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5 5IntroSurveillance Slides

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Introduction to Public Health Surveillance

 

Goals 



 

Define surveillance, explain surveillance systems Describe basic surveillance techniques by person, place, time Touch on importance of standardization Provide overview of how to present surveillance data

 

Surveillance 



For persons who need to carry out surveillance activities but have little prior experience or training  Also helpful for for people who would lik like e to better understand the process and reasoning behind surveillance methods and interpretation

 

What Is Surveillance? 

Centers for Disease Control and Prevention (CDC): epidemiologic surveillance is ―ongoing systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice, closely integrated with the timely dissemination of these data to those who need to know.‖  

 

Why Is Surveillance Important? 



Collecting data is merely one step Critical goal is to control and/or prevent diseases 



 Any data collected must be organized and carefully examined  Any results results need to be communicate communicated d to public health and medical communities

 

Why Is Surveillance Important? 

 Vital to communicate results 



During potential outbreak so public health and medical communities can help with disease prevention and control efforts During non-outbreak times to provide information about baseline levels of disease 

Baseline provides information to public health officials monitoring health at community level, serves as reference reference in future outbreaks

 

Surveillance Systems  

Classified as passive or active Passive Passiv e surveillance: local and state health departments rely on health care providers or laboratoriess to report cases of disease laboratorie 





Primary advantage is efficiency: simple and requires relatively few resources Disadvantage Disadvantag e is possibility of incomplete data due to underreporting Majority of public health surveillance systems are passive

 

Surveillance Systems 

 Active surveillance: surveillance: health department contacts health care providers or laboratories requesting information about conditions or diseases to identify possible cases 



Requires Req uires more resources than passive surveillance Useful when important to identify all cases 

Example: between 2002 and 2005, active surveillance used to detect adverse events associated with smallpox vaccine. (2)

 

Why Is Surveillance Important? 

Surveillance information has many uses: 















Monitoring disease trends Describing natural history of diseases Identifying epidemics epidemics or new syndromes Monitoring changes in infectious agents Identifying areas for research Evaluating hypotheses Planning public health policy Evaluating public health policy/interventions

 

Why Is Surveillance Important? 

Examples of uses of surveillance data: 









Evaluating impact of national vaccination campaigns Identifying AIDS when unknown syndrome Estimating impact of AIDS on US health care system in 1990s (using mathematical models based on surveillance data) Identifying outbreaks outbreaks of rubella and congenital rubella among Amish and Mennonite communities in 6 states in 1990 and 1991 (3) Monitoring Monitori ngfor obesity, obesity , physical activity, activity, indicators chronic diseases

other

 

How to Conduct Surveillance 





Surveillance data allow description and comparison of patterns of disease by person, place, and time Several ways to describe and compare patterns, from straightf straightforward orward presentations to statistically complex analyses Will concentrate on simple techniques

 

How to Conduct Surveillance: Person 

When available, demographic characteristics such as gender, age, race/ethnicity, occupation, education level, socio-economic status, sexual orientation, immunization status can reveal disease trends 

Example: looking at Streptoco Streptococcus ccus pneumoniae , a common cause of communitycommunity-acquired acquired pneumonia and bacterial meningitis, examining distribution of cases by race provides important information about burden of disease in different populations

 

How to Conduct Surveillance: Person – Person  – Numbers  Numbers and Rates 

Table 1 shows data collected on Streptococcus pneumoniae from CDC Emerging Infections Program Network, a surveillance program that collects data from multiple counties in 10 US states (4)

 

How to Conduct Surveillance: Person – Person  – Numbers  Numbers and Rates 



Data show majority of cases reported among whites Can draw only limited conclusions because race not recorded for 684 cases (15%)





Shows only number   rate of reported cases, not  of Total number of individuals by race needed to determine if there is a disproportionate burden of disease among races

 

How to Conduct Surveillance: Person – Person  – Numbers  Numbers and Rates 

Table 2 sh shows ows sa same me data with 2006 population estimates of total number of persons in each racial category used to calculate disease rates (4)

 

