2. Federal Public Health Surveillance Session 4, Part 2

3. Learning Objectives Session 4, Part 2 List federal public health surveillance systems relevant to epidemiology programs Discuss the major components of surveillance data analysis

4. Overview Session 4, Part 2 Role of the CDC in public health surveillance Examples of federal surveillance systems Basics of surveillance data analysis

5. Role of CDC in Public Health Surveillance

6. CDC’s Role in Surveillance Supports the states –Facilitates development of definitions, recommendations, and guidelines –Provides training and consultation –Distributes and oversees funding Receives, collates, analyzes, and reports data Suggests changes to be considered in public health surveillance activities Reports to the World Health Organization (WHO) as required (e.g. influenza, measles, etc.)

7. Provisional cases of selected notifiable diseases, United States, weeks ending Dec 3, 2011, and Dec 4 2010 (48th week) CDC Surveillance Data Reporting

8. Percentage* distribution of gestational ages at time of abortion, by age of women --- selected states, United States, 2008 * Based on the total number of abortions reported with known weeks of gestation. Source: CDC. Abortion Surveillance, United States – 2008. http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6015a1.htm?s_cid=ss601451_w http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6015a1.htm?s_cid=ss601451_w

9. Federal Data Sources Surveillance systems collect data on infectious and non-infectious conditions such as: –Foodborne Diseases Active Surveillance Network (FoodNet) –National West Nile Virus Surveillance System (ArboNet) –Waterborne-Disease Outbreak Surveillance System –Influenza Sentinel Physicians Surveillance Network

10. Federal Surveillance Resources CDC Morbidity and Mortality Weekly Report (MMWR) CDC Division of Preparedness and Emerging Infections CDC Office of Surveillance, Epidemiology, and Laboratory Services http://www.cdc.gov

11. Council of State and Territorial Epidemiologists (CSTE) Collaborates with CDC to recommend changes in surveillance, including what should be reported / published in MMWR Develops case definitions Develops reporting procedures http://www.cste.org

12. Examples

13. Example: ArboNet A cooperative surveillance system maintained by CDC and 57 state and local health departments Detects and reports the occurrence of domestic arboviruses

14. Arboviruses Cache Valley California serogroup [unspecified] Chikungunya Colorado tick fever Dengue Eastern equine encephalitis Jamestown Canyon Japanese encephalitis LaCrosse Powassan St Louis encephalitis Venezuelan equine encephalitis Western equine encephalitis West Nile

15. ArboNet: Human Data Demographics –Age, sex, county of residence Clinical –Date of onset –Type of arbovirus –Syndrome (encephalitis, meningitis, fever) Hospitalization Outcome Medical risk factors

16. Example: Dengue in Florida, 2011

17. ArboNet: Non-human Data Routine blood donor screening results Veterinary (equine and other animals) Avian Mosquito Sentinel chickens

18. ArboNet: Surveillance Issues “Real-time” reporting –Novel occurrence of West Nile virus –Web-based reporting (states) –Still relies on paper-based reporting (local) Incorporates ecologic data NEDSS integrated

19. U.S. Influenza Surveillance 1.Viral strain surveillance –WHO and National Respiratory and Enteric Virus Surveillance System 2.Outpatient illness surveillance –ILINet 3.Mortality surveillance –22 Cities Mortality Reporting System –Influenza-associated Pediatric Mortality Surveillance System 4.Hospitalization surveillance –FluSurv-NET 5.Summary of geographic spread –State and Territorial Epidemiologists Reports

20. Influenza-like Illness (ILI) Case Definition Fever of 100 degrees Fahrenheit or higher AND Cough and/or sore throat

21. Sentinel Influenza Surveillance Source: http://www.cdc.gov/flu/weekly/ 40 (2008)40 (2009)40 (2010)40 (2011) Late peak Pandemic

22. Basics of Surveillance Data Analysis

23. Considerations Surveillance data describes patterns of disease or injury Know the inherent strengths and weaknesses of a data set Examine data from broad to narrow

24. Rely on Computers to: Generate descriptive statistics –Tables of frequencies, proportions, rates –Graphs (bar or line) of proportions, rates –Maps of census tracts, counties, districts Aggregate or stratify rates –State versus county –Multiple weeks or months or years –Entire population versus age, gender, or race specific

25. Tuberculosis Cases: United States 1992 - 2010 Source: MMWR March 25, 2011 / 60(11);333-337 Trends in Tuberculosis: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6011a2.htmhttp://www.cdc.gov/mmwr/preview/mmwrhtml/mm6011a2.htm

26. Rely on Public Health Professionals to: Contact health care providers and laboratories to obtain missing data Interpret laboratory tests Make judgments about epidemiological linkages Identify or correct mistakes in data entry Determine if epidemics are in progress

27. Descriptive Epidemiology Person –What are the patterns among different populations? Place –What are the patterns in different geographic locations? Time –What are the patterns at different times? Numbers –Aggregate numbers reported Ratios –Proportions Rates

