.
Validation of the appropriateness and effectiveness of assays and systems is
paramount in the development process (Emanuel et al., 2003b). Development of
assays and systems needs to include assay validation parameters such as linearity,
limits of detection, inclusivity and exclusivity testing, ruggedness, robustness,
and repeatability. Validation parameters are detailed in Box 3-1.
A critical and often overlooked issue is that diagnostic systems and tests
intended to be used to test clinical samples must be approved by the U.S. Food
and Drug Administration in order to legally be distributed and used in the United
States. Many of the technologies discussed in this article are mature enough to
produce clinically useful diagnostic products. However, companies that may have
the capability to manufacture these diagnostic tests, and to gain FDA approval
for them, typically are not interested in doing so for tests to diagnose tropical
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BOX 3-1 Example of Diagnostic Systems
Validation Parameters
1. L
inearity (establish standard curve with single “type” strain). The concentrations will range from 100 pg to 1 fg of the target nucleic acid. When cloned
material is required (i.e., Variola), the concentrations will range from 1 pg to
10 ag.
a. There will be two replicates for each 10-fold dilution.
b. Data will be used to estimate limit of detection (LOD).
c. Slopes will be used to calculate amplification efficacy and efficiency using
the formulas.
d. All supporting data will be submitted in the data package.
e. Real-time polymerase chain reaction (PCR) curves.
f. Standard curve indicating slope and R2 values.
g. PCR efficacy and efficiency calculations.
2. Limit of detection.
a. LOD testing will be performed with the type strain.
b. A minimum of 58 positive results is required to establish the LOD.
c. 60 total replicates will be performed at the LOD of the assay consisting
of:
i. Three separate runs—two instruments—two operators—2 days.
ii. A minimum of two positive and two negative controls.
d. All supporting data will be submitted in the data package.
e. Operators, instruments, and dates of performance should be documented.
3. Inclusivity/exclusivity.
a. Inclusivity (testing the ability of the assay to pick up multiple strains of the
same agent).
i. Multiple strains of the target organism.
ii. Duplicate samples.
b. Exclusivity (test of whether assay cross-reacts with nucleic acids from other
organisms).
i. Panel will include near neighbor testing (genetic neighbors).
ii. Panel will include broad cross-reactivity panel.
iii. Duplicate on purified nucleic acids at a concentration at least 1,000x
the established LOD of the assay.
c. Environmental/matrix panel to include human DNA and cell culture extracts
used to produce viral agents.
SOURCE: Wolcott (2006).
diseases or biological threat agents because the commercial demand is low. This
is a chronic problem with no easy solution.
To help support the deployment of rapid agent identification systems, especially those that do not have enough commercial value to be fully supported by
commercial manufacturers, the Department of Defense relies on the Joint Program Executive Office–Critical Reagents Program (CRP). The CRP is a national
resource for the biological defense community, whose mission is production of
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global infectious disease surveillance and detection
detection reagents, standardization of procedures and training, and optimization
and transition of detection technologies. Their commodity areas include the
production of antigenic and genomic materials for test and evaluation purposes,
antibodies, to include the manufacturing of hand-held devices, molecular detection reagents, and sampling kits. Because of the confined nature of these materials
and the lack of commercialization due to the limited customer base, CRP provides
a vital link to the defense community to ensure harmonization of tests and evaluations and as an avenue for advanced development.
In the course of development of newer, faster, better, and cheaper rapid
diagnostic devices, the Department of Defense program is looking at potential
future platforms. Many characteristics of those future systems are discussed
above, but one that is showing some promise is DNA microarrays. Microarrays or
DNA chips are one of the latest methods for rapid infectious disease diagnostics.
Microarrays are a recent adaptation of Northern blot technology (Grunstein and
Hogness, 1975; Schena et al., 1995). The ability to label nucleotide sequences
with fluorescent tags, much like fluorescent antibody technology, has increased
their use in diagnostics. Microarrays are small, solid supports (typically glass
slides) on which DNA sequences are attached, or spotted, at fixed, orderly,
addressable locations. The DNA is composed of short, single-stranded fragments,
typically 5 to 50 nucleotides long. Microarrays can have up to tens of thousands
of spots, allowing for a large amount of data collected for each sample tested.
Microarrays depend on the annealing of two nucleic acid strands to function.
When sample DNA is prepared, usually through polymerase-based amplification,
fluorescent dyes are incorporated into the amplicon so that hybridization can
be detected. The kind of information required from microarrays drive how the
arrays are developed and used. Microarrays can be spotted with known sequences
of a variety of oligonucleotides for basic genomic investigation. Gaining wider
acceptance is the use of microarrays to “resequence” organisms. Utilizing known
sequences from already sequenced organisms and hybridizing genomic material
from organisms not previously sequenced, sequence differences can be determined. With more than 10,000 sequences (and growing as automated systems
improve) to interrogate on a single chip, variation in genomic sequences can
provide accurate species and subspecies determination. Finally, one of the earliest
applications of microarrays is their use in “transcriptomics” or gene expression
studies. Gene expression-based measurements of mRNA levels, and the differences between these levels in various states of organism growth (i.e., aerobic
versus anaerobic growth), has provided significant insights in gene regulation of
various organism functions.
Although microarrays have the demonstrated potential for diagnostics, routine use is hampered by several considerations. The first hurdle for microarrays is
the availability of high-quality, validated, and standardized arrays and processes.
A key limitation to implementation of routine diagnostic microarrays is identification of appropriate targets. Although ribosomal RNA gene targets are widely
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used, they are limited in their ability to resolve bacteria below the species level
(Saliba et al., 1966). Other bacterial target genes, including housekeeping genes,
are potentially useful, but data across the full breath of organisms are limited or
nonexistent. Even with good targets, optimal hybridization conditions for all the
probes on a single array are still challenging. Redundant variations in probes
help compensate to a degree. Another challenge to microarray routine use is
the sensitivity of most systems. To obtain appropriate sensitivity, polymerase
amplification is necessary. In most systems, this requires a multitude of specific
primers for the genes of interest. Because multiplexed PCR is limited to a dozen
or so reactions, several hundred iterations of PCR could be required to completely
cover all the potential probes on an array, which is not practical in routine use.
Until a good on-chip amplification or signal detection method is developed, the
use of diagnostic microarrays will be limited.
Ultimately, to meet the needs of users, rapid infectious disease diagnostic
assays need a comprehensive integrated system. This includes automated sample
processing and the use of multiple technologies to obtain results that can be interpreted against the clinical picture or medical intelligence. Currently, immunoassays and molecular assays are the most mature technologies. Immunoassays are a
maturing technology that has improving sensitivity and specificity. With improvements in signal amplification and the use of monoclonal antibodies, immunoassays are fast, robust, and approaching the sensitivity of some molecular methods.
Molecular methods are rapidly developing but are not at the full maturity level
yet. Amplification methods achieve exquisite sensitivity, but at the risk of potential contamination events. Together, immunoassays and molecular techniques are
very complementary and a powerful set of techniques for an integrated system
(Henchal et al., 2001) (Figure 3-6).
The future for rapid infectious disease diagnostics is the lab-on-a-chip
approach, where all sample processing, assay technologies, detection, and reporting are fully integrated into one unit. Miniaturized, disposable, and cost-effective
units will evolve from our current systems. As technologies mature and new
technologies are developed, rapid infectious disease diagnostics will become
available and practical.
Ramping Up to Success
Although we believe that the products of strategic, adequately supported
public–private partnerships to develop diagnostics could transform approaches
to control infectious diseases in poor countries, progress inevitably will be incremental, especially in the near term. Because new tests are likely to be imperfect,
we will need flexibility and creativity to ensure that these tools are used to
maximum effect. For example, rather than discard a rapid tuberculosis test with
high sensitivity but low specificity, we should consider incorporating it into a
diagnostic algorithm to quickly rule out tuberculosis in most patients present-
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D
Microfluidic backbone
B
Analyte AnalyteSpecific
specific
Binding
binding
C
C
Detection
Detection
3-6A
Power
Power
Subsystem
subsystem
Micro
Micro
Controller
controller
Anthrax
positive
BW
Module
Immunodiagnostics
Operator
Interface
interface
FIGURE 3-6 Comprehensive integrated diagnostic system. Integrated systems that employ more than one technology along with the sample
handling component are being investigated for the next-generation diagnostic systems.
Crude
Sample
sample
A
Sample
Preprocess
preprocess
Disposable cassette
Nucleic acid detection
Automated sample processing
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DETECTION AND DIAGNOSTICS
ing with chronic cough—a step that could dramatically decrease the workload
of tuberculosis clinics. Rather than develop a single test to replace the sputum
microscopy, we should embrace the concept of market segmentation and develop
a range of new tools suitable for different diagnostic environments.
We must also accept that new technology may require changes to longstanding public health practices. For example, tuberculosis epidemiology has long
been tracked by monitoring the number of smear-positive patients. If microscopy is replaced with a more sensitive test, tracking of tuberculosis trends could
be disrupted. But this is a small price to pay for better serving patients and
strengthening the world’s ability to bring tuberculosis under control. Similarly,
microscopy offers quantitative estimates of parasite burden, which is often used
by clinicians to estimate the severity of illness or to monitor the effectiveness of
treatment. Replacement with qualitative testing will force a change of practice,
even as it brings the power of confirmatory diagnosis out of referral laboratories
and into the community.
Finally, we emphasize that the impact of a new diagnostic test ultimately will
be determined by the extent to which it is used. Expanding use of a new technology, as with any global health intervention, ultimately will depend on political
will. Integration of improved diagnostics into national programs in the same
structured fashion that has been used for standard and second-line tuberculosis
drugs is possible, but only if leaders confront a range of issues that will make
implementation possible—from lifting import taxes to improving laboratory
capacity to modifying disease control guidelines. Is this too much to ask to give
our health-care practitioners the tools they need to do their jobs?
EMERGING TOOLS FOR MICROBIAL DIAGNOSIS,
SURVEILLANCE, AND DISCOVERY
W. Ian Lipkin, M.D.
Columbia University
Thomas Briese, Ph.D.6
Columbia University
Introduction
Here we describe methods and perspectives for pathogen surveillance and
discovery, and discuss challenges associated with proving causality. We provide
examples from our own experience to illustrate the complexity of pursuing
Jerome
L. and Dawn Greene Infectious Disease Laboratory, Mailman School of Public Health.
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global infectious disease surveillance and detection
research in this arena and to provide the reader with insights into the process that
led to the implementation of particular strategies.
Proof of Causation
Discovery of an organism in association with disease is only the first step in
understanding its role in pathogenesis. Many have wrestled with the challenge
of codifying the process of proving causation. Based on the germ theory of
disease formulated by Pasteur, Koch, and Loeffler proposed precise criteria that
define a causative relationship between agent and disease: The agent should be
present in every case of a disease, it should be specific for a disease (i.e., present in none other), and it should be propagated in culture and proven capable of
causing the same disease upon inoculation into a naïve host. Known as Koch’s
postulates (Koch, 1891), these criteria were subsequently modified by Rivers for
specific application to viruses (Rivers, 1937), and by Fredricks and Relman to
reflect the advent of molecular methods (Fredricks and Relman, 1996) (Table
3-2). Nonetheless, Koch’s postulates remain the ideal standard by which causality is considered to be proven. There are problems with holding to this standard.
Some agents cannot be propagated in culture. Additionally, for many human
viral pathogens, there may be no animal model. In many acute viral diseases, the
responsible agent can be readily implicated because it replicates at high levels
in the affected tissue at the time the disease is manifest, morphological changes
consistent with infection are evident, the agent is readily identified with classical
or molecular methods, and there is evidence of an adaptive immune response.
However, implication of viruses in chronic diseases may be confounded because
persistence requires restricted gene expression, classical hallmarks of infection
are absent, and/or mechanisms of pathogenesis are indirect or subtle. In the final
analysis, investigators are occasionally left with what amounts to an assessment
of strength of epidemiological association based on the presence of the agent,
its footprints (nucleic acid, and preferably, an immune response), and biological
plausibility based on analogy to diseases with related organisms where linkage
is persuasive.
Many Routes to Microbial Pathogenesis
Implication of an infectious agent is most straightforward in instances where
it is present at the site of disease at the time the disease is manifest. Two classic
examples where effects are readily appreciated at the infection site are poliomyelitis, where virus replicates in motor neurons of the brain and spinal cord,
causing cell loss and paralysis, and cholera, where Vibrio cholerae replication
and local elaboration of toxin in the intestine alters ion transport, resulting in
diarrhea. A more complex example of intoxication is botulism where replication
of Clostridium botulinum in the skin or the gastrointestinal tract leads to local
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DETECTION AND DIAGNOSTICS
TABLE 3-2 Criteria for Proof of Causation
Robert Koch (1890)a
Thomas R. Rivers (1937)
Fredricks and Relman (1996)
A microbe must be:
• P
resent in every case of a
disease.
• A
specific virus must be
found associated with a
disease with a degree of
regularity.
• C
andidate sequences should
be present in most cases of
disease and at sites of disease.
• Specific for that disease.
• I solated, propagated,
in culture, and shown
to induce disease upon
inoculation into the
experimental host.
• R
eisolated from the
experimental host wherein
the original syndrome is
replicated.
NOTE: This fourth postulate
though not required by Koch,
logically follows his other
conditions and so has been
added by some reviewers.
NOTE: The possibility of
a viral carrier state was
recognized and Koch’s
requirements of propagation
in media or cell culture was
abandoned.
• T
he virus must be shown
to be the causative agent
of disease in the sick
individual.
• F
ew or no sequences should
be present in host or tissue
without disease.
• S
equences should diminish
in frequency with resolution
of disease and increase with
relapse.
• S
equences should be present
prior to the onset of disease.
NOTE: The pathogen should
be present at the proper time
in specific regions and the
disease should be produced
with some regularity by
serious inoculation of
infected material into a
susceptible host.
aAlthough
Koch included basic points already in earlier papers, especially his 1884 paper on the
etiology of tuberculosis, his most explicit presentation was given at the 1890 International Congress
of Medicine; the proceedings of which were published in 1891.
SOURCE: Koch (1891); Rivers (1937); Fredricks and Relman (1996).
expression of a toxin that traffics to the neuromuscular junction to interfere with
motor function. Host responses to infection may contribute to pathogenesis.
Acute infection with influenza virus or severe acute respiratory syndrome (SARS)
coronavirus elicits cytokines and chemokines that cause pulmonary dysfunction. Chronic inflammation in hepatitis B and hepatitis C infections can result in
hepatic failure and hepatocellular carcinoma. Infection can also lead to inhibition of immune function. The capacity of viruses to enhance susceptibility to
opportunistic agents is now best known in the context of HIV/AIDS; however, the
observation of virus-induced immunosuppression dates back to the early 1900s
when von Pirquet noted the loss of skin reactivity to tuberculin in association with
measles infection. The effects of infection may depend on the age and maturation status of the host. Individuals at either extreme of life are at increased risk
for acute morbidity and mortality with a wide variety of infections. Encephalitis
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global infectious disease surveillance and detection
is far more common in individuals infected with West Nile virus after the age
of 50 years than in other adults or children. Infection during organogenesis may
have different consequences than at other times. Congenital rubella infection, for
example, can be associated with characteristic cardiac and central nervous system
defects. Persistent viral infections are described in animal models where subtle
effects on cellular physiology result in alterations in the expression of neurotransmitters or hormones that have profound effects including cognitive impairment,
hypothyroidism, or diabetes mellitus. Whether similar mechanisms can be implicated in human disease remains to be determined; nonetheless, these preclinical
studies indicate biological plausibility. Infection can break tolerance for “self,”
resulting in autoimmune disease. A classical example is molecular mimicry in
group A beta-hemolytic streptococcus infection where cross-reactivity to heart
and brain results in valvular disease and chorea, respectively. The capacity for
infections to cause disease via myriad mechanisms, direct and indirect, short and
long term, pose challenges for pathogen discovery.
Molecular Strategies for Pathogen Discovery
Methods for cloning nucleic acids of microbial pathogens directly from
clinical specimens offer new opportunities to investigate microbial associations
in chronic diseases (Relman, 1999). The power of these methods is that they can
succeed where methods for pathogen identification through serology or cultivation may fail due to absence of specific reagents or fastidious requirements for
agent replication. Over the past decade, the application of molecular pathogen
discovery methods resulted in identification of novel agents associated with both
acute and chronic diseases, including Borna disease virus, hepatitis C virus, Sin
Nombre virus, HHV-6, HHV-8, Bartonella henselae, Tropheryma whippelii, West
Nile virus, and SARS coronavirus (Challoner
���������������������������������������������
et al., 1995; Chang et al., 1994;
Choo et al., 1989; Lipkin et al., 1990; Nichol et al., 1993; Relman et al., 1990,
1992; VandeWoude et al., 1990).
Various methods are employed or proposed for cultivation-independent characterization of infectious agents. These can be broadly segregated into methods
based on direct analysis of microbial nucleic acid sequences (e.g., complementary DNA [cDNA] microarrays, consensus polymerase chain reaction [cPCR],
representational difference analysis [RDA], differential display [DD]), direct
analysis of microbial protein sequences (e.g., mass spectrometry), immunological systems for microbe detection (e.g., expression libraries, phage display), and
host response profiling.
The decision to employ a specific method is guided by the clinical features,
epidemiology, and spectrum of potential pathogens to be implicated. Expression libraries, composed of cDNAs or synthetic peptides, may be useful tools
in the event that large quantities of acute and convalescent sera are available for
screening purposes; however, the approach is cumbersome and labor-intensive,
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and success depends on the presence of a specific, high-affinity humoral immune
response. Mass spectrometry is an intriguing approach to pathogen discovery
(Dalluge, 2000; van Baar, 2000); however, potential confounds include mutations in flora that alter spectra without clinical correlation; the requirement for
establishment of large libraries of spectra representing flora of thousands of orga
nisms propagated in vitro and isolated in vivo; and the difficulties associated with
extending this technology to viruses, where disease may occur without robust
protein expression, and pathogenicity may be correlated with single base substitutions. The utility of host response messenger RNA (mRNA) profile analysis has
been demonstrated in several in vitro paradigms and some inbred animal models
(Diehn and Relman, 2001; Taylor et al., 2000; Zhu et al., 1998); nonetheless, a
variety of organisms may activate similar cascades of chemokines, cytokines,
and other soluble factors that influence host gene expression to produce what
are likely to be convergent gene expression profiles. RDA is an important tool
for pathogen identification and discovery. However, RDA is a subtractive cloning method for binary comparisons of nucleic acid populations (Hubank and
Schatz, 1994; Lisitsyn et al., 1993). Thus, although ideal for analysis of cloned
cells or tissue samples that differ only in a single variable of interest, RDA is
less well suited to investigation of syndromes wherein infection with any of several different pathogens results in similar clinical manifestations, or infection is
not invariably associated with disease. An additional caveat is that because the
method depends on the presence of a limited number of restriction sites, RDA is
most likely to succeed for agents with large genomes. Indeed, in this context, it is
noteworthy that the two viruses detected by RDA were herpesviruses (Challoner
et al., 1995; Chang et al., 1994).
Consensus PCR also has been a remarkably productive tool for biology. In
addition to identifying pathogens, this method has facilitated identification of a
wide variety of host molecules, including cytokines, ion channels, and receptors.
One difficulty in applying cPCR to pathogen discovery in virology has been that
it is difficult to identify conserved viral sequences of sufficient length to allow
cross-hybridization, amplification, and discrimination in a traditional PCR format. Although this may not be problematic when one is targeting only a single
virus family, the number of assays required becomes infeasible when preliminary
data are insufficient to permit a more directed, efficient analysis. To address
this problem, we adapted cPCR to differential display, a PCR-based method for
simultaneously displaying the genetic composition of multiple sample populations in acrylamide gels (Liang and Pardee, 1992). This hybrid method, known
as domain-specific differential display (DSDD), employs short, degenerate primer
sets designed to hybridize to viral genes that represent larger taxonomic categories than can be resolved in cPCR. Although this modification allowed us to identify West Nile virus as the causative agent of the 1999 New York City encephalitis
outbreak (Briese et al., 1999), it did not resolve issues of low throughput with
cPCR due to limitations in multiplexing.