How to Conduct Surveillance: Person – Person  – Numbers  Numbers and Rates 



While Table 1 showed that whites had the highest number  of  of cases, Table 2 indicates that the rate of disease was highest among blacks Using rates, stratifying by race provides information about disease burden in different populations that would not be apparent from total case numbers

 

More on Rates 



  Rates —A

rrate ate is ―an expression of the the frequency with which an event occurs in a

defined population‖ Using rates rather than raw numbers is essential to compare different classes of persons or populations at differen differentt times or

places. (5) Rate = number of events in a specified period average aver age population during the period

 

How to Conduct Surveillance: Place 



Best to characterize cases by place of exposure rather than by place at which cases reported The two may differ and place of exposure is more relevant to epidemiology of a disease 



Example: travelers on a cruise ship exposed to a disease just prior to disembarking but become symptomatic and are diagnosed after return to various home locations Example: person exposed to disease in small rural town but referred to tertiary care center 100 miles away where disease is diagnosed and reported

 

How to Conduct Surveillance: Place – Place  – Presenting  Presenting Data 



Data by geographic location can be presented in a table  Also helpful to use maps to facilit facilitate ate recognition of spatial associations in data 



See FOCUS   Volume 5, Issue 2: Mapping for Surveillance and Outbreak Investigation for discussion of maps and visual presentation of information

Inferential analysis can also be done using Inferential multilevel modeling, other statistical methods

 

How to Conduct Surveillance: Place – Place  – Modeling  Modeling Resou Resources rces 



Modeling of surveillance data by place is beyond scope of this issue Resourcess for further information: Resource 



Centers for Disease Control and Prevent Prevention. ion. Resources Resour ces for creating public health maps. http://www.cdc.gov/epiinfo/maps.htm.. Updated http://www.cdc.gov/epiinfo/maps.htm  August 14, 14, 2008. Accessed August August 22, 2008. 2008. Clarke KC, McLafferty SL, Tempalski BJ. On epidemiology and geographic information systems: A review and discussion of future directions. Emerg Infect Dis . 1996; 2(2):85-92.

 

How to Conduct Surveillance: Place – Place  – Spot  Spot Maps 





Spot maps: maps on which a dot or symbol marks a case of disease Made by indicating exposure locations of reported cases of disease on hard copy map with pins or colored pen Or with geographic information systems (GIS) 





Computer designed manipulating, analyzing, programs and displaying datafor in astoring, geographic context  Very  V ery useful for mapping surv surveillance eillance data by place Epi Map (part of Epi Info™) can be downloaded download ed for free at http://www.cdc.gov/epiinfo http://www.cdc.gov/epiinfo to  to assist with map making

 

How to Conduct Surveillance: Place – Place  – Spot  Spot Maps 



Example: spot map used to show geographic spread of cases in 1995 outbreak of toxoplasmosis thought to be associated with a municipal water system in British Columbia, Canada (5)

Spot maps show geographic distribution of cases but not population size at each location, so should not be used to assess disease risk

 

How to Conduct Surveillance: Time 



Compare number of cases reported in time period of interest (weeks, months, years) to number of cases reported during similar historical period Usually a delay (sometimes months to years) between disease onset and date when disease is reported, so preferable to use date of onset, if available, rather than date of report

 

How to Conduct Surveillance: Time – Time  – Line  Line Graphs 

Especially helpful for examining data not likely to have much short term variation 



Example: there is limited variation in number of  AIDS cases reported reported each mont month h

Provide valuable qualitative information; disease outbreaks often obvious from visual inspection of data, may not require a quantitative analysis

 

How to Conduct Surveillance: Time – Time  – Line  Line Graphs 



Example of line graph using fabricated data: reported cases of Salmonella typhimurium  for  for 2-year time intervals from 1974 to 2002 Spike in 1994 indicating outbreak of S. typhimurium obvious without quantitative analysis

 

How to Conduct Surveillance: Time – Time  – Incidence  Incidence Rates  

May use line graph to plot incidence rates Incidence rate is number of new cases that occur during a specified interval in a population at risk for developing the time disease 