28. Ratios Definition –A ratio is any fraction obtained by dividing one quantity by another; the numerator and denominator are distinct quantities, and neither is a subset of the other. Ratio examples –Odds –Rates –Proportions (special case)

29. Rates Measures the frequency of an event over a period of time Numerator –e.g., disease frequency for a period of time Denominator –e.g., population size

30. Raw Numbers versus Rates Source: MMWR March 25, 2011 / 60(11);333-337 Trends in Tuberculosis: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6011a2.htmhttp://www.cdc.gov/mmwr/preview/mmwrhtml/mm6011a2.htm

31. Why Use Rates? Rates provide frequency measures within the context of the population. Raw Surveillance Data Total Population Crude RateX 10 4 City A101,000.01100 per 10,000 City B101,000,000.00001.1 per 10,000

32. Crude versus Specific Rates Crude Rate: Rate calculated for the total population Specific Rate: Rate calculated for a sub-set of the population (e.g., race, gender, age)

33. Sample Analyses 1.Graph of HIV cases over time (by year) –Raw data –Rates 2.Maps of Salmonella rates by county: North Carolina, 2000 –Raw Data versus Rates –Choropleth

34. Number of HIV cases among IDUs and rate of IDU cases among all HIV cases, Estonia, 2000-2007 Source: EpiNorth.org. Kutsar K, Epshtein J. HIV infection Epidemiology in Estonia in 2000-2009. EpiNorth 2009; 10: 180-6. Rate per 100 HIV Cases Number of Cases among IDU Year

35. Raw Data Map North Carolina Salmonella Cases by County: 2000 Source: NC Communicable Disease Data by county for 2000, Communicable Disease Branch, Epidemiology Section, North Carolina Division of Public Health

36. Choropleth Map North Carolina Salmonella Cases by County: 2000 Source: NC Communicable Disease Data by county for 2000, Communicable Disease Branch, Epidemiology Section, North Carolina Division of Public Health

37. Choropleth Map North Carolina Salmonella Rates by County: 2000 Rate numerators: NC Communicable Disease Data for 2000 Rate denominators: U.S. Census population data, by county, for 2000

38. Raw Data Rates

39. Data Interpretation: Considerations Underreporting Inconsistent case definitions Has reporting protocol changed? Has the case definition changed? Have new providers or geographic regions entered the surveillance system? Has a new intervention (e.g., screening or vaccine) been introduced?

40. Example: Change in Case Definition

41. Summary Federal and state or local surveillance –Collaborative, reciprocal pathway for data collection and reporting –Data collected is used for the practice of public health Analysis and interpretation of surveillance data –Graph rates versus raw data –Investigate broad, total population rates prior to specific rates

42. References and Resources Disease Maps 2011 [Web page]. US Geological Survey. Available at: http://diseasemaps.usgs.gov/. Accessed March 1, 2012. http://diseasemaps.usgs.gov/ Epidemiology Program Office [Web page]. Centers for Disease Control and Prevention. Available at: http://www.cdc.gov/epo/. Accessed March 1, 2012.http://www.cdc.gov/epo/ Reportable Communicable Diseases – North Carolina. Raleigh: General Communicable Disease Control Branch, Epidemiology Section, Division of Public Health, North Carolina Department of Health and Human Services. NC Communicable Disease Reports. Available at: http://epi.publichealth.nc.gov/cd/figures.html#cds Accessed March 1, 2012. http://epi.publichealth.nc.gov/cd/figures.html#cds Klein R, Schoenborn C. Age Adjustment Using the 2000 Projected U.S. Population. National Center for Health Statistics / Centers for Disease Control and Prevention; January 2001. Healthy People 2010 Statistical Notes: No. 20. Available at: http://www.cdc.gov/nchs/data/statnt/statnt20.pdf. Accessed March 1, 2012. http://www.cdc.gov/nchs/data/statnt/statnt20.pdf

43. References and Resources Last JM. A Dictionary of Epidemiology. 2nd ed. New York, NY: Oxford University Press; 1988. Teutsch S, Churchill R. Principles and Practice of Public Health Surveillance. New York, NY: Oxford University Press; 1994. Background: West Nile Virus [Web page]. US Geological Survey; October 3, 2001. Available at: http://diseasemaps.usgs.gov/wnv_background.html. Accessed March 1, 2012.http://diseasemaps.usgs.gov/wnv_background.html CDC Morbidity and Mortality Weekly Report (MMWR), http://www.cdc.gov/mmwr. http://www.cdc.gov/mmwr CDC Division of Preparedness and Emerging Infections, http://www.cdc.gov/ncezid/dpei/. http://www.cdc.gov/ncezid/dpei/ CDC Office of Surveillance, Epidemiology, and Laboratory Services, http://www.cdc.gov/osels/. http://www.cdc.gov/osels/ Council of State and Territorial Epidemiologists, http://www.cste.org.http://www.cste.org