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To address the need for sensitive, facile, highly multiplexed pathogen surveillance, we established two new platforms for viral detection, MassTag PCR
and the GreeneChip. MassTag PCR is a multiplex PCR method that can accommodate in excess of 20 genetic targets with sensitivity in the range of 10 to 1,000
RNA copies (variability is a function of primer degeneracy). The GreeneChip
is a comprehensive viral microarray that addresses all vertebrate viruses in the
International Committee on Taxonomy of Viruses (ICTV) database. Both methods rely on the presence of an agent related to one already known. In instances
where agents are novel or sufficiently distant in sequence to related agents to
confound hybridization it may be necessary to resort to subtractive cloning
or high-throughput unbiased sequencing. Our algorithm for characterization of
clinical materials is illustrated in Figure 3-7. Where the list of candidates to be
considered can be addressed using MassTag PCR this is our method of choice
due to low cost, speed, and sensitivity. Where MassTag PCR fails or the list of
candidates exceeds 30 targets, we move to GreeneChips (viral or panmicrobial).
In the event that GreeneChips fail we shift to unbiased high-throughput sequencing or subtractive cloning.
MassTag PCR
Although singleplex PCR assays are well established in clinical microbiology and have proved indispensable in management of HIV and hepatitis C virus
(HCV), and in control of outbreaks where an agent is identified, multiplex assay
applications have lagged behind. Fluorescence reporter systems in real-time PCR
achieve quantitative detection with sensitivity similar to nested amplification;
however, their capacity to simultaneously query multiple targets is limited to
the number of fluorescent emission peaks that can be unequivocally separated.
At present up to four fluorescent reporter dyes are detected simultaneously. To
address the need for highly multiplexed assays, we created MassTag PCR, a
platform wherein digital mass tags rather than fluorescent dyes serve as reporters
(Figure 3-8). The first description of this method was published in the context of
a panel that distinguishes 22 different viral and bacterial respiratory pathogens
(Briese et al., 2005). It allowed us to identify viral and bacterial sequences in
respiratory samples as well as cultured materials, and to recognize instances of
coinfection not appreciated in reference laboratories using established diagnostics
assays. We later expanded the repertoire to include causative agents of hemorrhagic fever, and to subtype influenza viruses. Between October and December
2004, an increased incidence of influenza-like illness (ILI) was recorded by the
New York State Department of Health that tested negative for influenza virus by
molecular testing, and negative for other respiratory viruses by culture. Concern
that a novel agent might be implicated led us to investigate clinical materials
(Lamson et al., 2006). MassTag PCR resolved 26 of 79 previously negative
samples, revealing the presence of rhinoviruses in a large proportion of samples,
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DETECTION AND DIAGNOSTICS
Clinical specimen
Short candidate list
<30 agents
Refine:
MassTag primers
GreeneChip probes
Long candidate list
>30 agents
MassTag PCR
6 hours
GreeneChip
14 hours
(-)
(-)
(+)
High-throughput
sequencing
1 week
(+)
Sequencing
Surveillance/Causation
Quantitative real-time PCR
serology
FIGURE 3-7 A staged strategy for pathogen detection and discovery.
SOURCE: Lipkin (2006).
3-7
1. PCR Amplification with mass tag primers
4. Automated sample injection, photocleavage
A
Cleavage of mass tags from amplicon
Ultraviolet Light
B
A
A
B
B
Purified samples
1 1/2 min per sample
2 1/2 hrs for 96 analyses
96 well thermocycler plate
Ionization and detection
MS
A
A B
A
B
A
A B
B
A B
B
2. Product purification on filter plate
5. Detection and pathogen identification
B
Abundance
A
3. Elution into 96 well loading plate
for mass spectrometer analysis
Mass Size
FIGURE 3-8 Schematic representation of MassTag PCR procedure.
SOURCE: Briese et al. (2005).
3-8
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global infectious disease surveillance and detection
about half of which belonged to a previously uncharacterized genetic clade. The
2004 New York ILI study confirmed the utility of MassTag PCR for surveillance,
outbreak detection, and epidemiology by demonstrating its potential to rapidly
query samples for the presence of a wide range of candidate viral and bacterial
pathogens that may act alone or in concert.
MassTag PCR may not suffice in instances where either larger numbers of
known pathogens must be considered or sequence divergence may impair binding of PCR primers. The limitations of MassTag PCR (and other PCR platforms)
were poignantly demonstrated during analysis of samples from Marburg hemorrhagic fever outbreaks in the Democratic Republic of Congo during 1998–1999
wherein two of five subjects were negative. The explanation for failure became
clear after cPCR amplification and sequencing revealed three mismatches in
the forward and one in the reverse primer (Palacios et al., 2006). If we had
enjoyed our current access to unpublished, proprietary filovirus sequences at the
time primers were designed, we would have averted difficulty in this instance.
Nonetheless, despite access to sequences in World Health Organization (WHO)
network laboratories, this experience reinforced the need for a complementary
tool with higher tolerance for sequence divergence, and led us to develop the
GreeneChip, a DNA microarray system.
Establishment of the Greene Microbial Database
A critical early step in the development of the MassTag PCR and microarray tools was the establishment of a viral sequence database. This effort was
facilitated in 2002 by the move of the ICTVdB (International Committee on
Taxonomy of Viruses Database) and its director, Cornelia Büchen-Osmond, from
Biosphere 2 (Earth Institute) in Oracle, Arizona, to the Greene Laboratory; and
the establishment of a Northeast Biodefense Center Biomedical Informatics Core.
Because vertebrate viruses are highest priority for human disease, we focused on
them first, with a plan to extend the database to viruses of invertebrates, plants,
and prokaryotes as resources permitted. To ensure comprehensive coverage, we
included every vertebrate virus listed in the ICTVdB, a taxonomic database that
describes viruses at the levels of order, family, genus, and species. Efforts to
identify cognate sequences for members of each of these taxa in the National
Center for Biotechnology Information (NCBI) sequence database proved to be
more difficult than anticipated. The NCBI database is not exhaustively curated;
thus, it contains many entries where annotation is missing, outdated, or inaccurate. An additional confound is that only incomplete sequence is available for
many viruses, bacteria, and parasites, particularly some relevant to this project,
where genomic sequencing efforts are less advanced. To circumvent limitations
in curation and nomenclature in the NCBI database, and to minimize computa See
http://phene.cpmc.columbia.edu.
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DETECTION AND DIAGNOSTICS
tional costs in establishment of multiple alignments at the nucleotide (nt) level,
we began construction of the Greene Viral Database (GreeneVrdB) by using the
Protein Families database of alignments (Pfam) and Hidden Markov Models
(HMM). Sequences for the design of oligonucleotide probes and MassTag PCR
primers were selected based on biological parameters, including the degree of
conservation of proteins or domains, their expression level during infection, and
the amount of data available for the respective region.
The GreeneVrdB was established by integrating the taxonomy database
of ICTV and the sequence database of NCBI (Figure 3-9). The majority of
viral protein coding sequences in the NCBI database (84 percent) were represented in the Pfam database; the remainder were mapped using pair-wise Basic
Local Alignment Search Tool (BLAST) alignments. A panmicrobial database
(GreenePmdB) was established by supplementing the GreeneVrdB with ribosomal RNA (rRNA) sequences of fungi, bacteria, and parasites obtained from
the Ribosomal Database Project (RDP)10 or the NCBI database. At the time
of this writing the GreenePmdB comprises the 382,512 viral sequences of the
GreeneVrdB, representing both complete and partial viral genomes; 41,790 bacterial 16S rRNAs; 4,109 fungal 18S rRNAs; and 2,626 18S parasitic rRNAs.
These sequences represent all 2,011 vertebrate virus species and 135 bacterial,
73 fungal, and 63 parasite genera.
GreeneChips
DNA microarrays have potential to provide a platform for highly multiplexed
differential diagnosis of infectious diseases. The number of potential features far
exceeds that with any other known technology. Furthermore, probes of up to 70
nt are not uncommon. Thus, unlike PCR where short primer sequences demand
precise complementarity between probe and target, DNA arrays are less likely
to be confounded by minor sequence mismatches. Lastly, one can incorporate
both microbial and host gene targets. This affords an opportunity to both detect
microbes and assess host responses for signatures consistent with various classes
of infectious agents. Despite these advantages, DNA arrays have not been widely
employed because of limited sensitivity. Although a viral array was helpful in
identifying the causative agent of SARS in 2003, critical to its success was the
discovery that the agent could be propagated to high titer and had cytopathic
effect in Vero cells (Ksiazek et al., 2003). Once this advance was shared, several
investigators rapidly and independently identified the agent by electron microscopy, differential display, cDNA cloning, microarray, and cPCR. The challenge
of array sensitivity has now been addressed with improved methods for sample
See
http://pfam.wustl.edu.
http://www.ncbi.nih.gov.
10 See http://rdp.cme.msu.edu.
See
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global infectious disease surveillance and detection
ICTVdB
NCBI sequence data
(International Committee on
Taxonomy of Viruses)
(National Center for
Biotechnology Information)
Panmicrobial sequence database
Viral sequence
database
382,512 viruses
382,512
41,790
bacteria
4,109 fungus
2,626 parasites
Pfam database
(Protein FamiIies)
RDP
(Ribosomal Database Project)
+
NCBI
FIGURE 3-9 Greene pathogen database.
SOURCE: Lipkin (2006).
preparation, amplification, labeling, and printing. Together with Agilent Technologies, we created a DNA array platform suited to analysis of clinical materials
without amplification in culture. Investigation
by MassTag PCR and viral DNA
3-9
microarray of blood collected during the 2005 Angola Marburg virus outbreak
from an individual who died of hemorrhagic fever failed to yield a pathogen;
however, implementation of a panmicrobial DNA array, GreeneChipPm, implicated Plasmodium falciparum infection (Palacios et al., 2007).
Microbial Probes
Viral probes were designed to represent a minimum of three distinct genomic
target regions for every family or genus of vertebrate virus in the ICTVdB.
Where possible, we chose highly conserved regions within coding sequence
for an enzyme such as a polymerase, and two other regions corresponding to
more variable structural proteins. Our reasoning was that RNAs encoding structural proteins may be present at higher levels than those encoding proteins
needed only in catalytic amounts, and that use of probes representing noncontiguous sites along the genome might allow detection of naturally occurring or
intentionally created chimeric viruses. The viral array has been through several
iterations as the database evolved and technology allowed increases in probe
density. The first release, GreeneChipVr1.0, comprised a total of 9,477 viral
probes. The second release, GreeneChipVr1.1, added 6,271 more typing probes
for influenza virus A hemagglutinin and neuraminidase genes. Recent releases,
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GreeneChipVr1.5 (15,700 probes) and GreeneChipVr2.0 (86,300 probes), are the
result of higher printing density on the Agilent array platform and a new generation of probe design algorithms. The process for identifying bacterial, fungal, and
parasitic probes was similar, although restricted to 16S and 18S rRNA sequences.
GreeneChipPm1.0 contained a total of 29,495 probes, including the probes comprising GreeneChipVr1.1 as well as 11,479 16S rRNA bacterial, 1,120 18S rRNA
fungal, and 848 18S rRNA parasite probes.
Host Gene Markers
Identification of signal(s) representing a microbe in samples from affected
subjects is a primary objective in pathogen discovery. Nonetheless, evidence of
infection is bolstered by coterminous evidence of gene expression consistent with
an activated host immune response. Furthermore, gene expression profiles may be
helpful in implicating specific strains or serotypes (e.g., Th1 cytokine responses
are more robust with H5N1 than H1N1 influenza infection) (Cheung et al., 2002).
Finally, in cases where we fail to find clear evidence of a known pathogen, a
profile consistent with immune activation may be helpful in determining whether
to pursue additional studies focused on pathogen discovery. Thus, GreeneChips
include probes for genes associated with cytokines, chemokines, and their receptors; components of the interferon-inducible signaling pathways; immunoglobulins (Igs) and Ig receptors; toll-like receptors and their downstream signaling
pathways; complement components; major histocompatibility complex (MHC)
molecules; and heat shock proteins from a set of validated oligonucleotides
(Wright and Church, 2002).
GreeneLAMP Analysis Software and GreeneChip Validation
GreeneLAMP (Log-transformed Analysis of Microarrays using P-values)
version 1.0 software was created to assess results of GreeneChip hybridizations.
Common analysis software focuses on the differential two-color analysis used in
gene expression arrays, which is not applicable to the GreeneChip. GreeneLAMP
has a robust and generalized framework for microarray data analysis, including:
flexible data loading, filtering, and control experiment subtraction. Probe intensities are background corrected, log2-transformed, and converted to Z-scores (and
their corresponding p-values). Where available, control matched experiments
from uninfected samples are used and spots >2 standard deviations (SD) from
the mean are subtracted. In instances where matched control samples are not
available, the background distribution of signal fluorescence is calculated using
fluorescence associated with 1,000 random 60-mers (Null probes). In both scenarios, positive events are selected by applying a false-positive rate of 0.01 (the
rate at which Null probes are scored as significant) and a minimum p-value per
probe of 0.1 (in cases with a matching control) and 0.023 (2 SD; in cases without
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global infectious disease surveillance and detection
a matching control). A map, built from a Basic Local Alignment Search Tool for
nucleotides (BLASTN) alignment of probes to the Greene Pathogen Database,
is used to connect probe sequences to the respective entries in the Greene Pathogen Database. Each of those sequences corresponds to an NCBI Taxonomy ID
(TaxID). The individual TaxIDs are mapped to nodes in a taxonomic tree built
based on ICTV virus taxonomy or NCBI taxonomic classification for other organisms. The program output is a ranked list of candidate TaxIDs. Candidate TaxIDs
are ranked by combining the p-values for the positive targets for that TaxID using
the QFAST method of Bailey and Gribskov (Bailey and Gribskov, 1998).
The specificity of the viral GreeneChip was assessed using extracts of cultured cells infected with adeno-, alpha-, arena-, corona-, entero-, filo-, flavi-,
herpes-, orthomyxo-, paramyxo-, pox-, reo-, and rhabdoviruses (a total of 49
viruses). All were accurately identified by GreeneLAMP analysis. To assess
sensitivity, viral RNA extracted from infected cell supernatants (adeno-, West
Nile, St. Louis encephalitis, respiratory syncytial, entero-, SARS corona-, and
influenza viruses) was quantitated by real-time PCR, serially diluted, and subjected to GreeneChip analyses. The threshold of detection for adenovirus was
10,000 RNA copies; the threshold of detection for the other reference viruses
was 1,000 RNA copies per reverse transcription (RT)-reaction. The respiratory
GreeneChip was tested for detection and typing with 31 influenza virus A and B
reference strains of human and animal origin and, because reference strains represent only a limited fraction of the genetic variability, with numerous circulating
human influenza virus strains isolated worldwide since 1999. In summary, a total
of 69 viruses comprising 54 influenza virus A and B isolates of human, avian,
and porcine origin and 15 non-influenza human respiratory viruses were tested,
identified, and subtyped.
GreeneChips were also validated with clinical samples from patients with
respiratory disease, hemorrhagic fever, tuberculosis, and urinary tract infections,
and were demonstrated to identify human enterovirus A, human respiratory syncytial virus A, influenza A virus, Lake Victoria marburgvirus, SARS coronavirus,
lactobacillus, mycobacteria, and gammaproteobacteria in various specimen types,
including cerebrospinal fluid, nasopharyngeal swabs, sera/plasma, stools, and
urine.
Recovery of Hybridized Sequences from GreeneChips
Arrays can facilitate cloning and sequence analysis as well as pathogen identification. Hybridized products typically range from 200 nt to >1,000 nt. Because
GreeneChips display three or more probes representing different genomic regions
for each virus, one can rapidly recover sequence not only for hybridized products
but also for sequences between those products through use of PCR.
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189
Unbiased High-Throughput Sequencing
The advent of high-throughput sequencing technology affords unique
opportunities for pathogen discovery. Unlike consensus PCR or array methods
where investigators are limited by known sequence information and must make
choices regarding the range of pathogens to consider in a given experiment,
high-throughput sequencing is unbiased. Several systems are in development. We
have experience with the pyrosequencing system of 454 Life Sciences; however,
the principles for sample preparation and data analysis are broadly applicable
across platforms. Because all nucleic acid in a sample (whether host or pathogen) is amplified and sequenced, elimination of host nucleic acid can be critical
to boosting pathogen signal toward the threshold for detection. Our approach is
to apply a similar sample preparation and random PCR amplification protocol
as developed for the GreeneChip including extensive DNase I treatment of the
RNA template to remove host chromosomal DNA. This process obviates the
potential for detecting DNA genomes of pathogens; however, our reasoning is
that an active infection should be associated with transcription. After amplification and sequencing reads typically range in size from 40 to 400 base pairs. Raw
sequence reads are trimmed to remove sequences derived from the amplification
primer and filtered to eliminate highly repetitive sequences. After trimming and
eliminating repeats, sequences are clustered into nonredundant sequence sets.
Unique sequence reads are assembled into contiguous sequences, which are then
compared to the nonredundant sequence databases using programs that examine
homology at the nucleotide and amino acid levels (using all six potential reading
frames with adjustments for sequence gaps). Specific PCR tests are then designed
to examine association with disease, measuring burden, and obtaining additional
sequence for phylogenetic characterization.
Vignettes in Pathogen Discovery
Borna Disease Virus and Neuropsychiatric Disease
In 1985, Rott and Koprowski reported that serum from patients with bipolar
disorder reacted with cells infected with Borna disease virus (BDV), an unclassified infectious agent named after a town in Saxony (eastern Germany) that had
large outbreaks of equine encephalitis in the late 1800s. Intrigued both by the
concept that infection might be implicated in a neuropsychiatric disease, and
that established methods for virus isolation had failed, we and others began to
pursue characterization of this elusive neurotropic virus using molecular tools.
BDV nucleic acids were isolated by subtractive hybridization in 1989, the first
successful application of subtractive cloning in pathogen discovery (Lipkin et al.,
1990). This effort relied on cDNA cloning with home brew kits as it preceded the
advent of polymerase chain reaction and ready access to sequencing technologies.
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global infectious disease surveillance and detection
The correlation between cloned materials and disease was achieved by demonstrating that (1) candidate cDNAs competed with RNA template from brains of
infected rats for transcription and translation of a protein biomarker present in
brain (hybrid arrest experiments), (2) the distribution of candidate nucleic acid
correlated with pathology in brains of experimentally infected rats and naturally
infected horses (in situ hybridization), and (3) no signal was obtained in Southern hybridization experiments, wherein normal brain was probed with candidate
clones. Based on northern hybridization experiments the genome was variously
reported as a 8.5 kb negative polarity RNA or an 11 kb positive polarity RNA.
Over the next 5 years, the genome was cloned, and the virus was visualized and
classified as the prototype of a new family of nonsegmented negative-strand
(NNS) RNA virus with unusual properties: nuclear replication/transcription,
posttranscriptional modification of selected mRNA species by splicing, low-level
productivity, broad host range, neurotropism, and capacity for persistence (Briese
��������
et al., 1992, 1994; Cubitt et al., 1994; de la Torre, 1994; Schneemann et al.,
1995; Schneider et al., 1994). It
�����������������������������������������������������
was widely held that the introduction of specific
reagents such as recombinant proteins and nucleic acid probes would allow rapid
assessment of the role of BDV in human disease. However, in a classic example
of the pitfalls of PCR diagnostics, particularly using nesting methods, BDV
was implicated in a wide variety of disorders that included unipolar depression,
bipolar disorder, schizophrenia, chronic fatigue syndrome, AIDS encephalopathy,
multiple sclerosis, motor neuron disease, and brain tumors (glioblastoma multiforme) (Lipkin et al., 2001; Schwemmle et al., 1999). At the time of this writing,
there is no conclusive evidence that BDV infects humans. BDV is nonetheless a
fascinating virus, and its discovery has yielded intriguing models of viral pathogenesis, and provided guidance regarding methods for rigorously investigating
the role of infection in chronic disease with sensitive molecular tools. It is worth
noting that the two years of molecular gymnastics required to identify BDV could
be collapsed into a few weeks with current art. However, even with the explosion
in viral sequence data over the past decade, BDV is sufficiently different that it
could not be identified by consensus PCR or microarrays based on sequences
other than those representing Bornaviridae. To our knowledge it is unique in
this respect.
West Nile Virus Encephalitis
In late August 1999, health officials reported an outbreak of encephalitis
accompanied by profound weakness in Queens, New York. There was neither an
apparent increase in the frequency of encephalitis in New York, nor an automatic
reporting event that resulted in detection of the outbreak. Thus, the recognition of
the syndrome was due to the clinical acumen of Deborah Asnis, an infectious diseases physician at Flushing Hospital Medical Center, and Marcelle Layton, Assis-
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DETECTION AND DIAGNOSTICS
191
tant commissioner, Communicable Disease Program, New York City Department
of Health, and their associates.
