School-based Syndromic Health Surveillance

1. School-based Syndromic Health Surveillance Southwest Center for Advanced Public Health Practice Tarrant County Public Health Enhanced Influenza Surveillance Proposal Presented by: Tabatha Powell, MPH Doctoral Student Department of Epidemiology University of North Texas Health Sciences Center School of Public Health

2. Public health importance • Detecting flu outbreaks in schools can facilitate the development and implementation of timely public health recommendations to prevent the spread of disease to high risk populations • Burden of flu (CDC report) • Preparing for pandemic flu (HHS K-12 checklist) • Economic impact • Leads to lost days at work/school • Healthcare costs

3. Focusing on youth • Common vehicles for transmitting influenza to other persons in their households, • high-risk groups (e.g., the elderly, young children, and immuno-compromised individuals) • Children biologically more susceptible; naïve immune systems • Highest rates of infection; serious illness and death in children < 2 y.o. • Environment in which children interact daily is conducive to close contact and increased transmission

4. Importance of ILI data Necessary to distinguish increased absences due to other causes; to detect underlying causes of outbreaks Total absenteeism is not necessarily an appropriate proxy or early indicator for flu outbreaks Provides public health with information it can use to focus its limited resources more appropriately More precisely characterize flu and its community impact and help public health leaders marshal limited resources to control its spread

5. Project goals Short-term Process Outcomes Support early detection of flu through development of a school-based health surveillance system Enhance information exchange by developing an online venue (i.e. communication portal) Strengthen the quality of surveillance data

6. Project goals Long-term Impact Outcomes • Focus public health resources in response to early detection of increased ILI and student absenteeism rates • Slow spread of flu; reduce its magnitude and impact • Serve as a model for expansion with similar initiatives in Texas

7. Surveillance enhancements Reporting method Timeliness of data Data specifications Communication tools Public health response

8. System overview

9. Tarrant County Continue recruitment of public schools Recruit school-based health centers Recruit child care centers Lab enhancements Dallas Recruit schools Denton Recruit schools GIS component Proposal

10. Participation Tarrant County More than 500 schools in 16 districts* Seven ISDs participated (by end of May 2008) > 100 schools (February) 100 school nurses (February) Nearly 100 private schools One school participated

11. Each school district has its own “home page.” Though content is typically the same, it’s easy to customize it when desired or necessary.

12. The report form is the “landing page’ users see after they log in. Some fields are pre-filled for ease of completion. Users have said they can complete this form in five minutes or less. The CDC definition of ILI is given.

15. Used CDC’s Framework for Program Evaluation and Updated Guidelines for Evaluating Surveillance Systems Logic model Evaluation matrix Developed by UNT HSC SPH graduate students Methodology Conducted key informant interviews Administered survey to school nurses Focused on measuring system inputs and outputs to assess progress towards meeting process objectives Evaluation of pilot year

16. Logic model

17. Reporting trends in ILI data

18. Popularity of system resources Potential users interested in resources Current users view resources at a frequency less than expected as a result of time constraints

19. Public health response Absenteeism and ILI data used as supplemental data stream to other surveillance data, including chief complaint data from hospital EDs SPSN participating physician practices Laboratory findings Identified 'hot zones' Where increasing levels of absenteeism, ILI, and patients presenting with ILI to ED and local physicians Targeted testing of patients exhibiting ILI in 'hot zones

20. Focusing resources • Anticipated more effective use of antivirals • Ability for identification of cases earlier in the course of illness to meet recommendations for use as prophy in the first 24-48 hrs following onset • Promote vaccination to prevent and reduce likelihood and magnitude of future epidemics

21. Replicability Affordable Royalty-free, open-source portal platform (DotNetNuke) Not time intensive to maintain Some IT knowledge necessary Training resources for DNN

22. Next steps Revisions to report form Enhance functionality Flow data into ESSENCE Include attendance clerks Develop media campaign

23. Future directions • ACIP recognizes the importance of this age group in the spread of flu by recommending universal vaccination children 6mos-18yrs • Potential to be used in outbreak settings due to system’s flexibility • Move towards standardization of flu surveillance data for comparison across jurisdictions

24. Contact information: Tabatha Powell, MPH : tpowell@hsc.unt.edu Dean Lampman, MBA: dflampman@tarrantcounty.com Questions?

25. References Peterson, D et al. An effective school-based influenza surveillance system. Public Health Reports. 1979 Jan-Feb; 94(1): 88-92. Lenaway, D. and A. Ambler. Evaluation of a School-Based Influenza Surveillance System. Public Health Reports. May-June 1995;110: 333-337. Fujii, H. et al. Evaluation of the School Health Surveillance System for Influenza, Tokyo, 1999-200. Japanese Journal of Infectious Disease. 2002; 54: 97-98. Principi, N. et al. Burden of Influenza in Healthy Children and their Households. Arch. Dis. Child. 2004;89:1002-1007. Besculides, M. et al. Evaluation of School Absenteeism Data for Early Outbreak Detection, New York City. BMC Public Health. 2005; 5: 105. Viboud, C. et al. Br J Gen Pract. Risk Factors of Influenza Transmission in Households. 2004 Sep; 54(506): 684-9.