1. INFLUENZA SURVEILLANCE Julie L Freshwater, MPH PhD Influenza Surveillance Coordinator

2. Objectives 2  Define public health surveillance  List the importance and uses of surveillance data  Identify data quality issues  Discussion to identify strategies to improve data and data quality issues

3. “Ongoing, systematic collection, analysis, interpretation, and dissemination of data regarding a health-related event for use in public health action to reduce morbidity and mortality and to improve health” Centers for disease control and prevention, 2001 PUBLIC HEALTH SURVEILLANCE 3

4. Components of West Virginia’s Influenza Surveillance System 4  Local Health Department (LHD)  Schools  Providers  ILINet Providers (ILINet)  Sentinel Providers  Laboratories (Labs)  Sentinel  Hospital  Commercial  Office of Laboratory Services (OLS)

5. Local Health Departments (LHD) Sentinel Providers (ILINet) Office of Laboratory Services (OLS) Hospital/referral laboratories DIDE CDC Influenza-like Illness (ILI)Laboratory Data Feedback to Stakeholders Influenza Surveillance in West Virginia 5

6. System Objectives 6  Identify earliest case of influenza A in the state  Estimate duration of season  Identify outbreaks  Determine if circulating types of influenza are vaccine-strain

7. Surveillance Data Use 7  Inform the stakeholders by  Graphs  Maps  Newsletters

8. Influenza Data Use 8  Healthcare providers and hospitals  Public health departments  General public  CDC  WHO  FDA  Vaccine manufacturers

9. SURVEILLANCE FOR INFECTIOUS DISEASES 9  Surveillance method  Flexible  Sensitive  Surveillance data  Representative  Timely  Accurate and complete

10. THREATS TO DATA QUALITY 10 1. Lack of representativeness 2. Under-reporting 3. Inconsistent case definitions 4. Poor data quality 5. Lack of timeliness

11. 1. LACK OF REPRESENTATIVENESS 11  Data does not reflect the entire population under surveillance

12. Representativeness of West Virginia Influenza Surveillance Data 2010 12  Local health departments’ data  5 smallest counties data from 90% of providers  5 largest counties data from 29% of providers  ILINet  61% from rural  36% from small town

13. Provider Demographics 13  Family practice (61%)  Emergency Department (16%);  Urgent Care (8%)  Internal Medicine and Pediatrician (5% ea)  Student Health (3%)  Infectious Diseases and Health Department (1% ea)

14. Improving Representativeness of ILINet Data in your region 14  Population of your county?  Demographics?  ILINet providers see a representative sample of the population?  How would you improve representativeness?

15. Improving Representativeness of LHD ILI Data in your region 15  The state now has access to school absentee data, is there another source of data that could be collected at the local level?  Can the method of data collection be improved?

16. 2. UNDERREPORTING 16  Lack of awareness to report  Negative attitude toward reporting  Misconceptions that arise from lack of knowledge or negative attitude

17. Improving Reporting of West Virginia Influenza Surveillance Data 2010 17  Provide frequent feedback  Could lack of knowledge of how data is used be a barrier?  How do you communicate with your providers?

18. 3. INCONSISTENT DEFINITIONS 18  Providers may use clinical criteria that differs from the public health case definition  Case definition may change over time and not all reporters use most current version

19. Case Definition Use in West Virginia Influenza Surveillance Data 2010 19  ILINet Providers  53% use CDC case definition exclusively  Some use multiple case definitions

20. Improving Case Definition Use for ILINet West Virginia Surveillance Data 20  Does your sentinel provider use the CDC case definition exclusively to report ILI?  What strategies have been used in your region to improve the use of the ILI case definition?  What recommendations do you have to improve the use of the ILI case definition by sentinel providers?

21. 4. POOR DATA QUALITY 21  Incorrect information  Missing data elements  Duplicate records  Inconsistent information  Across geographic areas  Across reporters

22. Improving Data Quality for West Virginia Influenza Surveillance Data 22  Is the data complete to ILINet?  Does the sentinel provider send 2 specimens a week to OLS for testing?

23. 5. LACK OF TIMELINESS 23  Disease dependent reasons  Procedure dependent reasons  Time of report submission/processing  Delay in surveillance analysis  Delay in dissemination

24. Timeliness of influenza reporting January through May 2011 in West Virginia 24  LHD  <2 weeks of missing data :36  Reported late <2 times: 34  ILINet  <2 weeks of missing data :12  Reported late <2 times: 17

25. Improving Timeliness for West Virginia Influenza Surveillance Data 25  Issues with timeliness of reporting by sentinel providers?  Issues with timeliness of reporting by your LHD?  Any strategies to improve timeliness?  Recommendations for improving timeliness?

26. Specimens 26  Isolates provide specific information  Compare  Guide  Formulate  Monitor

27. 27 “A robust sentinel provider system is one of the best and most efficient means to staying prepared for novel and seasonal influenza because the combination of surveillance for ILI and laboratory confirmation carries preparedness to the local level. We recognize this may not be feasible in some of the smallest counties, however the track record of success for many counties is readily apparent from the data.”

28. For Discussion 28  List of questions  ILINet reporting data  LHD reporting data  Specimen submissions to OLS  County population data

29. Thanks to 29  Dr. Dee Bixler  Dr. Tegwin Taylor  UNC Center for Public Health Preparedness  Local Health Departments  Sentinel providers and those in the office that compile and report the data  Laboratories  OLS  Grant from the CDC

30. QUESTIONS? 30