On September 3, serology for the presence of antibodies to North American
arboviruses yielded results consistent with infection with St. Louis encephalitis virus (SLEV) (Asnis et al., 2000). St. Louis encephalitis (SLE) had not
been reported previously in New York although mosquito vectors competent
for transmission of SLE were present. Investigation of the outbreak epicenter
revealed sites of active mosquito breeding and early victims of the outbreak had
histories consistent with mosquito exposure. Thus, on September 3, a mosquito
eradication program was adopted by the state and by the city of New York. Concurrently, wildlife observers independently noted increased mortality of avian
species, including free-ranging crows and exotic birds housed in the Bronx Zoo.
Tracy McNamara, a veterinary pathologist at the Wildlife Conservation Society,
performed histologic analysis of birds and found meningoencephalitis, gross
hemorrhage of the brain, splenomegaly, and myocarditis (Steele et al., 2000).
Although 70 percent of emerging infectious diseases are zoonoses and the coincidence between the human and nonhuman outbreaks was striking, McNamara
was unable to persuade her colleagues in human infectious disease surveillance
to review materials. She forwarded tissue samples from diseased birds to the U.S.
Department of Agriculture (USDA) National Veterinary Service Laboratory in
Ames, Iowa, where virus was cultured and electron micrographs reported to be
consistent with the presence of either a togavirus or a flavivirus. Thereafter the
avian virus was forwarded from USDA to the Centers for Disease Control and
Prevention (CDC) in Fort Collins, Colorado, for molecular analysis (Lanciotti et
al., 1999).
On September 13–15, the CDC Encephalitis Project (composed of centers
in California, New York, and Tennessee) held its annual meeting in Albany, New
York. Data emerging from both California and New York over an 18-month survey period indicated that an etiological agent was never identified in 70 percent
of cases of encephalitis despite culture, serology, and molecular analyses. In this
context, our group was invited to discuss methods for identification of unknown
pathogens and to consider application to project samples of a new method for
amplifying viral nucleic acids, domain-specific differential display (DSDD).
Sherif Zaki at CDC Atlanta had demonstrated the presence of flavivirus protein
in brains of human victims of the New York City outbreak; however, efforts to
amplify SLEV or other flaviviral sequences by conventional reverse transcription
PCR (RT-PCR) had been unsuccessful. Employing several degenerate primer
sets designed to target in DSDD highly conserved domains in the NS3, NS5, and
3’-untranslated regions of flaviviruses, we obtained positive results for four of
the five New York patients in only a few hours. Sequence analysis confirmed the
presence of a lineage one West Nile virus (Briese et al., 1999; Jia et al., 1999).
Concurrently, our colleagues at CDC in Fort Collins reported West Nile-like
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global infectious disease surveillance and detection
sequences in cell lines infected with homogenates from New York birds. In concert these findings confirmed that the outbreak in New York City was a zoonosis
due to West Nile virus (WNV).
Subsequently, we established quantitative real-time PCR assays for sensitive high-throughput detection of virus in clinical materials and mosquito pools.
Analysis of blood samples from infected humans revealed the presence of WNV
sequences in late 1999 (Briese et al., 2000); however, the significance of humanhuman transmission was not appreciated until 2002, when transmission through
organ transplants and blood transfusion led to implementation of blood screening
by nucleic acid amplification tests (CDC, 2003, 2004). This outbreak illustrates
the power of molecular methods for addressing the challenges of emerging
infectious diseases. As an example of an emerging zoonosis it also underscores
the significance of enhancing communication between the human and veterinary
medicine communities.
Enteroviruses and Amyotrophic Lateral Sclerosis
Amyotrophic lateral sclerosis (ALS) is a disorder characterized by progressive loss of motor neurons and muscle atrophy. An inherited form caused by
mutations in the superoxide dismutase gene has been described; however, the
majority of cases are idiopathic. In 2000 Berger and colleagues, using nested
PCR, sequencing, and in situ hybridization methods, reported the striking finding that 15 of 17 French subjects with ALS, and only 1 of 29 subjects with
other neurologic diseases had sequences of a novel echovirus in the spinal
cord (Berger et al., 2000). Although other enteroviruses such as poliovirus and
human enterovirus 71 have been unequivocally implicated in acute motor neuron disease, this publication was the first to provide compelling evidence that
enteroviruses could cause slowly progressive chronic neurologic disease. Given
the potential utility of antiviral treatment of this devastating neurodegenerative
disorder we were encouraged by the National Institute of Neurological Disorders and Stroke (NINDS) to try to independently replicate the echovirus data.
Our experience in the BDV field, where problems with PCR hygiene had led
to spurious links to disease, was invaluable in directing experimental design.
Whereas the Berger group had used RNA template extracted from sections cut
on cryostats and analyzed by nested PCR in the same laboratory, we collected
frozen tissues from two tissue banks, extracted RNA in a laboratory with no
history of virus research, and performed blinded real-time PCR analyses in yet
another laboratory. Real-time PCR is similar in sensitivity to nested PCR but is
less sensitive to false-positive results because assays are performed in a closed
system wherein signal is read as fluorescent signal. Analysis of spinal cord and
motor cortex from 20 subjects with ALS and 14 controls revealed no echovirus
sequences (Walker et al., 2001). These results were well received by colleagues
but elicited less positive correspondence from some individuals who noted that
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DETECTION AND DIAGNOSTICS
our publication was foreclosing a promising research lead and clinical trials
with antiviral drugs.
Future Perspectives
Technologies will continue to evolve, allowing faster, more sensitive, and
less expensive methods for pathogen surveillance and discovery. Although multiplex PCR is relatively mature, microarray technology is still in its infancy;
near-term modifications already in development include microfluidic sample
processing and direct measurement of conductance changes associated with
hybridization. We have only touched the surface of proteomics and host response
profiling. It is conceivable that biomarkers will be found that are specific for
classes of infectious agents and/or provide insights that can guide clinical management. In chronic diseases the most substantive advances are likely to come not
from technical improvements, but from investments in prospective serial sample
collections and an appreciation that many diseases reflect intersections of genes
and environment in a temporal context.
Acknowledgments
We thank our colleagues at the Scripps Research Institute, the University of
California–Irvine, and Columbia University who have enabled our work in pathogen discovery over a period of more than 20 years. Current efforts are supported
by National Institutes of Health awards AI062705, AI070411, HL083850-01,
AI51292, AI056118, AI55466, AI57158 (Northeast Biodefense Center-Lipkin),
NS047537, and EY017404.
THE POTENTIAL IMPORTANCE OF PRESYMPTOMATIC,
HOST-BASED DIAGNOSIS IN BIODEFENSE AND
STANDARD HEALTH CARE
Stephen Albert Johnston, Ph.D.11
Arizona State University
Abstract
Through programs such as BioShield, BioWatch, and BioSense we have
created a first line of defense against traditional biothreats—our Bio-Maginot
Line. However, the biotechnology revolution is driving the potential to create
engineered pathogens that could circumvent these barriers. The increased risk
inherent in this revolution is unstoppable, and efforts to control the risk through
11 Professor,
Life Sciences; director, Center for Innovations in Medicine, The Biodesign Institute.
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global infectious disease surveillance and detection
regulation are probably unwise. Fortunately, for historical and technical reasons
we may have a window of opportunity to get ahead of this threat curve. Key to
this opportunity is the development of a diagnostic capability that could detect
infections before symptoms appeared. This host-based detection system would
be capable of detecting any type of threat agent—engineered or natural. Key
aspects of this diagnostic system are that it would be capable of reading hundreds
to thousands of blood, sputum, or urine components; rely on self-normalization
by regular testing of individuals; and be widely distributed in homes. Evidence
to date indicates that it may be possible to develop such a system. Obviously, its
cost could not be justified by the unpredictable probability of a biothreat attack.
Fortunately, the need for such a capability for biodefense is exactly in line with
the need for the same capability to transform traditional medicine, most obviously
for detecting natural outbreaks. The current health-care system is economically
unsustainable. One solution to this crisis is to convert standard health practice
from one that treats symptoms to one that detects disease very early—even
presymptomatically. The convergence of the need for presymptomatic diagnosis
capability, both for biodefense and standard medical practice, justifies an Apollolike effort to create this technology.
Particularly since 9/11 there has been increasing concern about biological
attacks. In the area of detection of attacks, we are relying on two basic strategies.
One strategy, BioWatch, would have enough detectors distributed throughout the
country to pick up airborne releases of pathogens. The hope is that a biothreat
release would be detected before people develop symptoms. The problems with
this strategy have been widely debated, but largely come down to the cost–benefit
ratio of sustaining a system that would be effective. There is also the concern
that engineered organisms would not be detected. The second major strategy is
based on sufficient, organized surveillance of health-related data to detect early
evidence of symptomatic people. The BioSense program is one example of this
effort. Unlike BioWatch, this type of approach has a clear crossover advantage
to standard medical practice. However, in the specific application to biothreat
detection, it is dependent on detecting sick people.
Programs such as BioWatch (defined on page 4), BioShield,12 and BioSense13
have created a certain level of defense, largely against pathogens and scenarios
based on analysis from the past century. This Bio-Maginot Line would provide
a measure of defense against the obvious attack. As with the real Maginot Line,
the concern is that the attack would go around the fortifications (Figure 3-10).
Although no one can predict the risk of a future attack, let alone one that would
12 On
July 21, 2004, President Bush signed into law Project BioShield, which provides new tools to
improve medical countermeasures protecting Americans against a chemical, biological, radiological,
or nuclear (CBRN) attack (White House, 2004).
13 BioSense is a national program intended to improve the nation’s capabilities for conducting near
real-time biosurveillance, enabling health situational awareness through access to existing data from
health-care organizations across the country (CDC, 2007).
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195
FIGURE 3-10 The Bio-Maginot Line.
SOURCE: Johnston (2006).
3-10
involve an engineered organism, there is little doubt that the threat will increase
over time. As cartooned in Figure 3-11, this increase is largely due to the biotechnology revolution. The ability to both understand and manipulate life is increasing exponentially. Most measures of technological capability in biotechnology,
like microchips, are obeying Moore’s Law.14 Whether it be growth in sequence
deposits to GenBank (Figure 3-12), ability to sequence DNA, or facility at synthesizing genes, the revolution is amazing.
This revolution will drive remarkable change, but with it will come new
opportunities for ill application. For example, the science of interfering RNAs
started with some strange observations in plants in the 1990s. It progressed
quickly to study in animal systems and now is standard technique for manipulating gene expression. The technology is offered as kits, and several biotechnology
companies are pursuing its medical applications. A Nobel Prize was given for its
discovery in 2006, a record time from discovery to prize. Yet it takes relatively
little imagination to see how the incorporation of RNA interference (RNAi)
constructs into viruses might augment their virulence. Almost every new technology in biotechnology and almost every new understanding of immunology and
host–pathogen interactions could be configured to ill ends.
The same revolution that will drive dramatic new opportunities for contributions from biotechnology will increase the prospects for bad applications,
14 Moore’s
Law states that computing power will double every 1.5 years. This prediction has largely
held.
Copyright © National Academy of Sciences. All rights reserved.
1965
1970
1975
1985
1990
1995
DNA shuffling
1980
Copyright © National Academy of Sciences. All rights reserved.
Risk
FIGURE 3-11 Changing spectrum of biothreat risk.
SOURCE: Johnston (2006).
Genome
sequencing
Recombinant
DNA
1960
Natural pathogens
2000
2005
2010
2015
2020
2025
3-11 broadside
RNA i
Chemical gene
synthesis
Reverse viral genetics
Time
Antibiotic
resistance
Valley of the
shadow of
death
2030
2035
Biorevolution
2040
Decision
driven ∆
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Sequences (millions)
Base pairs of DNA (billions)
DETECTION AND DIAGNOSTICS
Base pairs
Sequences
FIGURE 3-12 Growth of GenBank, 1982–2005.
SOURCE: NCBI (2007).
or even accidental events. The opportunities are dynamic. The sequence of any
pathogen can be determined in one3-12
day. We are rapidly increasing our knowledge
of host–pathogen interactions and the human immune response to infection. As
stated above new technologies are being developed at a rapid pace. In addition,
the ability to set up high-throughput screens is becoming more common. The
combination of these trends will create the potential to create new pathogens
(Figure 3-13).
The impact of these trends is clear. We are moving from a relatively simple
threat space involving a list of potential pathogens and likely scenarios to one
that has much higher dimensionality (Figure 3-14). The implications are that
in the future, lists of relative importance of pathogens (e.g., Select Agent lists)
and likely scenarios of attack are going to become, if they are not already, less
useful.
That is the bad news. There is good news. For all the foreboding, a bioattack
has not occurred since October 11, 2001. Why not if the risk is increasing? There
are probably many explanations. One is that the Soviet biothreat program was
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global infectious disease surveillance and detection
Sequence
of all
microbes
Anything
you
want
New
technologies
Knowledge
of host, bugs,
and disease
mechanisms
HTP
screening
FIGURE 3-13 The combination of rapid knowledge and technological growth will create
the potential to make new pathogens.
SOURCE: Johnston (2006).
3-13
Number of variables
is increasing
NN df
N df
Anthrax
plague
smallpox
glanders
etc.
Any
combination
of microbe
and knowledge
Select Agent lists
scenario-based
strategies
FIGURE 3-14 The threat space is becoming increasingly complex.
SOURCE: Johnston (2006).
3-14
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DETECTION AND DIAGNOSTICS
decommissioned before the real revolution in biotechnology had penetrated their
operation. Second, Islam has placed biology as a low science. This was reflected
in the number of graduate students in biology versus engineering, though this
trend may be changing. Finally, making biothreat agents is still not easy. It would
involve multiple steps and specific reagents. Anything of this nature can easily
have one step go wrong. Of course if enough attempts are made, one will likely
succeed—but the odds are now in our favor.
We may now be in a grace period relative to preparing for a biological
attack—the valley of the shadow of death (Figure 3-11). If we continue to base
our preparedness on protection against specific pathogens or scenarios, we may
be in trouble. An alternative is to invest in developing platform technologies and
strategies that offer broad-based defense. Examples include developing systems
to generate and validate vaccines rapidly, and creating strategies to quickly produce new therapeutics to new pathogens from preexisting modules. However, I
think the most important shift in emphasis would be to host-based diagnosis to
allow presymptomatic detection of infections. The ability to detect infections
before they are symptomatic has obvious value to strategies from quarantine
to antibiotic treatment. It also addresses the problem of detecting the release of
a new pathogen as the sensing is the host itself. Detection is not dependent on
knowing what pathogens might be used.
The premise for this concept is presented in Figure 3-15. All of the factors
that determine a person’s health status could be monitored in near-real time by
Genes
Environment
Age
Serum/cell
components
Sex
State of
health
FIGURE 3-15 Biosignature pattern recognition in human diseases. Host-based presymptomatic detection of events.
SOURCE: Johnston (2006).
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global infectious disease surveillance and detection
profiling all the components of blood. Blood chemistry, or that of sputum or
urine, reflects changes in health, specifically early effects of infection. Continuous monitoring of blood components of healthy individuals would create their
own biosignatures of health and disease (Figure 3-16), the ultimate in personalized diagnostics. Devices capable of generating such biosignatures are already
in development. These units are aimed at a clinical setting largely for application to early detection or characterization of a specific illness, such as cancer. A
DocInBox diagnostic device relevant to biodefense would have to be capable of
detecting the early events of infection against the background of all other causes
of change in health status.
This type of biosignature diagnosis has two distinctive features. Approximately 45 biomarkers are FDA approved. In contrast, biosignatures would involve
measuring hundreds or possibly thousands of blood components. If the basis of
disease could be anything, one has to sample broadly. Second, real-time and
frequent monitoring of individuals would allow normalizing each person’s bio-
State of health
baseline
State of health
Continuous monitoring of the healthy
State of health
FIGURE 3-16 Personalized medicine based on biosignatures.
SOURCE: Johnston (2006).
Copyright © National Academy of 3-16
Sciences. All rights reserved.
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DETECTION AND DIAGNOSTICS
signature to himself or herself. This is in contrast to traditional biomarkers where
diagnosis is made based on values established in the population (Figure 3-17).
To meet these expectations the basic specifications for such a DocInBox are
clear. To detect a pathogen release, the unit must work in near-real time. Most
respiratory infections have a presymptomatic period of a few days at most (Figure
3-18). An assay system that takes a week to process has little value relative to
infections, but would for other chronic ailments. If the goal is presymptomatic
diagnosis obviously well people need to be monitored. Particularly for infectious
disease, it follows that the diagnostic devices should be in the homes or places
of work. Having these units in the physician’s office or emergency room will
do little good in detecting a biothreat release. If the units are to be dispersed in
homes, their operation must be rugged and inexpensive.
There are two issues relative to the possibility of attaining this goal. First,
is presymptomatic diagnosis of infections biologically feasible? The evidence is
scant in this regard. This topic will be the focus of a more extensive review, but
there are some positive indications. In vitro studies have shown that the transcription pattern of dendritic cells changes on exposure to pathogens and that different pathogens elicit different patterns (Huang et al., 2001). This is important as
dendritic cells are in the first line of exposure to pathogens. Microarray analysis
of human blood cells has shown that individual patterns can be monitored over
time (Whitney et al., 2003). Finally, it appears that microarrays of gene expres-
} Normal
Measure
Individual
T=0
Measure
T=1
Biosignature elements
FIGURE 3-17 Biosignatures versus biomarkers.
SOURCE: Johnston (2006).
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global infectious disease surveillance and detection
5 Days
Rhinoviruses
1-4 Days
Influenza
Parainfluenza
4 Days
Respiratory Syncytial
Virus (RSV)
7 Days
7-10 Days
Pertussis
5-8 Days
Adenovirus
Epstein-Barr Virus (EBV)
4-6 Weeks
I I I I I I I I I I I I I I I I I I I I I I I I I I I
1
5
10
15
20
Days
FIGURE 3-18 Upper respiratory disease incubation periods.
SOURCES: Adapted from Meneghetti (2006); Basu (1998); Smith et al. (2006).
sion can also detect presymptomatic responses in primates (Rubins et al., 2004).
3-18
We have preliminary evidence (Johnston and Magee, unpublished) from a model
of cowpox infection in mice that the infected mice can be distinguished from
mock-infected mice three hours after infection, also by microarray analysis of
blood cells. Clearly, more definitive studies of the limitations of presymptomatic
diagnosis are needed.
The other issue is the technological challenge of creating the diagnostic
system. This will be a formidable challenge. It will involve a coordinated, highly
interdisciplinary effort that will include new instrumentation, modeling/algorithm
development, data handling and transmission as well as judicious use of animal models and clinical testing (Figure 3-19). One challenge we have been
addressing is how to develop the binding agents to measure thousands of blood
components.
Though the technological challenges are great, such a diagnostic system is
probably feasible. If developed it would be a major factor in preventing largescale loss from a biothreat attack and may serve as a serious deterrent. However,
the effort and cost to put such a system in place could not be justified based
solely on the probability of a biothreat attack. Though its application to detection of natural outbreaks could be more easily supported, even this use would
probably not drive an economic imperative to initiate this development program.
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DETECTION AND DIAGNOSTICS
Human
studies
Data
management
Animal
models
Instrumentation
DocInBox
Computation
modeling
Biological
detection
Systems
biology
FIGURE 3-19 Program to create DocInBox diagnosis.
SOURCE: Johnston (2006).
Fortunately, a presymptomatic diagnostic system is also needed for another more
easily justifiable application—the impending crisis in standard health care.
The cost of U.S. health care was approximately $2.2 trillion in 2006. This
3-19
cost is estimated to be approximately $4
trillion by 2015 (Figure 3-20). Currently
this cost accounts for approximately 19 percent of our Gross Domestic Product
(GDP), rising to 25 percent or more by 2015 (Figure 3-21). By comparison,
health-care costs have outpaced energy costs since the 1980s (Figure 3-22).
Because most health costs are in the later years of life, with an aging population
these trends are expected to continue (Figure 3-23). Clearly, we spend an enormous amount of our wealth on health care. If this investment contributes substantially to the productivity and creative output of the population it is money well
spent. However, approximately 85 percent of this expenditure is on taking care of
sick people and only about 15 percent on drugs and diagnostics. Our health-care
system costs so much because it is largely postsymptomatic focused, and therefore centered on taking care of sick people. This system is clearly unsustainable
economically. It will require either reducing care or revolutionizing medicine. If
we opt for the latter, the key aspect will be converting medicine to a focus on
presymptomatic diagnosis. A corollary of this transition will be improvement in
quality of life. This will afford a “squaring” of the life curve (Figure 3-24) such
that we not only live longer, but better.