Number of new cases may be used as a proxy for overall disease occurrence  Value  V alue ofte often n multip multiplied lied by 1,00 1,000 0 or 100,000 to impro improve ve interpretability

Reporting incidence rates rather than numbers Reporting particularly important if population has changed in size or characteristics characteristics 

Example: addition of towns to a surveillance region has increased population size, or influx of migrant workers has significantly changed the demographics

 

Standardization  

Rate made up of numerator and denominator Surveillance data often numerator data (number of cases reported in time period) 



Utility of these raw numbers is limited because do not take into account size of population or distribution of demographic factors such as age or gender

Rates allow more meaningful comparisons over time within a population, among subpopulations, or between populations 

Rates take into account size of the population and time period involved (3)

 

Standardization  



Crude rates often calculated using surveillance data Number of events of interest (such as reported cases of disease) for a specific period of time for the entire population Only appropriate to compare crude rates if populations are similar with respect to factors related to disease interest, such as age, gender, Example:of would be inappropriate to compare raterace of 

prostate cancer in population with high proportion of elderly men to rate in another population with mostly mo stly young men, since risk of prostate cancer increases with age

 

Standardization 

Standardization used to remove effects of differences in confounding variables such as age when comparing or more Results in two adjusted rates populations 



Is particularly useful when comparing rates in different populationss (e.g., compar population comparing ing state data to national data) when comparison of crude rates may be misleading if populations differ on key variables



Most common technique uses weighted average rates specific to potential confounding variables, based on specified distribution of the variables (5)

 

Data Presentation 



Surveillance data must be presented in way that is easy to understand and interpret Many ways to display surveillance data: (3) 



Line graphs for displaying data by time Maps for presenting data in i n geographic context







Graphical such as histograms, frequency polygons, displays box plots, scatter diagrams, bar charts, pie charts, or stem-and-leaf displays Spot or chloropleth maps Single/multivariable tables

 

Data Presentation 





 

The choice of a particular graph or table depends on type of data, but presentation should be simple and easy to follow Should provide all information necessary to interpret the figure without referring to text Include title (when describes subject or disease,concise time, place (that when relevant) Define any abbreviations or symbols Note any data exclusions (3)

 

Data Presentation 

 Additional display guidelines for tables and graphs

 

Conclusion 

Surveillance is valuable epidemiologic



tool that can serve many purposes When surveillance data is collected, analyzed, interpreted, reported appropriately appropriately, , the these se data can provide important information about disease patterns to inform public health practice and policy

 

References 1. 2.

3.

Thacker SB, Berkelman RL. Public health surveillance in the United States. Epidemiol Rev . 1988;10:164-190. Thomas TN, Reef S, Neff L, Sniadack MM, Mootrey GT.. A review of the smallpox vaccine adverse GT events active surveillance system. Clin Infect Dis . 2008;46 Suppl 3:S212-S220. Janes GR, Hutwanger L, Cates Jr W, Stroup DF, Williamson GD GD.. Descriptive Epidemiology:  Analyzing and Interpreting Interpreting Surveillance Surveillance Data. In: Teutsch SM, Churchill RE, eds. Principles and Practice of Public Health Surveillance . New York, NY: Oxford University Press, inc, 2000:112-167.

 

References 4.

Centers for Disease Control and Prevention. Prevention. Active Bacterial Core Surveillance Report (ABCs), Emerging Infections Program Network, Streptococcus Streptoco ccus pneumoniae , 2006. http://www.cdc.gov/ncidod/dbmd/abcs/survreports  /spneu06.pdf2007  /spneu06.p df2007.. Published 2007 2007. Accessed  August 21, 21, 2008. Epidemiology . 3rd ed. 5. Last JM, ed.  A Dictionary of Epidemiology  New York, NY: Oxford University Press, Inc, 1995. 6. Eng SB, Werker DH, King AS, et al. Computergenerated generat ed dot maps as an epidemiologic tool: Investigating Investiga ting an outbreak of toxoplasmosis. Emerg Infect Dis. 1999;5(6):815-819. Dis. 1999;5(6):815-819.

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