We are fortunate that a key technology required for being prepared for the
biothreats of the future is also the exact capability we have basically no choice
but to develop for standard health care of the future, as well as for more prob-
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Copyright © National Academy of Sciences. All rights reserved.
FIGURE 3-20 Health-care spending projections.
SOURCE: Adapted from HHS (2007).
3-20 broadside
$2.2T 2007
Total U.S. health-care expenditures ($)
$4T 2016
204
Copyright © National Academy of Sciences. All rights reserved.
3-21 Broadside to match 3-20?
18%
FIGURE 3-21 In 2005, 18 percent of GDP was spent on health care. By 2015, it is projected to be 25 to 30 percent.
SOURCE: Adapted from HHS (2007).
Total U.S. health-care expenditure
Gross Domestic Product
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global infectious disease surveillance and detection
Total U.S. energy spending
Total U.S. health-care spending
FIGURE 3-22 Comparison of U.S. spending on energy and health care, 1970–2004.
NOTE: The 2001 to 2004 numbers were projected based on oil prices. Total energy costs
2002–2004: Numbers are estimates based on extrapolation of energy price increase based
on increases in petroleum prices, applied to Department of Defense known energy use
figures. OPEC basket price averaged $50.71
per barrel in 2005, $36.05 per barrel in 2004,
3-22
$28.10 per barrel in 2003, $24.36 per barrel in 2002, $23.12 per barrel in 2001, and $27.60
per barrel in 2000 (DoE, 2006).
SOURCES: EIA (2005); HHS (2007).
$4, 500
$4, 000
$3, 500
$3, 000
$2, 500
$2, 000
$1, 500
$1, 000
$500
$0
All ages Under
25
25–34
35–44
45–54
55–64
65+
65–74
Age
FIGURE 3-23 Average annual health-care expenditures by age, 2005.
SOURCE: DoL (2007).
3-23
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75+
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Survival (quality)
DETECTION AND DIAGNOSTICS
0
0.2
0.4
0.6
0.8
1
1.2
Age
FIGURE 3-24 Human species needs to square life’s curve: Higher quality = less cost.
SOURCE: Johnston (2007).
able threats from natural infections. From the perspective of being prepared for
engineered biothreats, we should take advantage of the valley of the shadow of
death (Figure 3-11) to get ahead of the threat
curve. Presymptomatic diagnosis
3.24
should be a key element in this preparedness. From the perspective of standard of
care, this same technology could be key to revolutionizing us as a species. Such
potential merits an Apollo-like effort to complete.
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Resource Needs and Opportunities
OVERVIEW
Following workshop sessions that emphasized technical considerations for
infectious disease surveillance, detection, diagnosis, and reporting, the final session focused on relevant issues in public health policy, many of which had been
raised in prior discussions.
Global Coordination
The opening presentation, by Will Hueston, of the School of Public Health
and College of Veterinary Medicine of the University of Minnesota, describes
challenges in coordinating these vital public health activities. In his contribution
to this chapter, Hueston adopts a business perspective to analyze key technical
and social impediments to coordination. He explores how surveillance might
be repurposed as part of a system of disease detection, reporting, and outbreak
investigation; then he outlines political, technical, and educational measures that
would support such reform. By way of conclusion, Hueston employs business
strategic planning analysis to identify strengths, weaknesses, opportunities, and
threats inherent in current approaches to addressing infectious diseases.
Following Hueston’s presentation, a panel discussion explored diverse perspectives on resource needs and opportunities for infectious disease surveillance,
detection, diagnosis, and reporting. William Karesh, who spoke in a previous session about infectious disease surveillance in animals (see Summary and Assessment and Chapter 1), concurred with Hueston’s position that surveillance should
be designed to answer questions of long-term importance, rather than of present213
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day urgency. Noting that “society is healthier because more people understand
health,” Karesh advocated greater information sharing by public health officials
as a way to reduce, rather than increase, panic in response to disease threats, and
also to increase popular support for funding public health. He envisioned a twoway exchange of surveillance information, with the global public both supplying
essential data and receiving the benefits of its meaningful interpretation.
Panelist James LeDuc, Director for Global Health in the Institute of Human
Infections and Immunity at University of Texas Medical Branch, offered a concrete example of the potential for such “grassroots” surveillance: In Cambodia,
a network of “semitrained” villagers with cell phones and Mopeds swab sick
chickens and ducks to check for avian influenza and alert the health community to
suspected human cases. Multinational companies represent another newly tapped
source of global surveillance information; LeDuc noted that the Centers for Disease Control and Prevention (CDC) has established collaborations with a number of major companies operating in China, encouraging them to share signs of
unusual disease activity. He also identified two recent developments at the World
Health Organization (WHO) as significant opportunities for global coordination
in addressing infectious disease: the appointment to Director-General of Margaret
Chan, who has extensive experience in this area, and the ratification of the revised
International Health Regulations (IHRs; see Summary and Assessment).
On Location and in the Lab
In contrast to the global perspective taken by LeDuc, panelists Marci Layton,
Fernando Guerra, and Frances Downes offered local viewpoints on infectious
disease surveillance and detection. Layton, who had previously discussed local
public health surveillance as conducted by the New York City Department of
Health and Mental Hygiene (DOHMH; see Summary and Assessment and Chapter 1 overview), reemphasized that public health is an essentially local pursuit,
and that its most important asset is its infrastructure, particularly its workforce.
While acknowledging advantages in disease detection conferred by the increasing
volume of surveillance information available at the local level, she stressed the
importance of passing this inevitably noisy data through a “public health filter,”
embodied in “an epidemiologist looking at the data, a physician interviewing
other physicians to find out more deeply about a case, or field staff going out and
investigating the case.” This process converts raw surveillance data into “trustable” intelligence that avoids being premature or panic inducing, Layton said.
Guerra, Director of Health for San Antonio and Bexar County, Texas, works
with a population much smaller than that of New York City, but one that is similarly diverse and changeable. His experiences in building and using surveillance
systems, such as an immunization registry and tracking program, reveal the
profound influence of social circumstances on public health and their potential
contribution to “situational awareness” of disease threats, as discussed in prior
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sessions (see Summary and Assessment). The terms of reference for syndromic
surveillance need to be broadened, Guerra argued, and in particular should
encompass psychosocial and environmental circumstances.
Downes, Laboratory Director for the Michigan Department of Community
Health, discussed opportunities for improving infectious disease surveillance
from the perspective of the public health laboratory. Her contribution to this chapter, which summarizes her presentation, describes the creation and strengthening
of laboratory networks, the removal of barriers to disease reporting by laboratories, the role of information technologies, and the incorporation of syndromic
surveillance and disease diagnosis in the field. Given its unique position as “the
point at which laboratory science and public health surveillance intersect,” the
public health laboratory should lead the integration of nontraditional laboratory
surveillance sources into public health surveillance, Downes observed.
Funding
Nearly every panel member discussed some aspect of funding, beginning
with LeDuc’s blunt assessment that support for government and academic
research on public health is severely constrained, and will remain so for the
foreseeable future. As a result, he said, investments in disease surveillance and
detection must deliver the greatest value for money, and existing systems must
be subject to ongoing evaluation. LeDuc advocated a “transparent independent
investigation” of the federal BioSense (syndromic surveillance) and BioWatch
(aerosol detection) programs to determine whether they are truly answering
important questions. This would include considering the potential value of other
questions and/or systems and their applicability to standard clinical practice, as
well as for the detection of extraordinary disease threats. A similar argument was
taken up by panelist and speaker Ian Lipkin, director of Columbia University’s
Greene Infectious Disease Laboratory (see Summary and Assessment and Chapter 3), who noted that thoughtful investments in the surveillance and detection of
acute infectious disease may ultimately pay off in addressing chronic disease, in
which infections and immunity appear to play a role. Recognizing that funding
for surveillance tends to be tied to specific disease threats, LeDuc encouraged the
development of systems that can be adapted to a broad range of conditions (e.g.,
from avian influenza to any infectious respiratory disease).
Layton identified investment in infrastructure as key to improved disease surveillance by DOHMH. “That means people,” she explained. “It means field surveillance staff. It means public health nurses. It is physicians, laboratory support,
environmental health scientists, veterinarians, and . . . information technology
experts to allow us to process information and respond to it. Syndromic surveillance allows me to know what is going on in the city,” she continued, “but the
ability to do that [results from a] tremendous investment in staff infrastructure.”
Similarly, Downes noted that “the collection and analysis of surveillance data
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global infectious disease surveillance and detection
is only one part of the challenge of responding to emerging infectious diseases.
Epidemiologic and laboratory resources are needed to investigate early warning
signals and take actions to interrupt continued disease transmission.”
Workforce Issues
Several panelists identified a shrinking public health workforce as a challenge to infectious disease surveillance and detection, due in part to the relatively
low salaries of public health professionals. To encourage the kind of interest and
commitment necessary to produce the next generation of public health practitioners, Lipkin suggested engaging the media. “The number of kids who are
interested in forensics as a result of CSI has gone up dramatically,” he noted.
“Why not do something similar in public health?” Karesh argued for rewarding researchers who pursue the public good as their primary goal; for example,
those who release key information prior to publication, and those whose negative
results are difficult to publish, despite their epidemiological value.
COORDINATION OF DISEASE SURVEILLANCE,
DETECTION, DIAGNOSTICS, AND REPORTING
William D. Hueston, D.V.M., Ph.D.
University of Minnesota
Most of the presentations at this forum have focused on the technical aspects
of surveillance, diagnostics, and detection. My presentation will focus primarily
on the challenges of coordination as a leadership responsibility and management
imperative, with coordination defined from a business perspective: “Synchronization and integration of activities, responsibilities, and command and control
structures to ensure that the resources are used most efficiently in pursuit of the
specified objectives” (BusinessDictionary, 2007). Before I address these broad
issues, however, I would like to introduce five technical impediments to the coordination of infectious disease surveillance across animal and public health.
Technical Impediments to Coordination
First, there is the challenge of incorporating surveillance into the information
architecture of medical and veterinary medical business systems. Medical and
veterinary facilities decide to implement information systems when the benefits
outweigh the cost of installation and support. Most medical records systems are
designed to collect and compile records to enhance business efficiency, an obvious benefit that reduces the volume of paper records and the personnel needed to
College
of Veterinary Medicine and School of Public Health.
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compile the records. Generating bills and tracking cost center performance present different information management challenges than analyzing agent, host, and
environment data to support surveillance systems and epidemiological analyses.
Although the benefits of having a national or global surveillance system may
be readily apparent on a societal level, there may not be a visible return on the
investment required for an individual business to participate. Surveillance and
epidemiology generally are viewed as public goods, that is, the benefits accrue to
the whole society. Hence individual institutions and businesses often are reluctant
to participate in national surveillance programs without some inducement such
as government grants or preferred insurance rates, or some penalty, like a legal
requirement for involvement. Understanding the “value proposition” is critical
to forming productive collaborations.
A second challenge involves the lack of a common lexicon, so that certain
terms have different meanings in different disciplines. Various ontologies exist
to annotate biological terms such as the International Classification of Diseases
(ICD) and Standardized Nomenclature for Medicine (SNOMED) for human
medicine, and the Standardized Nomenclature for Veterinary Diagnoses and
Operations (SNVDO) and Standardized Nomenclature for Veterinary Medicine
(SNOVET) for veterinary medicine. The challenges of defining an integrated
human/veterinary system are myriad, such as rectifying hand versus paw versus
hoof naming conventions and adding population data—a cow is a member of a
herd and a chicken a member of a flock, where the population data represent one
element of the diagnosis. Although substantial progress has been made, no global
standard has emerged for an ideal medical vocabulary for use in both human and
veterinary medicine.
A third issue is the need for standardized communication protocols that
enable surveillance, detection, and response systems to share data and results in
real time. In this age of high-tech communications and increasing international
travel, a classic example of the lack of standardization exists with the differences in cell phone or videotaping protocols between the United States and
Europe. Agreeing on a standardized approach can be a monumental undertaking,
such as establishing an animal identification system in the United States. The
U.S. Department of Agriculture’s Animal and Plant Health Inspection Service
(APHIS) worked for years with a variety of stakeholders to reach a decision to
move ahead with a 15-character animal identification number, a 13-character
group/lot identification number, and a 7-character premises identification number
(USDA, 2006).
A fourth concern is how to secure the resources to support surveillance, particularly global surveillance. Despite widespread recognition of the importance
of global surveillance for the public good, health-care systems are nationally
based and, in a number of countries, funded largely by third-party payers and
user fees. The development of the Global Early Warning Systems (GLEWS)
in 2006 represents the first joint early warning and response system combining
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global infectious disease surveillance and detection
and coordinating the separate surveillance activities of the World Organization
for Animal Health (OIE), the Food and Agricultural Organization of the United
Nations (FAO), and the World Health Organization (WHO) (WHO, 2006). However, the GLEWS coverage is variable, reflecting huge differences in the capacity
of individual countries in terms of their laboratory resources, trained personnel,
internal surveillance systems, and reporting capabilities.
Confidentiality provides a final example of the technical challenges for
coordination. Even when secure communications can be guaranteed, protecting
individual privacy, proprietary business information, and sensitive national security data are topics of intense debate. Strategies like summarizing individual data
to produce group statistics may obscure the very trends that are of public health
interest. Differing objectives may bring those who provide the data and those who
compile and report the data into conflict. Examples include “shunning” of individuals who test positive for a disease despite a low risk of transmission during
casual social contact; regulatory action on voluntarily participating farms after
detection of an agent of concern; changes in consumer purchasing patterns of
finished products based on comparison of contamination rates on raw ingredients
before processing; and imposition of trade restrictions following the voluntary
reporting of an animal disease agent detection considered to pose only a limited
risk to production agriculture, such as detection of a low-pathology strain of avian
influenza in wild birds.
Paradigm Impediments to Coordination
Our collective approach to surveillance is framed by the prevailing paradigms of our society. Currently, coordination of disease surveillance, detection,
diagnostics, and reporting is stymied by an overriding philosophical framework
comprising our public health focus, our definition of health, our perspective on
risk, our fascination with disease agents, our propensity to glorify emergency
response, and our preoccupation with technology. A series of examples will help
to illustrate these challenges:
• Despite the fact that public health surveillance is all about populations,
we tend to think in terms of the individual. Individual stories galvanize public
action as they personalize stories of illness, pain, and death. Betty Ford’s breast
cancer and Rock Hudson’s AIDS diagnosis are often cited as turning points for
U.S. public health policy for these diseases. Furthermore, our focus tends to be
parochial, evaluating public health priorities from our personal and local perspectives rather than considering the world at large.
• We tend to define health as absence of disease; success as complete cure
or eradication of an infectious disease scourge; the primary public health function
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as rapid response to crises; and our compelling public health vision as zero risk.
In stark contrast, physicians explain that we can achieve a high quality of life
despite a number of illnesses and afflictions; economists argue that the focus on
eradication of disease is not optimal use of our health-care dollars; decreasing
prevention budgets contribute to the occurrence of crises needing rapid response;
and scientists point out that zero risk is unachievable.
• All too often we focus our infectious disease resources on the agent,
ignoring the web of causation, including genetics, host immunity, and social
and environmental factors. By focusing disproportionately on the agent, we fail
to adequately track host and environmental risk factors that contribute to the
emergence and reemergence of infectious diseases and we are lulled into the
erroneous conclusion that successful risk management depends on identification
of the specific agent. However, agent identification was not a prerequisite for the
public health heroes who made important contributions prior to the formulation of
the germ theory of disease, such as Ignaz Semmelweis (whose advocacy of hand
washing drastically reduced mortality due to puerperal fever) and John Snow (a
father of epidemiology, who gathered evidence that linked the spread of cholera
with water contaminated by waste from infected people).
• We are strongly influenced by what I call the “John Wayne mentality,”
which dictates that when something goes wrong, someone is to blame and that
party must be hunted down and punished and thereby, the problem is solved
(often this mindset results in a case of shooting the messenger). We wholeheartedly embrace the war metaphor, wherein public health wages battles against
infectious diseases. Such conflicts have winners and losers, and it is our job to
win; indeed, victory over infectious disease was prematurely declared by U.S.
Surgeon General William H. Stewart in 1967 (IOM, 2006, particularly pp. 1-2).
• We are fascinated by technology. Even though few of us use even a
fraction of the power of our computers or cell phones, we rush to upgrade to
the latest and greatest improvement of speed, graphics, communications, and
games software. While partially inured to the exaggerated claims of biotechnology, genomes, and pharmaceuticals, we still cling to the hope that technology
will provide the silver bullet. When we complete careful reviews of our public
health program failures, technology is rarely the culprit. The lack of people
skills—including leadership and teamwork—is far more commonly cited as a
major contributor to public health program underperformance than a shortage
of technology. Disciplinary silos and professional egos are more damaging than
absence of the latest “techno-solution” or “miracle-mycin.”
Coordination as a Leadership and Management Imperative
The overall high health status of people and animals in the United States
contributes to the prevailing attitude of “if it ain’t broke, don’t fix it.” Our comparative good health also leads us to focus on the “disease du jour” or the crisis
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global infectious disease surveillance and detection
of the moment rather than prioritizing our investments by the potential impact
they can make on measures of population health such as infant mortality, risk
factor avoidance, or adolescent pregnancy. In the absence of a headline-grabbing
outbreak or the untimely demise of a celebrity, we are loath to fund surveillance
systems that could anticipate such threats and trigger proactive prevention campaigns. Success in a disease control program often is met with reduced funding
or elimination of the surveillance and disease detection programs on which the
success was based. As an example, the successful U.S. campaigns against the
zoonoses bovine brucellosis (undulant fever in humans) and bovine tuberculosis
(one form of tuberculosis in humans) depended on a traceability system that
allowed affected cattle detected at slaughter to be traced back to their herd of
origin. Given the eradication successes, however, funding was dropped for the
identification systems and the United States has slipped backward in its ability to
trace cattle back to the farm of origin. While the most highly trained fire-fighting
unit in most communities—that of its local airport—is rarely used, our tendency
is to decommission surveillance, detection, diagnostic, and reporting infrastructures when the disease of concern becomes rare.
An Alternative World View
Coordinating surveillance requires that we “begin with the end in mind,” as
Stephen Covey memorialized (Covey, 1989). What is the surveillance intended
to accomplish? Why is coordination important? How will the surveillance results
be used? What benefits will the surveillance yield for those who are expected
to participate? Presumably the overarching goal of coordinated surveillance is
improvement of public health, that is, the health of the community. Public health
involves identifying problems, setting priorities, formulating policies to address
these priorities, promoting health and preventing illness, and providing access
to health care.
Achieving these lofty public health goals requires a very different paradigm
characterized by a global perspective, a focus on health, an ecosystem approach
(agent, host, environment), a risk management goal, prioritization based on
importance rather than urgency, and a commitment to working with people to
manage the dilemmas rather than seeking a technology quick fix (Table 4-1).
We increasingly recognize that we live in a complex world of microbial
ecology, a world in which microbes are ubiquitous and adaptive and in which
disease and emergent disease is the norm rather than the exception. If we think
of surveillance only in terms of agent detection, we will not be able to effectively
manage these new risks. For example, initial responses to recent foodborne disease outbreaks in leafy greens demonstrated a lack of understanding of complex
food production and distribution systems. These complex systems must incorporate multiple critical control points including the application of best practices and
targeted monitoring and feedback loops.
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TABLE 4-1 Current Public Health Paradigm and Alternative World View
Current Paradigm
Alternative World View
Health is absence of disease
Health is well-being (in mind, body, spirit)
Infectious disease is all about the agent
Infectious disease emerges at the convergence
of agent, host, environment
Zero risk is achievable
Zero risk is unachievable; risk management is
the goal
Success is eradication/cure
Success is homeostasis with microbes that are
ubiquitous, constantly evolving and adapting
Public health function is to react
Public health function is health promotion
Reaction requires agent detection
Risk management can be successful whether or
not microbe is identified
Urgency dictates priority
Surveillance informs policy and guides action
on basis of importance
Answers lie solely in technology
Answers involve people, politics, partners
SOURCE: Hueston (2006).
Real-time surveillance of food products and their raw materials must be
combined with quality control and food safety systems in processing and distribution, sensitive public health disease detection, prompt reporting, and rapid
outbreak investigation. The entire food system must retain the flexibility to adjust
its risk management strategies to changing risk factors (hosts, agents, and the
environment) without waiting for outbreaks to occur. Without a dynamic and
adaptive food safety system, significant resources will be squandered on useless
activities such as large recalls announced after most of the product has already
been consumed.
The Politics of Coordination
Coordination is all about politics, which I define as the interpersonal dynamics that occur whenever two or more people are gathered together. Politics of
societies are influenced by culture, and the organizational culture of the various
public health agencies and the regulated industries is as germane to the practice of
public health as is ethnicity, gender, religion, and other factors. To coordinate—to
harmonize in common action and effort—requires effective political processes
over the long term. “People skills” are needed to build coordination and collaboration, yet the social sciences are rarely emphasized—or even mentioned—in the
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global infectious disease surveillance and detection
programs that train doctors, public health professionals, veterinarians, and plant
pathologists. Interpersonal and teamwork skills are described as “non-technical”
or “soft skills” and omitted from the curriculum. As has been demonstrated time
and time again, university faculties assume that students “ought to know all that
stuff before they get into graduate school or professional school.”
Toward Optimal Surveillance
The optimal surveillance system is integrated and dynamic, with ongoing
data collection. Real-time analysis would generate information relevant to risk
management that would in turn drive policy and action. This ideal surveillance
system incorporates feedback processes, permitting continuous, evolutionary
change. It would integrate information on infectious disease in humans, domestic
animals, wildlife, and plants collected and maintained through cross-disciplinary
collaboration such as plant pathologists working in public health or psychiatrists
working in veterinary medicine.
What is the way forward toward such a “system of systems?” Beginning with
the end in mind, we need to prioritize public health goals. We need to complement agent surveillance with host and environmental monitoring. We need to
recognize that societal stability and economic security are critical for maintaining
a functional public health infrastructure, and find ways to make “doing the right
thing” both beneficial to society and profitable for the private sector. We need
multiple functional models that will work in the developing world as well as
in industrialized countries. The information systems we need to develop would
support global public health. Finally, because we can anticipate many future challenges, we must incorporate capacity for adaptation into the design of integrated
surveillance systems.
Changing the Prevailing Paradigms
There is no magic formula for changing paradigms. However, change can
occur incrementally, by rewarding progress no matter how slow, and then identifying, documenting, and celebrating successes, large and small. Fostering paradigm
change is difficult, requiring a number of simultaneous activities, including:
• We must nurture a new generation of public health professionals who
adopt a holistic, global perspective of health, and who look for creative ways
to manage risks. We need to imbue these emerging public health professionals
with a commitment to transdisciplinary approaches. We also need to encourage
them to embrace change and be adaptable in a world that will never be risk
free.
• Combining experiential learning opportunities with more didactic educational approaches will enable our new public health professionals to be more
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effective, to be more adaptive, to understand complex challenges and opportunities, and to manage the complex dilemmas of the future.
• We must establish a robust, global public health infrastructure that incorporates interoperable high- and low-tech solutions, such as the cell phone surveillance system described in this report (see Johnson and Blazes in Chapter 2). Like
Voxiva, we need to bring cultural anthropologists into health delivery teams to
examine motivators for promoting public health in different cultures.
• We must examine the ethics of surveillance, and in particular the question as to whether effectively contained disease outbreaks need be reported to the
public. I found the HealthMap presentation (see Brownstein in Chapter 2) both
exciting and frightening, because it labels countries as to whether or not they
have a given infectious disease within their borders. Although that knowledge
may help us to detect global disease patterns and target intervention resources,
it also has the potential to set back international development, given that reports
of infectious disease can lead to trade embargoes and reductions in tourism and
investment. This, in turn, will decrease infectious disease reporting. Futhermore,
labeling an entire country in terms of disease presence or absence acts against
the recognizing potential to safely establish free zones or even agricultural enterprises within a country where a specific disease is widespread.
• Finally, we must build public–private partnerships for global health. While
public funding will always be constrained by other societal demands, we can
identify potential benefits of improving public health in ways that make sense to
corporations. The private sector can move much faster and contribute a wider array
of resources toward those shared public health goals than the public sector can.
Strengths, Weaknesses, Opportunities, and Threats
SWOT analysis emerged in the 1960s and 1970s as a strategic planning
tool used to evaluate the Strengths, Weaknesses, Opportunities, and Threats of
a project or initiative. Looking at current disease surveillance, detection, diagnostics, and reporting systems, we can draw several conclusions from a brief
SWOT analysis.
The public health dilemmas of infectious diseases are global, not local. While
our local strengths include the vast array of technology and data at our disposal, our
principal weakness is the disparate global environment in which we must operate,
where countries vary greatly in terms of infrastructure capacity, human and fiscal
resources, and commitment to public health. We are also plagued by the disconnect between surveillance and action, which is exacerbated by the misconception
of surveillance as a goal, rather than as a means to an end.
Progress toward integrated, global surveillance is threatened by the potential
for unintended consequences. The potential for surveillance to deepen the firstworld/third-world divide is a huge threat to global coordination and collaboration. Thus we need to discuss the possible consequences—both intended and
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unintended—with our stakeholders and the beneficiaries we serve, both domestically and globally.
A key opportunity lies in the possibility of developing an overarching, integrated, global surveillance plan that will take us out of our disciplinary silos—a
plan that sets priorities based on global considerations of public health impacts
and identifies the resources necessary for coordination. These priorities necessarily must balance the potential impact on and the degree of buy-in from the
community that they are meant to serve. Experience has taught me that ideal
solutions lacking community support will fail, while popular, partial solutions
will succeed. We must be willing to address today’s complex public health dilemmas one small step at a time. After all, as I am frequently reminded by a mentor,
“slow progress is progress.”
Finally, we have a tremendous opportunity to foster a new generation of
global public health leaders who will catalyze coordination through very different paradigms than those held today. Progress toward coordinated surveillance
will be accelerated by active transdisciplinary leadership development programs
in global public health.
Defining Success
How can we measure our progress toward global coordination of infectious disease surveillance, detection, diagnostics, and reporting? A successful
system will allow us to more effectively anticipate new threats and will adapt
fluidly to manage risk under novel conditions. It will encourage the formation
of public–private partnerships to support surveillance. New leaders will step
forward to promote international collaboration toward shared goals. Finally, we
will know we have succeeded when we can document incremental improvement
in global public health.
IMPROVING INFECTIOUS DISEASE SURVEILLANCE AND
DETECTION: A PUBLIC HEALTH LABORATORY PERSPECTIVE
Frances Pouch Downes, Dr.P.H.
Michigan Department of Community Health
The practice of infectious disease surveillance has co-evolved with the public health laboratory to address important health concerns with ever-advancing
technologies. This ongoing partnership is essential to the continued improvement
of surveillance systems. Public health laboratories in the United States are major
contributors of infectious disease reports. In Michigan, for example, 60 percent
of all laboratory results in the Michigan Disease Surveillance System are received
Laboratory
Director.
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from the state’s public health laboratory. Nationally, public health laboratories
perform more than 40 million tests annually and are responsible for generating
35 to 65 percent of all positive laboratory findings for reportable diseases (APHL,
2002).
This essay examines key opportunities for improving infectious disease
surveillance from the perspective of the public health laboratory. These include
the creation and strengthening of laboratory networks; the acknowledgment and
removal of barriers to disease reporting by laboratories; the adoption and adaptation of information technologies by and for laboratory use; and the extension of
the laboratory–surveillance partnership to refine and validate syndromic surveillance and rapid field diagnosis of reportable diseases.
Establishing Laboratory Networks
Surveillance benefits from the collection of comprehensive data from diverse
sources, and public health laboratories can play an instrumental role in facilitating
and garnering support for this process. The public health laboratory community
increasingly has embraced the concept of laboratory networks that enable a wide
variety of laboratories to contribute their testing results to surveillance and disease control databases. Examples of current and potential laboratory networks are
described in the following paragraphs.
The National Laboratory System
In 2001, the Centers for Disease Control and Prevention (CDC) launched
pilot programs in four states (Michigan, Minnesota, Nebraska, and Washington)
to implement a National Laboratory System (NLS) of statewide laboratory networks (CDC, 2004). Since the initiation of the NLS, many public health laboratories have undertaken network development programs within their states that
improve public health response and surveillance through partnerships with traditional and nontraditional partners, including clinical and hospital laboratories,
health advocacy organizations, agriculture and veterinary laboratories, and commercial laboratories.
Integrated Surveillance Networks
The public health laboratory is the juncture at which medical laboratory
science and public health surveillance intersect. Due to this unique position, the
public health laboratory must provide the leadership to forge relationships that
eventually will lead to the integration of nontraditional laboratory surveillance
data sources into public health surveillance.
Recent infectious disease emergence and foodborne disease outbreaks demonstrate the need for public health surveillance to integrate nontraditional sources
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of data. Peanut butter, fresh spinach, and tomatoes recently have been identified
as vehicles of enteric bacterial infections. In these examples, improved access to,
and monitoring of, agriculture and food processor laboratory results by public
health practitioners may have enabled earlier identification of disease activity
and outbreaks. Because most emerging infectious diseases are zoonotic, animal
diagnostic testing is clearly another rich source of data to collect for improved
surveillance of emerging, reemerging, or novel infections.
Technical and Professional Networks
Although network-building activities rarely involve increased screening or
testing for public health laboratories themselves, public health laboratories undertaking these efforts frequently provide technical training (e.g., in rapid screening
for bioterrorism agents), consultation (e.g., on antimicrobial resistance testing),
and feedback (e.g., the use of laboratory reports for surveillance and outbreak
response). Network development also encourages the development of best practice guidelines for tests of public health importance (e.g., rapid HIV testing,
estimated glomerular filtration rate, cholesterol screening). Even simple efforts
such as the development of educational materials or tools and presentations to
remind laboratorians about the importance of their role in disease reporting, or
the participation of public health laboratories in state and regional clinical laboratory professional organizations, can ultimately improve the completeness and
timeliness of disease reporting. Equally important, technical and professional
networks develop relationships among organizations that can work together to
refine surveillance systems through the use of mechanisms such as electronic
medical record exchanges and electronic laboratory reporting.
Addressing Barriers to Reporting
To improve the timeliness and completeness of reporting by laboratories,
and thereby the quality of surveillance, the following critical barriers must be
addressed.
Reporting Costs
The cost of preparing and shipping isolates and specimens to public health
laboratories for reference and molecular epidemiology testing are not reimbursed
by third-party insurance providers or public health agencies. Recent changes to
the U.S. Postal Service (USPS) regulations prohibiting the use of the USPS for
shipping infectious agents have only exacerbated this problem. For example,
some states require that clinical laboratories submit their public health laboratory
isolates of Mycobacterium tuberculosis and other microbes. These isolates must
now be shipped to public health laboratories by commercial courier services that
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attach a $50 surcharge to each infectious agent shipment. The burden of this cost
is borne by the clinical or other originating laboratory and is not reimbursable by
public or third-party insurers.
Shrinking Workforce
The medical laboratory is beginning to see the first signs of a looming shortage of trained professionals. Between 1980 and 2003, the number of medical
technology programs declined from nearly 800 to 240, and the annual number of
graduates of accredited programs declined from 6,184 to 1,668 (Personal communication, S. Anderson at the 2004 Clinical Laboratory Education Conference).
The laboratory professional workforce will be exacerbated as the majority of the
workforce reach retirement age in the next two decades. Less than 10 percent
of the laboratory professional workforce is eligible for retirement now, but in
the next 10 years, approximately 40 percent of the current workforce will be
eligible, and in 15 years 62 percent will be eligible (Personal communication, S.
Anderson at the 2004 Clinical Laboratory Education Conference). Vacancies due
to an inadequate pool of qualified candidates translate into less time available to
prepare and ship isolates and specimens to public health laboratories, prepare and
submit reports of reportable diseases to public health agencies, and participate in
training on emerging health issues and disease reporting.
Labor-Intensive Methods
Antigen detection and other simple point-of-care tests, among other emerging testing technologies, may be more rapid and require less equipment and
labor. However, public health reference and molecular testing used to detect and
investigate disease outbreaks often requires a microbial isolate. For example,
isolates of suspect Mycobacterium tuberculosis must be available for public
health testing using currently practiced methods for the public health testing of
reference level identification (Metchock et al., 1999), antimicrobial susceptibility
testing (NCCLS, 2003; Plikaytis, 1992), and genotyping (Cowan et al., 2002).
Public health laboratories may need to perform more preliminary testing to
obtain isolates from rapid test specimens and work with front-line practitioners
to assure quality of point-of-care tests and collection of additional specimens for
confirmatory and molecular epidemiology testing. Eventually, alternative public
health laboratory confirmatory and typing methods that do not require microbial
isolates will need to be developed.
Standardized Reporting
Laboratory testing to identify potential cases of reportable disease is increasingly performed for multiple states by commercial clinical laboratories. Com-
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global infectious disease surveillance and detection
municable disease reporting requirements, however, vary from state to state.
Reporting and isolate submission compliance by multistate laboratories will
only improve when states standardize reporting and isolate submission lists and
formats.
Adoption and Adaptation of Information Technology
Information technology that can improve current surveillance systems is
available, but it has not been universally adopted. CDC’s Public Health Information Network (PHIN) standards make adopting this technology nationally
feasible. As with the establishment of laboratory networks, trust and resources
are needed to achieve data exchange between the clinical laboratory and public
health surveillance systems in the following critical areas.
Electronic Laboratory Information System Reporting
As noted in the contribution by Joseph Lombardo (see Chapter 1), many
hospitals use the Health Level Seven (HL-7) format, which can create a message from the originating laboratory information system and transfer it to a
surveillance information system that captures and stores disease surveillance
data for case investigation and data analysis. Widespread adoption of electronic
laboratory reporting would eliminate the current slow, labor-intensive practice
of transcription of results from a laboratory information system to a paper form
and submission by mail or reentering results to a web-based interface with the
surveillance system. Broader adoption of this faster and more complete method
of laboratory reporting may require additional linkage to hospital information
systems that contain patient-specific information not available in the laboratory
information system. Also, resource commitment is required from both the clinical
laboratory and the surveillance system to initiate and maintain electronic laboratory reporting.
Electronic Health Records
Regional initiatives are underway to develop electronic health record
exchanges throughout the United States. While economics and quality of care
are often the motivating forces in the development of the health information
exchange networks, these networks can and should be designed and used for public health surveillance (and registry) reporting. Public health entities are able to
The
PHIN is CDC’s vision for advancing fully capable and interoperable information systems in
the many organizations that participate in public health. PHIN is a national initiative to implement a
multiorganizational business and technical architecture for public health information systems (CDC,
2007).
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receive patient-specific health information while still complying with the Health
Insurance Portability and Accountability Act (HIPAA).
The Role of the Laboratory in Syndromic Surveillance and Field Diagnosis
Syndromic Surveillance
Novel surveillance systems are being piloted and used in a variety of settings for a variety of uses. Laboratory-based reporting is highly specific but not
sensitive; conversely, syndromic surveillance is very sensitive, but not specific.
Syndromic surveillance systems are designed to detect large-scale events clustered in time and space. They will not detect low-frequency events like the first
cases of disease outbreak.
Syndromic surveillance systems can complement, but cannot replace, traditional case and laboratory-based reporting systems. Syndromic surveillance
system data should be validated periodically with traditional case confirmation
and laboratory testing methods. It is also important to evaluate programmatic
investments in syndromic surveillance early warning systems, such as BioSense
and BioWatch, to determine if they have been used as intended and if the investment is warranted (GAO, 2005).
Field Diagnosis
Global public health surveillance and clinical patient care may benefit from
easily performed microbe-specific rugged tests. The “gold standard” tests are
essentially unavailable in many parts of the world and are often so time consuming that they stymie disease control efforts. Exciting advances in the development
of field-ready diagnostics are resulting from public–private partnerships. However, investment in such technology should not supersede investments or precede
efforts in total quality systems.
A comprehensive laboratory quality system approach is relevant for any test,
whether it is complex or simple to perform, and in any testing setting, whether
it is the traditional laboratory, the clinic, or the field (CLSI, 2004). Inaccurate
results generated from unmonitored testing can lead to misdirected patient care,
inaccurate disease reporting to surveillance systems, and wasted resources. When
rugged, simple field tests are used, traditional microbiology also should be accessible to provide reference-level testing to detect emerging infectious diseases
(i.e., microbes that will not be recognized by disease-specific tests) and to validate field tests on an ongoing basis.
Enacted in 1996, HIPAA required the Department of Health and Human Services to establish
national standards for electronic health-care transactions and national identifiers for providers, health
plans, and employers. It also addressed the security and privacy of health data (HHS, 2005).
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global infectious disease surveillance and detection
Conclusion
As investments are made in surveillance systems, it is also critical to commit
adequate resources to analyzing and responding to the increased volume of surveillance data. For example, PulseNet—a much-heralded early warning system
for foodborne diseases—does not live up to its full potential due to inadequate
resources for laboratory studies and epidemiology. Moreover, the collection and
analysis of surveillance data is only one part of the challenge of responding to
emerging infectious diseases. Epidemiologic and laboratory resources are needed
to investigate early warning signals and to take effective actions to break the
cycle of disease transmission.
REFERENCES
APHL (Association of Public Health Laboratories). 2002. Advancing the national electronic surveillance system: An essential role for public health laboratories, http://www.aphl.org/Documents/
Global_docs/advancing_NEDSS.pdf (accessed May 24, 2007).
BusinessDictionary. 2007. Definition of “coordination,” http://www.businessdictionary.com/
definition/coordination.html (accessed May 5, 2007).
CDC (Centers for Disease Control and Prevention). 2004. National Laboratory System (NLS), http://
www.phppo.cdc.gov/mlp/nls.aspx (accessed May 10, 2007).
CDC. 2006. PulseNet, http://www.cdc.gov/pulsenet/ (accessed May 10, 2007).
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CLSI (Clinical and Laboratory Standards Institute). 2004. GP26—Application of a quality management system model for laboratory services; Approved guidelines—Third edition. Wayne, PA:
Clinical and Laboratory Standards Institute.
Covey, S. 1989. The seven habits of highly effective people. New York: Simon and Schuster.
Cowan, L. S., L. Mosher, L. Diem, J. P. Massey, and J. T. Crawford. 2002. Variable-number tandem
repeat typing of Mycobacterium tuberculosis with low copy number of IS6110 by using mycobacterial interspersed repetitive units. Journal of Clinical Microbiology 40(2):1592-1602.
GAO (General Accounting Office). 2005. Information technology: Federal agencies challenges in
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Hueston, W. 2006. Coordination of disease surveillance, detection, diagnostics, and reporting. Presentation to the Institute of Medicine Forum on Microbial Threats, Washington, DC, December
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federal agencies (CDC, U.S. Department of Agriculture/Food Safety and Inspection Service, Food and
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to distinguish strains at the DNA level. DNA “fingerprints,” or patterns, are submitted electronically
to a dynamic database at CDC, allowing for rapid comparison of the patterns (CDC, 2006).
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IOM (Institute of Medicine). 2006. Ending the war metaphor: The changing agenda for unraveling
the host–microbe relationship—Workshop Summary. Washington, DC: The National Academies
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Metchock, B. G., F. S. Nolte, and R. J. Wallace, Jr. 1999. Mycobacterium. In Manual of clinical
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H. Yolken. Washington, DC: American Society for Microbiology.
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(accessed May 5, 2007).
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Appendix A
Agenda
Global Infectious Disease Surveillance and Detection:
Assessing the Challenges—Finding Solutions
The National Academies
500 Fifth Street, NW – Room 100
Washington, DC
December 12–13, 2006
Tuesday, December 12, 2006
8:00 a.m.
Continental Breakfast
8:30 a.m.
Welcome and Opening Remarks
P. Fred Sparling, M.D., Vice Chair
Forum on Microbial Threats
8:45–9:15 a.m.
Keynote Address: “Syndromic Surveillance: Moving
from Theory to Practice”
Patrick W. Kelley, M.D., Dr.P.H.
The National Academies
9:15–9:45 a.m.
Discussion
233
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global infectious disease surveillance and detection
Session I:
Surveillance for Emerging, Reemerging, and Novel Infectious Diseases
Moderator: Col. Ralph Erickson, M.D., Department of Defense Global Emerging
Infectious Surveillance and Response System
9:45–10:15 a.m.
Public Health Infectious Disease Surveillance
Michael Stoto, Ph.D.
Georgetown University
10:15–10:45 a.m.
Infectious Disease Surveillance: The “Local”
Perspective
Marci Layton, M.D.
New York City Department of Health and Mental
Hygiene
10:45–11:00 a.m.
Break
11:00–11:30 a.m.
Animal Disease Surveillance
William Karesh, D.V.M.
Wildlife Conservation Society
11:30 a.m.–12:00 p.m. Plant Disease Surveillance and Detection
Jacque Fletcher, Ph.D.
Oklahoma State University
Jim Stack, Ph.D.
Kansas State University
12:00–12:30 p.m.
Open Discussion of Session I
12:30–1:15 p.m.
Lunch
Session II:
Infectious Disease Detection and Diagnostics
Moderator: David Relman, M.D., Stanford University
1:15–1:45 p.m.
Mark D. Perkins, M.D.
Foundation for Innovative New Diagnostics (FIND)
1:45–2:15 p.m.
Stephen Johnston, Ph.D.
Arizona State University
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APPENDIX A
2:15–2:45 p.m.
Animal Disease Detection: Diagnostic Laboratory
Perspective
Alex Ardans, D.V.M.
California Animal Health & Food Safety Laboratory
System
2:45–3:00 p.m.
Break
3:00–3:30 p.m.
Rapid Infectious Disease Diagnostic Assays
Mark Wolcott, Ph.D.
U.S. Army Medical Research Institute of Infectious
Diseases
3:30–4:00 p.m.
Discussion of the GreeneChip: A Panmicrobial
Oligonucleotide Array for the Diagnosis of
Infectious Diseases
W. Ian Lipkin, M.D.
Columbia University
4:00–5:00 p.m.
Open Discussion of Session II
5:00–5:45 p.m.
Open Discussion of Day 1
6:00–7:00 p.m.
Open Reception
Wednesday, December 13, 2006
8:00 a.m.
Continental Breakfast
8:30 a.m.
Opening Remarks/Summary of Day 1
Peggy Hamburg, Vice Chair
Forum on Microbial Threats
Session III:
Current and Future Methods for Infectious Disease
Surveillance, Reporting, and Communication
Moderator: Stephen S. Morse, Ph.D., Columbia University
8:40–9:10 a.m.
Discussion of ProMED-mail
Stephen S. Morse, Ph.D.
Columbia University
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global infectious disease surveillance and detection
9:10–9:40 a.m.
Discussion of the Global Public Health Intelligence
Network
Abla Mawudeku, M.P.H.
Global Public Health Intelligence Network
9:40–10:10 a.m.
Implications of “Real Time” and “Batch Reporting” for
Surveillance
Joseph Lombardo, Ph.D.
The Johns Hopkins University Applied Physics
Laboratory
10:10–10:30 a.m.
Break
10:30–11:00 a.m.
Using Cell Phone Technology for Infectious Disease
Surveillance
�������������
Pamela Johnson, Ph.D.
Voxiva
David Blazes, M.D., M.P.H.
Naval Medical Research Unit, Peru
11:00–11:30 a.m.
HealthMap: A Global Disease Alert Mapping System
John Brownstein, Ph.D.
Harvard Medical School
11:30 a.m.–12:15 p.m. Open Discussion of Session III
12:15–1:00 p.m.
Lunch
Session IV:
Infectious Disease Detection, Surveillance, and Reporting—
Resource Needs and Opportunities
Moderator: Fred Sparling, M.D., University of North Carolina
1:00–1:30 p.m.
Coordination of Disease Surveillance, Detection,
Diagnostics, and Reporting
Will Hueston, D.V.M., Ph.D.
University of Minnesota
1:30–3:30 p.m.
Discussion Panel
• Marci Layton, M.D.
New York City Department of Health and Mental
Hygiene
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APPENDIX A
• Fernando Guerra, M.D., M.P.H.
San Antonio Department of Health
• Frances P. Downes, Dr.P.H.
Michigan Public Health Laboratory
• W. Ian Lipkin, M.D.
Columbia University
• James LeDuc, Ph.D.
University of Texas Medical Branch
3:30–4:15 p.m.
Open Discussion of Session IV
4:15–4:30 p.m.
Closing Remarks/Adjourn
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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Appendix B
Acronyms
ALS
APHIS
ARIMA
ARS
amyotrophic lateral sclerosis
Animal and Plant Health Inspection Service
autoregressive moving average
Agricultural Research Service
BDV
BLAST
BSN
Borna disease virus
Basic Local Alignment Search Tool
Basic Surveillance Network
CBP
CDC
cDNA
CGIAR
cPCR
CRP
CSREES
Customs and Border Protection
Centers for Disease Control and Prevention
complementary DNA
Consultative Group on International Agriculture Research
consensus polymerase chain reaction
Critical Reagents Program
Cooperative State Research, Education, and Extension
Service
DD
DHS
DoD
DOHMH
DoI
DoS
DOTS
differential display
Department of Homeland Security
Department of Defense
Department of Health and Mental Hygiene (New York City)
Department of the Interior
Department of State
directly observed therapy shortcourse
238
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APPENDIX B
DSDD
DSN
domain-specific differential display
disease surveillance network
ECDC
ECL
ED
EDR
EFSA
EISS
EMEA
END
ER
ESSENCE
EU
EWGLI
EWRS
European Center for Disease Control
electrochemiluminescence
emergency department
Emerging Disease Reports
European Food and Safety Authority
European Influenza Surveillance Scheme
European Agency for the Evaluation of Medicinal Products
exotic Newcastle disease
emergency room
Electronic Surveillance System for the Early Notification of
Community-Based Epidemics
European Union
European Working Group for Legionella Infections
Early Warning Response System
FAO
FAS
FDA
FIND
FMD
FTP
Food and Agriculture Organization of the United Nations
Federation of American Scientists
Food and Drug Administration
Foundation for Innovative New Diagnostics
foot-and-mouth disease
File Transfer Protocol
GAINS
GAO
GEIS
GIS
GLEWS
GOARN
GPHIN
GreenVrdB
Global Avian Influenza Network for Surveillance
Government Accountability Office
Global Emerging Infections Surveillance and Response
System
Geographic Information System
Global Early Warning and Response System
Global Outbreak Alert and Response Network
Global Public Health Intelligence Network
Greene Viral Database
HCV
HHA
HHS
HIPAA
HIV
HL-7
HMM
HSPD
hepatitis C virus
hand-held assay
Department of Health and Human Services
Health Insurance Portability and Accountability Act
human immunodeficiency virus
Health Level Seven
Hidden Markov Models
Homeland Security Presidential Directive
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global infectious disease surveillance and detection
ICD
ICTV
ICTVdB
ICU
IEEE
IHR
ILI
INSTEDD
IOM
IPM
ISID
IT
ITU
International Classification of Diseases
International Committee on Taxonomy of Viruses
International Committee on Taxonomy of Viruses Database
intensive care unit
Institute of Electrical and Electronics Engineers
International Health Regulation
influenza-like illness
International System for Total Early Disease Detection
Institute of Medicine
Integrated Pest Management
International Society for Infectious Diseases
information technology
International Telecommunications Union
JBAIDS
Joint Biological Agent Identification and Diagnostic System
LEADERS
LOD
Lightweight Epidemiological Advanced Detection Emergency
Response System
limit of detection
MedISys
MHC
MoH
mRNA
MS
Medical Intelligence System
major histocompatibility complex
Ministry of Health
messenger RNA
messaging system
NATO
NCBI
NGO
NIAID
NIH
NINDS
NLS
NMRCD
NPDN
NPDRS
NRC
NRDM
North Atlantic Treaty Organization
National Center for Biotechnology Information
nongovernmental organization
National Institute of Allergy and Infectious Diseases
National Institutes of Health
National Institute of Neurological Disorders and Stroke
National Laboratory System
Naval Medical Research Center Detachment
National Plant Diagnostic Network
National Plant Disease Recovery System
National Research Council
National Retail Data Monitor
OIE
OIG
World Organization for Animal Health
Office of the Inspector General
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APPENDIX B
PCR
PDA
Pfam
PHIN
PMM
ProMED
polymerase chain reaction
personal digital assistant
Protein families database of alignments
Public Health Information Network
ProMED-mail
Program for Monitoring Emerging Diseases
RDA
RDP
RDT
RFI
RODS
RSS
RSVP
RT-PCR
representational difference analysis
Ribosomal Database Project
rapid diagnostic test
request for information
Real-Time Outbreak and Disease Surveillance System
Really Simple Syndication
Rapid Syndrome Validation Project
reverse transcriptase–PCR
SARS
SD
SLEV
SMS
SNOMED
SNOVET
SNVDO
SPC
SWOT
SYRIS
severe acute respiratory syndrome
standard deviation
St. Louis encephalitis virus
short message service
Standardized Nomenclature for Medicine
Standardized Nomenclature for Veterinary Medicine
Standardized Nomenclature for Veterinary Diagnoses and
Operations
statistical process control
Strengths, Weaknesses, Opportunities, and Threats
Syndromic Reporting Information System
TaxID
TB
TED
TPA
TRF
Taxonomy identification
tuberculosis
Technology, Entertainment, and Design
tripropylamine
time-resolved fluorescence
USAID
USAMRIID
USDA
USGS
USPS
U.S. Agency for International Development
U.S. Army Medical Research Institute of Infectious Diseases
U.S. Department of Agriculture
U.S. Geological Survey
U.S. Postal Service
VPN
virtual private network
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global infectious disease surveillance and detection
WCS
Wildlife Conservation Society
WHO
World Health Organization
WHO-OVL
Outbreak Verification List
Wildlife GAINS Wildlife Global Animal Information Network for Surveillance
WNV
West Nile virus
Copyright © National Academy of Sciences. All rights reserved.
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Appendix C
Forum Member Biographies
Stanley M. Lemon, M.D. (Chair), is the John Sealy Distinguished University
Chair and director of the Institute for Human Infections and Immunity at the
University of Texas Medical Branch (UTMB) at Galveston. He received his
undergraduate A.B. degree in biochemical sciences from Princeton University
summa cum laude and his M.D. with honors from the University of Rochester.
He completed postgraduate training in internal medicine and infectious diseases
at the University of North Carolina at Chapel Hill and is board certified in both.
From 1977 to 1983 he served with the U.S. Army Medical Research and Development Command, followed by a 14-year period on the faculty of the University
of North Carolina School of Medicine. He moved to UTMB in 1997, serving
first as chair of the Department of Microbiology and Immunology, then as dean
of the School of Medicine from 1999 to 2004. Dr. Lemon’s research interests
relate to the molecular virology and pathogenesis of the positive-stranded RNA
viruses responsible for hepatitis. He has had a long-standing interest in antiviral
and vaccine development and has served previously as chair of the Anti-Infective
Drugs Advisory Committee of the U.S. Food and Drug Administration (FDA).
He is the past chair of the Steering Committee on Hepatitis and Poliomyelitis of
the World Health Organization (WHO) Programme on Vaccine Development. He
currently serves as a member of the U.S. Delegation of the U.S.–Japan Cooperative Medical Sciences Program, and he chairs the Board of Scientific Councilors
of the National Center for Infectious Diseases (NCID) of the Centers for Disease
Control and Prevention (CDC). He was co-chair of the Committee on Advances
in Technology and the Prevention of Their Application to Next Generation Biowarfare Threats for the National Academy of Sciences (NAS), and he recently
chaired an Institute of Medicine (IOM) study committee related to vaccines
243
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global infectious disease surveillance and detection
for the protection of the military against naturally occurring infectious disease
threats.
Margaret A. Hamburg, M.D. (Vice-chair), is vice president for Biological Programs at the Nuclear Threat Initiative, a charitable organization working to reduce
the global threat from nuclear, biological, and chemical weapons. She is in charge
of the biological program area. She completed her internship and residency in
internal medicine at the New York Hospital/Cornell University Medical Center
and is certified by the American Board of Internal Medicine. Dr. Hamburg is a
graduate of Harvard College and Harvard Medical School. Before taking on her
current position, she was the assistant secretary for planning and evaluation, U.S.
Department of Health and Human Services (HHS), serving as a principal policy
advisor to the secretary of health and human services with responsibilities including policy formulation and analysis, the development and review of regulations
and legislation, budget analysis, strategic planning, and the conduct and coordination of policy research and program evaluation. Prior to this, she served for
nearly six years as the commissioner of health for the city of New York. As chief
health officer in the nation’s largest city, her many accomplishments included the
design and implementation of an internationally recognized tuberculosis control
program that produced dramatic declines in tuberculosis cases, the development
of initiatives that raised childhood immunization rates to record levels, and the
creation of the first public health bioterrorism preparedness program in the nation.
She currently serves on the Harvard University Board of Overseers. She has been
elected to membership in the IOM, the New York Academy of Medicine, and the
Council on Foreign Relations and is a fellow of the American Association for the
Advancement of Science (AAAS) and the American College of Physicians.
P. Frederick Sparling, M.D. (Vice-chair), is the J. Herbert Bate Professor Emeritus of Medicine, Microbiology, and Immunology at the University of North
Carolina (UNC) at Chapel Hill and is director of the North Carolina Sexually
Transmitted Infections Research Center. Previously he served as chair of the
Department of Medicine and chair of the Department of Microbiology and Immunology at UNC. He was president of the Infectious Diseases Society of America
(IDSA) from 1996 to 1997. He was also a member of the IOM’s Committee on
Microbial Threats to Health (1991–1992). Dr. Sparling’s laboratory research is in
the molecular biology of bacterial outer membrane proteins involved in pathogenesis, with a major emphasis on gonococci and meningococci. His current studies
focus on the biochemistry and genetics of iron-scavenging mechanisms used by
gonococci and meningococci and the structure and function of the gonococcal
porin proteins. He is pursuing the goal of a vaccine for gonorrhea.
David W. K. Acheson, M.D., is chief medical officer at the FDA’s Center for
Food Safety and Applied Nutrition. He received his medical degree at the Uni-
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APPENDIX C
versity of London. After completing internships in general surgery and medicine,
he continued his postdoctoral training in Manchester, England, as a Wellcome
Trust research fellow. He subsequently was a Wellcome Trust training fellow
in Infectious Diseases at the New England Medical Center and at the Wellcome
Research Unit in Vellore, India. He was associate professor of medicine, Division
of Geographic Medicine and Infectious Diseases, New England Medical Center,
until 2001. He then joined the faculties of the Department of Epidemiology
and Preventive Medicine and Department of Microbiology and Immunology at
the University of Maryland Medical School. Currently at FDA, Dr. Acheson’s
research concentration is on foodborne pathogens and encompasses a mixture of
molecular pathogenesis, cell biology, and epidemiology. Specifically, his research
focuses on Shiga toxin-producing E. coli and understanding toxin interaction
with intestinal epithelial cells using tissue culture models. His laboratory has also
undertaken a study to examine Shiga toxin-producing E. coli in food animals in
relation to virulence factors and antimicrobial resistance patterns. More recently,
Dr. Acheson initiated a project to understand the molecular pathogenesis of
Campylobacter jejuni. Other studies have undertaken surveillance of diarrheal
disease in the community to determine causes, outcomes, and risk factors of
unexplained diarrhea. Dr. Acheson has authored or coauthored more than 72 journal articles and 42 book chapters and reviews, and he is coauthor of the book Safe
Eating (Dell Health, 1998). He serves as a reviewer for more than 10 journals
and is on the editorial boards of Infection and Immunity and Clinical Infectious
Diseases. He is a fellow of the Royal College of Physicians and a fellow of the
Infectious Diseases Society of America, and he holds several patents.
Ruth L. Berkelman, M.D., is the Rollins Professor and director of the Center for
Public Health Preparedness and Research at the Rollins School of Public Health,
Emory University in Atlanta. She received her A.B. from Princeton University
and her M.D. from Harvard Medical School. Board certified in pediatrics and
internal medicine, she began her career at CDC in 1980 and later became deputy
director of NCID. She also served as a senior advisor to the director, CDC, and
as assistant surgeon general in the U.S. Public Health Service. In 2001 she came
to her current position at Emory University, directing a center focused on emerging infectious disease and other urgent threats to health, including terrorism. She
has also consulted with the biologic program of the Nuclear Threat Initiative and
is most recognized for her work in infectious diseases and disease surveillance.
She was elected to the IOM in 2004. Currently a member of the Board on Life
Sciences of The National Academies, she also chairs the Board of Public and
Scientific Affairs at the American Society of Microbiology (ASM).
Enriqueta C. Bond, Ph.D., is president of the Burroughs Wellcome Fund. She
received her undergraduate degree from Wellesley College, her M.A. from the
University of Virginia, and her Ph.D. in molecular biology and biochemical
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global infectious disease surveillance and detection
genetics from Georgetown University. She is a member of the IOM, the AAAS,
the ASM, and the American Public Health Association. Dr. Bond serves on the
council of the IOM as its vice chair; she chairs the Board of Scientific Counselors
for NCID at CDC, and she chairs the IOM’s Clinical Research Roundtable. She
serves on the board and the executive committee of the Research Triangle Park
Foundation and on the board of the Medicines for Malaria Venture. Prior to being
named president of the Burroughs Wellcome Fund in 1994, she had served on the
staff of the IOM since 1979, becoming the IOM’s executive officer in 1989.
Roger G. Breeze, Ph.D., received his veterinary degree in 1968 and his Ph.D.
in veterinary pathology in 1973, both from the University of Glasgow, Scotland.
He was engaged in teaching, diagnostic pathology, and research on respiratory
and cardiovascular diseases at the University of Glasgow Veterinary School from
1968 to 1977 and at Washington State University College of Veterinary Medicine from 1977 to 1987, where he was professor and chair of the Department of
Microbiology and Pathology. From 1984 to 1987 he was deputy director of the
Washington Technology Center, the state’s high-technology sciences initiative,
based in the College of Engineering at the University of Washington. In 1987,
he was appointed director of the U.S. Department of Agriculture’s (USDA’s)
Plum Island Animal Disease Center, a biosafety level 3 facility for research and
diagnosis of the world’s most dangerous livestock diseases. In that role he initiated research into the genomic and functional genomic basis of disease pathogenesis, diagnosis, and control of livestock RNA and DNA virus infections. This
work became the basis of U.S. defense against natural and deliberate infection
with these agents and led to his involvement in the early 1990s in biological
weapons defense and proliferation prevention. From 1995 to 1998, he directed
research programs in 20 laboratories in the Southeast for the USDA Agricultural Research Service before going to Washington, DC, to establish biological
weapons defense research programs for USDA. He received the Distinguished
Executive Award from President Clinton in 1998 for his work at Plum Island and
in biodefense. Since 2004 he has been chief executive officer of Centaur Science
Group, which provides consulting services in biodefense. His main commitment
is to the Defense Threat Reduction Agency’s Biological Weapons Proliferation
Prevention program in Europe, the Caucasus, and Central Asia.
Steven J. Brickner, Ph.D., is research advisor, antibacterials chemistry, at Pfizer
Global Research and Development. He received his Ph.D. in organic chemistry
from Cornell University and was a National Institutes of Health (NIH) postdoctoral research fellow at the University of Wisconsin–Madison. He is a medicinal
chemist with nearly 20 years of research experience in the pharmaceutical industry, all focused on the discovery and development of novel antibacterial agents.
He is an inventor or coinventor on 21 U.S. patents and has published numerous
scientific papers, primarily within the area of the oxazolidinones. Prior to join-
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APPENDIX C
ing Pfizer in 1996, he led a team at Pharmacia and Upjohn that discovered and
developed linezolid, the first member of a new class of antibiotics to be approved
in the past 35 years.
Nancy Carter-Foster, M.S.T.M., is senior advisor for health affairs for the U.S.
Department of State, assistant secretary for science and health, and the secretary’s
representative on HIV/AIDS. She is responsible for identifying emerging health
issues and making policy recommendations for U.S. foreign policy concerns regarding international health, and she coordinates the department’s interactions with the
nongovernmental community. She is a member of the IDSA and the AAAS. She has
helped bring focus to global health issues in U.S. foreign policy and has brought a
national security focus to global health. In prior positions as director for congressional and legislative affairs for the Economic and Business Affairs Bureau of the
U.S. Department of State, foreign policy advisory to the majority whip of the U.S.
House of Representatives, trade specialist advisor to the House of Representatives
Ways and Means Trade Subcommittee, and consultant to the World Bank, Asia
Technical Environment Division, Ms. Carter-Foster has worked on a wide variety
of health, trade, and environmental issues amassing in-depth knowledge and experience in policy development and program implementation.
Gail H. Cassell, Ph.D., is vice president of Scientific Affairs, Distinguished Lilly
Research Scholar for Infectious Diseases, Eli Lilly & Company. Previously she
was the Charles H. McCauley Professor and, beginning in 1987, the chair of the
Department of Microbiology, University of Alabama Schools of Medicine and
Dentistry at Birmingham, a department which, under her leadership, ranked first
in research funding from NIH since 1989. She is a member of the Director’s
Advisory Committee of CDC. Dr. Cassell is past president of the ASM and is
serving her third 3-year term as chair of the Public and Scientific Affairs Board of
the ASM. She is a former member of the NIH Director’s Advisory Committee and
a former member of the Advisory Council of the National Institute of Allergy and
Infectious Diseases. She has also served as an advisor on infectious diseases and
indirect costs of research to the White House Office on Science and Technology
and was previously chair of the Board of Scientific Counselors of NCID at CDC.
She served 8 years on the Bacteriology-Mycology-II Study Section and served
as its chair for 3 years. She serves on the editorial boards of several prestigious
scientific journals and has authored more than 275 articles and book chapters. She
has been intimately involved in the establishment of science policy and legislation related to biomedical research and public health. Dr. Cassell has received
several national and international awards and an honorary degree for her research
on infectious diseases.
Bill Colston, Ph.D., is currently the division leader for the Chemical and Biological Countermeasures Division at Lawrence Livermore National Laboratory
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global infectious disease surveillance and detection
(LLNL). This newly formed division consists of four programs whose missions
include threat awareness, detection, response, and attribution. These programs
are made up of approximately 190 researchers from a variety of disciplines. The
mission of these programs is to provide science, technology, and deployed capabilities to defend the nation, its people, and warfighters against the threat of biological and chemical terrorism. The larger vision is to meet the challenges of an
ever-changing threat by transforming our understanding of pathogenicity and host
response and expanding our reach globally. Dr. Colston holds a Ph.D. in biomedical engineering and has published numerous publications and patents, largely in
biological measurement sciences. Directly prior to this assignment, he founded
the Department of Homeland Security’s Biodefense Knowledge Center.
Col. Ralph (Loren) Erickson, M.D., Dr.P.H., M.P.H., is the director of the
Department of Defense Global Emerging Infections Surveillance and Response
System (DoD-GEIS) headquartered in Silver Spring, Maryland. He holds a B.S.
degree in chemistry from the University of Washington, an M.D. from the Uniformed Services University of the Health Sciences, an M.P.H. from Harvard, and
a Dr.P.H. from Johns Hopkins. Residency trained and board certified in preventive medicine, Dr. Erickson has held a number of leadership positions within
the Army Medical Department, including: director of the General Preventive
Medicine Residency Program, Walter Reed Army Institute of Research; director
of Epidemiology and Disease Surveillance, U.S. Army Center for Health Promotion and Preventive Medicine; commander of the U.S. Army Center for Health
Promotion and Preventive Medicine (Europe); and specialty leader for all U.S.
Army preventive medicine physicians.
Mark B. Feinberg, M.D., Ph.D., is vice president for Policy, Public Health, and
Medical Affairs in the Merck Vaccine Division of Merck & Co., Inc. He received
his bachelor’s degree magna cum laude from the University of Pennsylvania in
1978 and his M.D. and Ph.D. from Stanford University School of Medicine in
1987. From 1985 to 1986, Dr. Feinberg served as a project officer for the Committee on a National Strategy for AIDS of the IOM and the NAS. Following receipt
of his M.D. and Ph.D., he pursued postgraduate residency training in internal
medicine at the Brigham and Women’s Hospital of Harvard Medical School and
postdoctoral fellowship research in the laboratory of Dr. David Baltimore at the
Whitehead Institute for Biomedical Research. From 1991 to 1995, Dr. Feinberg
was an assistant professor of medicine, microbiology, and immunology at the University of California, San Francisco (UCSF), where he also served as an attending
physician in the AIDS/Oncology Division and as director of the Virology Research
Laboratory at San Francisco General Hospital. From 1995 to 1997, he was a medical officer in the Office of AIDS Research in the office of the director of NIH, and
chair of the NIH Coordinating Committee on AIDS Etiology and Pathogenesis
Research. During this period, he also served as executive secretary of the NIH
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APPENDIX C
Panel to Define Principles of Therapy of HIV Infection. Prior to joining Merck in
2004, Dr. Feinberg served as professor of medicine and microbiology and immunology at the Emory University School of Medicine and as an investigator at the
Emory Vaccine Center. He also founded and served as the medical director of the
Hope Clinic—a clinical research facility devoted to the clinical evaluation of novel
vaccines and to translational research studies of human immune system biology.
At UCSF and Emory, Dr. Feinberg and colleagues were engaged in the preclinical development and evaluation of novel vaccines for HIV and other infectious
diseases and in basic research studies focused on revealing fundamental aspects
of host–virus relationships that underlie the pathogenesis of HIV and simian
immunodeficiency virus infections. In addition to his other professional roles, he
has also served as a consultant to, and member of, several committees of the IOM
and the NAS.
J. Patrick Fitch, Ph.D., is laboratory director for the National Biodefense Analysis and Countermeasures Center (NBACC) and the president of Battelle National
Biodefense Institute, LLC (BNBI). BNBI manages and operates the NBACC
national laboratory for the Department of Homeland Security as a Federally
Funded Research and Development Center established in 2006. The NBACC
mission is to provide the nation with the scientific basis for awareness of biological threats and attribution of their use against the American public. Dr. Fitch
joined Battelle in 2006 as vice president for Biodefense Programs after more
than 20 years of experience leading multidisciplinary applied science teams at the
University of California’s Lawrence Livermore National Laboratory. From 2001
to 2006, he led the LLNL Chemical and Biological National Security Program
(CBNP), with applied science programs from pathogen biology and material
science to deployed systems. CBNP accomplishments include performing more
than 1 million assays on national security samples; setting up and operating 24/7
reach-back capabilities; setting up a nationwide bioalert system; receiving three
R&D 100 awards; designing signatures for validated assays in the CDC Laboratory Response Network and the National Animal Health Laboratory Network;
and designing, demonstrating, and deploying the BASIS biodetection system,
leading to the nationwide BioWatch system. He has authored several books and
book chapters, including An Engineering Introduction to Biotechnology. He has
chaired and served on several panels of The National Academies. His advisory
board activities have included U.S. Animal Health Association, Texas A&M
University DHS Center of Excellence, Central Florida University (College of
Engineering), Colorado State University (College of Engineering), California
State Breast Cancer Research Program, and Biomolecular Engineering. Dr. Fitch
was a fellow of the American Society for Laser Medicine and Surgery and an
associate editor of Circuits, Systems and Signal Processing. He has received two
national awards for medical devices, a technical writing award for an article in
Science, and an international best paper award from the Institute of Electrical
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global infectious disease surveillance and detection
and Electronics Engineers (IEEE). He also coinvented the technology, developed
the initial business plan, and successfully raised venture investments for a hightech medical device start-up company. Dr. Fitch received his Ph.D. from Purdue
University and B.S. from Loyola College of Maryland.
Capt. Darrell R. Galloway, M.S.C., Ph.D., is chief of the Medical Science
and Technology Division for the Chemical and Biological Defense Directorate
at the Defense Threat Reduction Agency. He received his baccalaureate degree
in microbiology from California State University in Los Angeles in 1973. After
completing military service in the U.S. Army as a medical corpsman from 1969
to 1972, Captain Galloway entered graduate school and completed a doctoral
degree in biochemistry in 1978 from the University of California, followed by
2 years of postgraduate training in immunochemistry as a fellow of the National
Cancer Institute at the Scripps Clinic and Research Foundation in La Jolla, California. Captain Galloway began his navy career at the Naval Medical Research
Institute in Bethesda, Maryland, where from 1980 to 1984 he served as a research
scientist working on vaccine development. In late 1984 Captain Galloway left
active service to pursue an academic appointment at Ohio State University, where
he is now a tenured faculty member in the Department of Microbiology. He also
holds appointments at the University of Maryland Biotechnology Institute and
the Uniformed Services University of Health Sciences. He has an international
reputation in the area of bacterial toxin research and has published more than 50
research papers on various studies of bacterial toxins. In recent years Captain
Galloway’s research has concentrated on anthrax and the development of DNAbased vaccine technology. His laboratory has contributed substantially to the
development of a new DNA-based vaccine against anthrax that has completed the
first phase of clinical trials. Captain Galloway is a member of the ASM and has
served as president of the Ohio branch of that organization. He received an NIH
Research Career Development Award. In 2005 Captain Galloway was awarded
the Joel M. Dalrymple Award for significant contributions to biodefense vaccine
development.
S. Elizabeth George, Ph.D., is deputy director, Biological Countermeasures
Portfolio Science and Technology Directorate, Department of Homeland Security
(DHS). Until merging into the new department in 2003, she was program manager
of the Chemical and Biological National Security Program in the Department of
Energy’s National Nuclear Security Administration’s Office of Nonproliferation
Research and Engineering. Significant accomplishments include the design and
deployment of BioWatch, the nation’s first civilian biological threat agent monitoring system, and PROTECT, the first civilian operational chemical detection
and response capability deployed in the Washington, DC, area subway system.
Previously, she spent 16 years at the U.S. Environmental Protection Agency
(EPA), Office of Research and Development, National Health and Ecological
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Effects Research Laboratory, Environmental Carcinogenesis Division, where she
was branch chief of the Molecular and Cellular Toxicology Branch. She received
her B.S. in biology in 1977 from Virginia Polytechnic Institute and State University and her M.S. and Ph.D. in microbiology in 1979 and 1984, respectively, from
North Carolina State University. From 1984 to 1986, she was a National Research
Council fellow in the laboratory of Dr. Larry Claxton at EPA. Dr. George is the
2005 chair of the Chemical and Biological Terrorism Defense Gordon Research
Conference. She has served as councilor for the Environmental Mutagen Society
and president and secretary of the Genotoxicity and Environmental Mutagen
Society. She holds memberships in the ASM and the AAAS and is an adjunct
faculty member in the School of Rural Public Health, Texas A&M University. She
is a recipient of the EPA Bronze Medal and Scientific and Technological Achievement Awards and DHS Under Secretary’s Award for Science and Technology.
She is the author of numerous journal articles and has presented her research at
national and international meetings.
Jesse L. Goodman, M.D., M.P.H., is director of FDA’s Center for Biologics
Evaluation and Research (CBER), which oversees medical, public health, and
policy activities concerning the development and assessment of vaccines, blood
products, tissues, and related devices and novel therapeutics, including cellular
and gene therapies. He moved full-time to FDA in 2001 from the University of
Minnesota, where he was professor of and director of the Division of Infectious
Diseases. A graduate of Harvard College, he received his M.D. at the Albert Einstein College of Medicine, did residency and fellowship training at the Hospital
of the University of Pennsylvania and at the University of California–Los Angeles (UCLA; where he was also chief medical resident), and is board certified in
internal medicine, oncology, and infectious diseases. He trained in the virology
laboratory of Jack Stevens at UCLA and has had an active laboratory program in
the molecular pathogenesis of infectious diseases. In 1995 his laboratory isolated
the etiologic agent of human granulocytic ehrlichiosis (HGE) and subsequently
characterized fundamental events involved in infection of leukocytes, including
their cellular receptors. He is editor of the book Tick Borne Diseases of Humans
published by ASM Press in 2005 and is a staff physician and infectious diseases
consultant at the NIH Clinical Center and the National Naval Medical Center/
Walter Reed Army Medical Center, as well as adjunct professor of medicine at
the University of Minnesota. He is active in a wide variety of clinical, public
health, and product development issues, including pandemic and emerging infectious disease threats, bioterrorism preparedness and response, and blood, tissue,
and vaccine safety and availability. In these activities, he has worked closely
with CDC, NIH, and other HHS components, academia, and the private sector,
and he has put into place an interactive team approach to emerging threats. This
model was used in the collaborative development and rapid implementation of
nationwide donor screening of the U.S. blood supply for West Nile virus. He has
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been elected to the American Society for Clinical Investigation (ASCI) and to
the IOM.
Eduardo Gotuzzo, M.D., is principal professor and director at the Instituto de
Medicina Tropical “Alexander von Humbolt,” Universidad Peruana Cayetan
Heredia (UPCH) in Lima, Peru, as well as chief of the Department of Infectious
and Tropical Diseases at the Cayetano Heredia Hospital. He is also an adjunct
professor of medicine at the University of Alabama, Birmingham School of
Medicine. Dr. Gotuzzo is an active member in numerous international societies
and has been president of the Latin America Society of Tropical Disease (2000–
2003), the IDSA Scientific Program (2000–2003), the International Organizing
Committee of the International Congress of Infectious Diseases (1994–present),
president-elect of the International Society for Infectious Diseases (1996–1998),
and president of the Peruvian Society of Internal Medicine (1991–1992). He has
published more than 230 articles and chapters as well as six manuals and one
book. Recent honors and awards include being named an honorary member of the
American Society of Tropical Medicine and Hygiene in 2002, associate member
of the National Academy of Medicine in 2002, honorary member of the Society
of Internal Medicine in 2000, and distinguished visitor at the Faculty of Medical
Sciences, University of Cordoba, Argentina, in 1999. In 1988 he received the
Golden Medal for Outstanding Contribution in the Field of Infectious Diseases
awarded by Trnava University, Slovakia.
Jo Handelsman, Ph.D., received her Ph.D. in molecular biology from the University of Wisconsin–Madison (UW–M) in 1984 and joined the faculty of the
UW–M Department of Plant Pathology in 1985, where she is currently a Howard
Hughes Medical Institute (HHMI) professor. Her research focuses on the genetic
and functional diversity of microorganisms in soil and insect gut communities.
The Handelsman lab has concentrated on discovery and biological activity of
novel antibiotics from cultured and uncultured bacteria and has contributed to the
pioneering of a new technique called metagenomics that facilitates the genomic
analysis of assemblages of uncultured microorganisms. Handelsman is studying
the mid-gut of the gypsy moth to understand the basis for resistance and susceptibility of microbial communities to invasion, developing it as a model for
the microbial community in the human gut. In addition to her passion for understanding the secret lives of bacteria, Dr. Handelsman is dedicated to improving
science education and the advancement of women in research universities. She
is director of the HHMI New Generation Program for Scientific Teaching, which
is dedicated to teaching graduate and postdoctoral students the principles and
practices of teaching and mentoring. She is codirector of The National Academies
Summer Institute for Undergraduate Education in Biology, a collaborative venture between HHMI and The National Academies that aims to train a nationwide
network of faculty who are outstanding teachers and mentors. Dr. Handelsman
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is codirector of the Women in Science and Engineering Leadership Institute
at UW–M, whose mission is to understand the impediments to the successful
recruitment and advancement of women faculty in the sciences and to develop
and study interventions intended to reduce those barriers.
Carole A. Heilman, Ph.D., is director of the Division of Microbiology and
Infectious Diseases (DMID) of the National Institute of Allergy and Infectious
Diseases (NIAID). She received her bachelor’s degree in biology from Boston
University in 1972 and earned her master’s degree and doctorate in microbiology from Rutgers University in 1976 and 1979, respectively. Dr. Heilman began
her NIH career as a postdoctoral research associate with the National Cancer
Institute, where she carried out research on the regulation of gene expression during cancer development. In 1986, she came to NIAID as the influenza and viral
respiratory diseases program officer in DMID and, in 1988, she was appointed
chief of the respiratory diseases branch, where she coordinated the development of acellular pertussis vaccines. She joined the Division of AIDS as deputy
director in 1997 and was responsible for developing the Innovation Grant Program for Approaches in HIV Vaccine Research. She is the recipient of several
notable awards for outstanding achievement. Throughout her extramural career,
Dr. Heilman has contributed articles on vaccine design and development to many
scientific journals and has served as a consultant to the World Bank and WHO.
She is also a member of several professional societies, including the IDSA, the
ASM, and the American Society of Virology.
David L. Heymann, M.D., is currently assistant director-general for communicable diseases and the representative of the director-general for polio eradication
at the World Health Organization. Prior to that, from July 1998 until July 2003,
Dr. Heymann was executive director of the WHO Communicable Diseases Cluster which includes WHO’s programs on infectious and tropical diseases, and
from which the public health response to SARS was mounted in 2003. From
October 1995 to July 1998 Dr. Heymann was director of the WHO Program on
Emerging and other Communicable Diseases, and prior to that was the chief of
research activities in the WHO Global Program on AIDS. Before joining WHO,
Dr. Heymann worked for 13 years as a medical epidemiologist in sub-Saharan
Africa (Cameroon, Côte d’Ivoire, Malawi, and the Democratic Republic of
Congo—formerly Zaire) on assignment from the CDC in CDC-supported activities. These activities aimed at strengthening capacity in surveillance of infectious
diseases and their control, with special emphasis on the childhood immunizable
diseases including measles and polio, African haemorrhagic fevers, poxviruses,
and malaria. While based in Africa, Dr. Heymann participated in the investigation of the first outbreak of Ebola in Yambuku (former Zaire) in 1976, then
again investigated the second outbreak of Ebola in 1977 in Tandala, and in 1995
directed the international response to the Ebola outbreak in Kikwit. Prior to these
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13 years in Africa, Dr. Heymann worked two years in India as a medical epidemiologist in the WHO Smallpox Eradication Program. Dr. Heymann holds a B.A.
from the Pennsylvania State University, an M.D. from Wake Forest University, a
Diploma in Tropical Medicine and Hygiene from the London School of Hygiene
and Tropical Medicine, and has completed practical epidemiology training in
the two-year Epidemic Intelligence Service (EIS) of CDC. He is a recipient of
the American Public Health Association Award for Excellence and the American
Society of Tropical Medicine and Hygiene Donald MacKay medal, and is a member of the IOM. Dr. Heymann has published over 140 scientific articles on infectious diseases and related issues in medical and scientific journals, and authored
several chapters on infectious diseases in medical textbooks. He is currently editor of the 18th edition of the Control of Communicable Diseases Manual, a joint
publication of WHO and the American Public Health Association.
Phil Hosbach is vice president of New Products and Immunization Policy at
Sanofi Pasteur. The departments under his supervision are new product marketing, state and federal government policy, business intelligence, bids and contracts,
medical communications, public health sales, and public health marketing. His
current responsibilities include oversight of immunization policy development.
He acts as Sanofi Pasteur’s principal liaison with CDC. Mr. Hosbach graduated
from Lafayette College in 1984 with a degree in biology. He has 20 years of
pharmaceutical industry experience, including the past 17 years focused solely on
vaccines. He began his career at American Home Products in Clinical Research
in 1984. He joined Aventis Pasteur (then Connaught Labs) in 1987 as clinical
research coordinator and has held research and development positions of increasing responsibility, including clinical research manager and director of clinical
operations. Mr. Hosbach also served as project manager for the development
and licensure of Tripedia, the first diphtheria, tetanus, and acellular pertussis
(DTaP) vaccine approved by FDA for use in U.S. infants. During his clinical
research career at Aventis Pasteur, he contributed to the development and licensure of seven vaccines and has authored or coauthored several clinical research
articles. From 2000 through 2002, Mr. Hosbach served on the board of directors
for Pocono Medical Center in East Stroudsburg, Pennsylvania. Since 2003 he
has served on the board of directors of Pocono Health Systems, which includes
Pocono Medical Center.
James M. Hughes, M.D., received his B.A. in 1966 and M.D. in 1971 from
Stanford University. He completed a residency in internal medicine at the University of Washington and a fellowship in infectious diseases at the University
of Virginia. He is board certified in internal medicine, infectious diseases, and
preventive medicine. He first joined CDC as an epidemic intelligence service
officer in 1973. During his CDC career, he has worked primarily in the areas
of foodborne disease and infection control in health-care settings. He became
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director of NCID in 1992. The center is currently working to address domestic
and global challenges posed by emerging infectious diseases and the threat of
bioterrorism. He is a member of the IOM and a fellow of the American College
of Physicians, the IDSA, and the AAAS. He is an assistant surgeon general in
the Public Health Service.
Stephen A. Johnston, Ph.D., is currently director of the Center for Innovations in Medicine in the Biodesign Institute at Arizona State University. His
center focuses on formulating and implementing disruptive technologies for
basic problems in health care. The center has three divisions: Genomes to Vaccines, Cancer Eradication, and DocInBox. The Genomes to Vaccines group has
developed high-throughput systems to screen for vaccine candidates and is applying them to predict and produce chemical vaccines. The Cancer Eradication
group is working on formulating a universal prophylactic vaccine for cancer.
The DocInBox group is developing technologies to facilitate presymptomatic
diagnosis. Dr. Johnston founded the Center for Biomedical Inventions (a.k.a.,
Center for Translation Research) at the University of Texas–Southwestern, the
first center of its kind in the medical arena. He and his colleagues have developed
numerous inventions and innovations, including the gene gun, genetic immunization, TEV protease system, organelle transformation, digital optical chemistry
arrays, expression library immunization, linear expression elements, and others.
He also was involved in transcription research for years, first cloning Gal4, then
later discovering functional domains in transcription factors and the connection
of the proteasome to transcription. He has been professor at the University of
Texas Southwestern Medical Center at Dallas and associate and assistant professor at Duke University. He has been involved in several capacities as an advisor
on biosecurity since 1996 and is a member of the WRCE SAB and a founding
member of BioChem 20/20.
Gerald T. Keusch, M.D., is provost and dean for Global Health at Boston
University and Boston University School of Public Health. He is a graduate of
Columbia College (1958) and Harvard Medical School (1963). After completing a residency in internal medicine, fellowship training in infectious diseases,
and 2 years as an NIH research associate at the Southeast Asia Treaty Organization (SEATO) Medical Research Laboratory in Bangkok, Thailand, Dr. Keusch
joined the faculty of Mt. Sinai School of Medicine in 1970, where he established
a laboratory to study the pathogenesis of bacillary dysentery and the biology and
biochemistry of Shiga toxin. In 1979 he moved to Tufts Medical School and New
England Medical Center in Boston to found the Division of Geographic Medicine, which focused on the molecular and cellular biology of tropical infectious
disease. In 1986 he integrated the clinical infectious diseases program into the
Division of Geographic Medicine and Infectious Diseases, continuing as division chief until 1998. He has worked in the laboratory and in the field in Latin
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America, Africa, and Asia on basic and clinical infectious diseases and HIV/
AIDS research. From 1998 to 2003, he was associate director for international
research and director of the Fogarty International Center at NIH. Dr. Keusch is a
member of the American Society for Clinical Investigation (ASCI), the Association of American Physicians, the ASM, and the IDSA. He has received the Squibb
(1981), Finland (1997), and Bristol (2002) awards of the IDSA. In 2002 he was
elected to the IOM.
Rima F. Khabbaz, M.D., is director of NCID at CDC. She received her B.S. in
1975 and her M.D. in 1979 from the American University of Beirut in Lebanon.
She trained in internal medicine and completed a fellowship in infectious diseases at the University of Maryland in Baltimore. She is board certified in
internal medicine. She first joined CDC as an epidemic intelligence service
officer in 1980. During her CDC career, she worked primarily in the areas of
health care–associated infections and viral diseases. She is a fellow of the IDSA
and an elected member of the American Epidemiologic Society. She served on
FDA’s Blood Product Advisory Committee, on FDA’s Transmissible Spongiform
Encephalopathy Advisory Committee and on the Annual Meeting Scientific Program Committee of the IDSA. She played a leading role in developing CDC’s
programs related to blood and food safety and in CDC’s responses to outbreaks
of new and reemerging diseases.
Lonnie J. King, D.V.M., is currently the director of CDC’s new National Center
for Zoonotic, Vector-Borne, and Enteric Diseases (NCZVED). Dr. King leads the
center’s activities for surveillance, diagnostics, disease investigations, epidemiology, research, public education, policy development, and disease prevention and
control programs. NCZVED also focuses on waterborne, foodborne, vectorborne,
and zoonotic diseases of public health concern, which also includes most of CDC’s
select and bioterrorism agents, neglected tropical diseases, and emerging zoonoses.
Before serving as director, he was the first chief of the agency’s Office of Strategy
and Innovation. In 1996 Dr. King was appointed dean of the College of Veterinary
Medicine, Michigan State University. He served for 10 years as dean of the college. As dean, he was the chief executive officer for academic programs, research,
the teaching hospital, diagnostic center for population and animal health, basic and
clinical science departments, and outreach and continuing education programs. As
dean and professor of large animal clinical sciences, Dr. King was instrumental
in obtaining funds for the construction of the $60 million Diagnostic Center for
Population and Animal Health, initiated the Center for Emerging Infectious Diseases in the college, served as the campus leader in food safety, and had oversight
for the National Food Safety and Toxicology Center. He brought the Center for
Integrative Toxicology to the college and was the university’s designated leader
for counterbioterrorism activities for his college and was involved in reestablishing
public health programs at Michigan State University. Prior to this, Dr. King was
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APPENDIX C
administrator for USDA’s Animal and Plant Health Inspection Service (APHIS).
Dr. King served as the country’s chief veterinary officer for 5 years and worked
extensively in global trade agreements within the North American Free Trade
Agreement and the World Trade Organization. Before beginning his government
career in 1977, he was in private veterinary practice for 7 years in Ohio and
Georgia. He received his B.S. and D.V.M. from Ohio State University in 1966
and 1970, respectively. He earned his M.S. in epidemiology from the University
of Minnesota while on special assignment with USDA in 1980. He received his
master’s in public administration from The American University in Washington,
DC, in 1991. Dr. King has a broad knowledge of animal agriculture and the veterinary profession through his work with other governmental agencies, universities,
major livestock and poultry groups, and private practitioners. Dr. King is a boardcertified member of the American College of Veterinary Preventive Medicine and
has completed the senior executive fellowship program at Harvard University. He
served as president of the Association of American Veterinary Medical Colleges
from 1999 to 2000 and was vice chair for the National Commission on Veterinary
Economic Issues from 2000 to 2004. Dr. King helped start the National Alliance
for Food Safety, served on the Governor’s Task Force on Chronic Wasting Disease for the state of Michigan, and was a member of four NAS committees; most
recently he chaired The National Academies Committee on Assessing the Nation’s
Framework for Addressing Animal Diseases. Dr. King is one of the developers
of the Science, Politics, and Animal Health Policy Fellowship Program, and he
lectures extensively on the future of animal health and veterinary medicine. He
served as a consultant and member of the Board of Scientific Counselors to CDC’s
National Center for Infectious Diseases and is a member of the IOM’s Forum on
Microbial Threats. Dr. King is an editor for the OIE Scientific Review on Emerging Zoonoses, is a current member of FDA’s Board of Scientific Advisors, and is
president of the American Veterinary Epidemiology Society. Dr. King was elected
to the IOM in 2004.
Col. George W. Korch, Ph.D., is commander, U.S. Army Medical Research
Institute for Infectious Diseases, Ft. Detrick, Maryland. Dr. Korch attended
Boston University and earned a B.S. in biology in 1974, followed by postgraduate
study in mammalian ecology at the University of Kansas from 1975 to 1978. He
earned his Ph.D. from the Johns Hopkins School of Hygiene and Public Health
in Immunology and Infectious Diseases in 1985, followed by postdoctoral experience at Johns Hopkins from 1985 to 1986. His areas of training and specialty are
the epidemiology of zoonotic viral pathogens and medical entomology. For the
past 15 years, he has also been engaged in research and program management for
medical defense against biological pathogens used in terrorism or warfare.
Joshua Lederberg, Ph.D., is professor emeritus of molecular genetics and informatics and Sackler Foundation Scholar at the Rockefeller University in New York
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City. His lifelong research, for which he received the Nobel Prize in 1958, has
been in genetic structure and function in microorganisms. He has a keen interest
in international health and from 1990 to 1992 was co-chair of a previous IOM
Committee on Emerging Microbial Threats to Health. Currently he is co-chair
of the Committee on Emerging Microbial Threats to Health in the Twenty-First
Century. He has been a member of the NAS since 1957 and is a charter member
of the IOM.
Lynn G. Marks, M.D., is board certified in internal medicine and infectious diseases. He was on the faculty at the University of South Alabama College of Medicine in the Infectious Diseases Department, focusing on patient care, teaching,
and research, where his academic research interest was in the molecular genetics
of bacterial pathogenicity. He subsequently joined the anti-infectives clinical
group of SmithKline Beecham (now GlaxoSmithKline) and later advanced to be
global head of the Consumer Healthcare Division Medical and Regulatory Group.
He then returned to pharmaceutical research and development as global head of
the Infectious Diseases Therapeutic Area Strategy Team for GlaxoSmithKline.
Edward McSweegan, Ph.D., is a program officer at NIAID. He graduated from
Boston College with a B.S. in 1978. He has an M.S. in microbiology from the
University of New Hampshire and a Ph.D. in microbiology from the University
of Rhode Island. He was a National Research Council Associate from 1984 to
1986 and did postdoctoral research at the Naval Medical Research Institute in
Bethesda, Maryland. Dr. McSweegan served as an AAAS diplomacy fellow in the
U.S. State Department from 1986 to 1988 and negotiated science and technology
agreements with Poland, Hungary, and the former Soviet Union. After moving to
NIH, he continued to work on international health and science projects in Egypt,
Israel, India, and Russia. Currently, he manages NIAID’s bilateral program with
India, the Indo–U.S. Vaccine Action Program, and represents NIAID in the HHS
Biotechnology Engagement Program with Russia and related countries. He is a
member of the AAAS, the ASM, and the DC Science Writers Association. He is
the author of numerous journal and science articles.
Stephen S. Morse, Ph.D., is founding director of the Center for Public Health
Preparedness at the Mailman School of Public Health of Columbia University and
is an associate professor in the epidemiology department. He recently returned
to Columbia after 4 years in government service as program manager at the
Defense Advanced Research Projects Agency (DARPA), where he codirected
the Pathogen Countermeasures Program and subsequently directed the Advanced
Diagnostics Program. Before coming to Columbia, he was assistant professor of
virology at Rockefeller University in New York, where he remains an adjunct faculty member. He is the editor of two books, Emerging Viruses (Oxford University
Press, 1993; paperback, 1996), which was selected by American Scientist for its
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APPENDIX C
list of 100 Top Science Books of the 20th Century, and The Evolutionary Biology
of Viruses (Raven Press, 1994). He currently serves as a section editor of the CDC
journal Emerging Infectious Diseases and was formerly an editor-in-chief of the
Pasteur Institute’s journal Research in Virology. Dr. Morse was chair and principal
organizer of the 1989 NIAID/NIH Conference on Emerging Viruses, for which he
originated the term and concept of emerging viruses/infections. He has served as
a member of the IOM/NAS Committee on Emerging Microbial Threats to Health,
chaired its Task Force on Viruses, and was a contributor to the resulting report,
Emerging Infections (1992). He was a member of the IOM’s Committee on Xenograft Transplantation and he currently serves on the Steering Committee of the
IOM’s Forum on Emerging Infections (now the Forum on Microbial Threats). Dr.
Morse also served as an adviser to WHO, the Pan‑American Health Organization,
FDA, the Defense Threat Reduction Agency, and other agencies. He is a fellow of
the New York Academy of Sciences and a past chair of its microbiology section,
a fellow of the American Academy of Microbiology of the American College of
Epidemiology, and an elected life member of the Council on Foreign Relations.
He was the founding chair of ProMED, the nonprofit international Program to
Monitor Emerging Diseases, and was one of the originators of ProMED-mail,
an international network inaugurated by ProMED in 1994 for outbreak reporting
and disease monitoring using the Internet. Dr. Morse received his Ph.D. from the
University of Wisconsin–Madison.
Michael T. Osterholm, Ph.D., M.P.H., is director of the Center for Infectious
Disease Research and Policy at the University of Minnesota, where he is also professor at the School of Public Health. Previously, Dr. Osterholm was the state epidemiologist and chief of the acute disease epidemiology section for the Minnesota
Department of Health. He has received numerous research awards from NIAID
and CDC. He served as principal investigator for the CDC-sponsored Emerging
Infections Program in Minnesota. He has published more than 240 articles and
abstracts on various emerging infectious disease problems and is the author of the
best-selling book, Living Terrors: What America Needs to Know to Survive the
Coming Bioterrorist Catastrophe. He is past president of the Council of State and
Territorial Epidemiologists. He currently serves on the IOM Forum on Microbial
Threats. He has also served on the IOM Committee to Ensure Safe Food from
Production to Consumption, the IOM Committee on the Department of Defense
Persian Gulf Syndrome Comprehensive Clinical Evaluation Program, and as a
reviewer for the IOM report on chemical and biological terrorism.
George Poste, Ph.D., D.V.M., is director of the Arizona Biodesign Institute and
Dell E. Webb Distinguished Professor of Biology at Arizona State University.
From 1992 to 1999, he was chief science and technology officer and president,
Research and Development of SmithKline Beecham (SB). During his tenure at
SB, he was associated with the successful registration of 29 drug, vaccine, and
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diagnostic products. He is chairman of diaDexus and Structural GenomiX in
California and Orchid Biosciences in Princeton. He serves on the board of directors of AdvancePCS and Monsanto. He is an advisor on biotechnology to several
venture capital funds and investment banks. In May 2003, he was appointed as
director of the Arizona Biodesign Institute at Arizona State University. This is a
major new initiative combining research groups in biotechnology, nanotechnology, materials science, advanced computing, and neuromorphic engineering.
He is a fellow of Pembroke College in Cambridge and distinguished fellow at
the Hoover Institution and Stanford University. He is a member of the Defense
Science Board of the U.S. Department of Defense. In this capacity he chairs the
Task Force on Bioterrorism. He is also a member of the NAS Working Group on
Defense Against Bioweapons. Dr. Poste is a board-certified pathologist, a fellow
of the Royal Society, and a fellow of the Academy of Medical Sciences. He was
awarded the rank of Commander of the British Empire by Queen Elizabeth II in
1999 for services to medicine and for the advancement of biotechnology. He has
published more than 350 scientific papers; has coedited 15 books on cancer, biotechnology, and infectious diseases; and serves on the editorial board of multiple
technical journals. He is routinely invited to be the keynote speaker at a wide
variety of academic, corporate, investment, and government meetings to discuss
the impact of biotechnology and genetics on health care and the challenges posed
by bioterrorism.
David A. Relman, M.D., is an associate professor of medicine (infectious diseases and geographic medicine) and of microbiology and immunology at Stanford
University School of Medicine, and chief of the infectious disease section at the
Veterans Affairs (VA) Palo Alto Health Care System. Dr. Relman received his
B.S. in biology from the Massachusetts Institute of Technology and his M.D.
from Harvard Medical School. He completed his residency in internal medicine
and a clinical fellowship in infectious diseases at Massachusetts General Hospital,
Boston, after which he moved to Stanford for a postdoctoral fellowship in 1986,
and joined the faculty there in 1994. His research focus is on understanding the
structure and role of the human indigenous microbial communities in health and
disease. This work brings together approaches from ecology, population biology,
environmental microbiology, genomics, and clinical medicine. A second area
of investigation explores the classification structure of humans and nonhuman
primates with systemic infectious diseases, based on patterns of genome-wide
gene transcript abundance in blood and other tissues. The goals of this work are to
understand mechanisms of host–pathogen interaction, as well as predict clinical
outcome at early time points in the disease process. His scientific achievements
include the description of a novel approach for identifying previously unknown
pathogens, the characterization of a number of new human microbial pathogens,
including the agent of Whipple’s disease, and some of the most in-depth analyses
to date of human indigenous microbial communities. Among his other activities,
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Dr. Relman currently serves as chair of the Board of Scientific Counselors of the
National Institute of Dental and Craniofacial Research (NIH), is a member of the
National Science Advisory Board for Biosecurity, and advises a number of U.S.
government departments and agencies on matters related to pathogen diversity,
the future life sciences landscape, and the nature of present and future biological
threats. He was co-chair of the Committee on Advances in Technology and the
Prevention of Their Application to Next Generation Biowarfare Threats for the
NAS. He received the Squibb Award from the IDSA in 2001, the Senior Scholar
Award in Global Infectious Diseases from the Ellison Medical Foundation in
2002, an NIH Director’s Pioneer Award in 2006, and a Doris Duke Distinguished
Clinical Scientist Award in 2006. He is also a fellow of the American Academy
of Microbiology.
Gary A. Roselle, M.D., received his M.D. from the Ohio State University School
of Medicine in 1973. He served his residency at the Northwestern University
School of Medicine and his infectious diseases fellowship at the University of
Cincinnati School of Medicine. He is the program director for infectious diseases
for the VA Central Office in Washington, DC, as well as the chief of the medical
service at the Cincinnati VA Medical Center. He is a professor of medicine in
the Department of Internal Medicine, Division of Infectious Diseases at the University of Cincinnati College of Medicine. Dr. Roselle serves on several national
advisory committees. In addition, he is currently heading the Emerging Pathogens
Initiative for the Department of Veterans Affairs. He has received commendations
from the Cincinnati Medical Center director, the under secretary for health for
the Department of Veterans Affairs, and the secretary of veterans affairs for his
work in the infectious diseases program for the Department of Veterans Affairs.
He has been an invited speaker at several national and international meetings and
has published more than 80 papers and several book chapters.
Janet Shoemaker is director of the ASM’s Public Affairs Office, a position she
has held since 1989. She is responsible for managing the legislative and regulatory affairs of this 42,000-member organization, the largest single biological science society in the world. She has served as principal investigator for a project
funded by the National Science Foundation (NSF) to collect and disseminate data
on the job market for recent doctorates in microbiology and has played a key role
in ASM projects, including the production of the ASM Employment Outlook in
the Microbiological Sciences and The Impact of Managed Care and Health System Change on Clinical Microbiology. Previously, she held positions as assistant
director of public affairs for the ASM, as ASM coordinator of the U.S./U.S.S.R.
Exchange Program in Microbiology, a program sponsored and coordinated by
NSF and the U.S. Department of State, and as a freelance editor and writer. She
received her baccalaureate, cum laude, from the University of Massachusetts, and
is a graduate of the George Washington University programs in public policy and
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Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
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global infectious disease surveillance and detection
in editing and publications. She has served as commissioner to the Commission
on Professionals in Science and Technology and as the ASM representative to
the ad hoc Group for Medical Research Funding, and is a member of Women in
Government Relations, the American Society of Association Executives, and the
AAAS. She has coauthored published articles on research funding, biotechnology,
biological weapons control, and public policy issues related to microbiology.
Brian J. Staskawicz, Ph.D., is professor and chair, Department of Plant and
Microbial Biology, University of California–Berkeley. Dr. Staskawicz received
his B.A. in biology from Bates College in 1974 and his Ph.D. from the University
of California–Berkeley in 1980. Dr. Staskawicz’s work has contributed greatly to
understanding the molecular interactions between plants and their pathogens. He
was elected to the NAS in 1998 for elucidating the mechanisms of disease resistance, as his lab was the first to clone a bacterial effector gene from a pathogen
and among the first to clone and characterize plant disease-resistance genes. Dr.
Staskawicz’s research focuses on the interaction of the bacteria, Pseudomonas
and Xanthomonas, with Arabidopsis, tomato, and pepper. He has published extensively in this area and is a one of the leading scientists in the world working on
elucidating the molecular basis of plant innate immunity.
Terence Taylor is president and director of the International Council for the Life
Sciences (ICLS). He is responsible for the overall direction of the ICLS and its
programs, which have the goal of enhancing global biosafety and biosecurity.
From 1995 to 2005, he was assistant director of the International Institute for
Strategic Studies (IISS), a leading independent international institute, and president and executive director of its U.S. office (2001 to 2005). He studies international security policy, risk analysis, and scientific and technological developments
and their impact on political and economic stability worldwide. At IISS he was
one of the Institute’s leading experts on issues associated with nuclear, biological,
and chemical weapons and their means of delivery. In his previous appointments,
he has had particular responsibilities for issues affecting public safety and security in relation to biological risks and advances in the life sciences. He was one of
the commissioners to the United Nations (UN) Special Commission on Iraq, for
which he also conducted missions as a chief inspector. He was a research fellow
on the Science Program at the Center for International Security and Cooperation
at Stanford University, where he carried out, among other subjects, studies of the
implications for government and industry of the weapons of mass destruction
treaties and agreements. He has also carried out consultancy work for the International Committee of the Red Cross on the implementation and development of
the laws of armed conflict. He has served as chairman of the World Federation of
Scientists’ Permanent Monitoring Panel on Risk Analysis. He served as a career
officer in the British Army on operations in many parts of the world, including counterterrorist operations and UN peacekeeping. His publications include
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APPENDIX C
monographs, book chapters, and articles for, among others, Stanford University,
the World Economic Forum, Stockholm International Peace Research Institute
(SIPRI), the Crimes of War Project, International Herald Tribune, Wall Street
Journal, the International Defence Review, the Independent (London), Tiempo
(Madrid), the International and Comparative Law Quarterly, the Washington
Quarterly, and other scholarly journals, including unsigned contributions to IISS
publications.
Copyright © National Academy of Sciences. All rights reserved.
Global Infectious Disease Surveillance and Detection: Assessing the Challenges -- Finding Solutions, Workshop Summa
http://www.nap.edu/catalog/11996.html
Copyright © National Academy of Sciences. All rights reserved.
