Henry R. Rolka, R.N., M.P.S., M.S. Centers for Disease Control and Prevention February 19, 2004

1. Overview of ‘Syndromic Surveillance’presented as background to Multiple Data Source Issue forDIMACS Working Group on Adverse Event/Disease Reporting, Surveillance, and Analysis II Henry R. Rolka, R.N., M.P.S., M.S. Centers for Disease Control and Prevention February 19, 2004

2. New data types and functional objectives have largely expanded the scope of public health surveillance

3. New surveillance challenges and opportunities are growing in complexity

4. Outline of Presentation • Background and context for appreciation of new complexities. • Major themes and issues. • Focus for this meeting • Summary and discussion.

5. Public Health Surveillance “Ongoing systematic collection, analysis, and interpretation of outcome-specific data for use in the planning, implementation, and evaluation of public health practice.” *Stephen Thacker, CDC

6. Surveillance System  Data Collection  Analysis  Dissemination

7. Surveillance System Components Population of interest which generates events Public health response Interpretation for associations, trends, unusual patterns, signals Measurement and recording Analytical applications Transactional data • Data Management • Quality checks • Editing Data preprocessing for a specific purpose (‘views’, ‘data marts’)

8. Conceptual Taxonomy Public Health Surveillance Medical Utilization and Adverse Events Disease Drug Vaccine Other Products/Services Traditional ‘Syndromic’ Infectious Disease Other Birth defect Injuries Etc.

9. NETSS • Weekly data regarding cases of nationally notifiable diseases. • Core surveillance data: date, county, age, sex, and race/ethnicity. • Some disease-specific epidemiological information. • Transmitted electronically by the states and territories to CDC each week.

10. Figure 1 published weekly in the MMWR

11. Syndromic Surveillance “Monitoring frequency of illnesses with a specified set of clinical features in a given population, without regard to the diagnoses.” Arthur Reingold, UC Berkeley

12. Surveillance System Components Epidemiological decisions Data collection and preprocessing Data View Reporting or recording anomaly Application of statistical algorithms Data processing error A Statistical aberration due to natural variability ‘Something unusual’ noted in data etc. True increase in disease B Requires information from other data sources Naturally occurring outbreak Deliberate exposure event C

13. Non-traditional Data Types for Public Health Surveillance • Pre-diagnostic/chief complaint (text data) • Over-the-counter sales transactions • Drug store • Grocery store • 911-emergency calls • Ambulance dispatch data • Absenteeism data • ED discharge summaries • Managed care patient encounter data • Prescription/pharmaceuticals

14. Potential Syndromic Surveillance Data Sources Pharmaceutical Sales • Day 1 - feels fine • Day 2 - headaches, • Day 3 - develops cough, • Day 4 – • Day 5 – Worsens, • Day 6 - • Day 7 - • Day 8 - Nurse’s Hotline Managed Care Org Absenteeism Ambulance Dispatch (EMS) ED Logs Traditional Surveillance *Farzad Mostashari, NYC DoH

15. Messy Data • Noisy, periodic (weekly, seasonally) • Multiple data streams • Duplicate records • Syndromic coding not standardized • Data quality • Means for evaluation not well developed

16. Bio-ALIRT • “Bio-Event Advanced Leading Indicator Recognition Technology” • Program to develop technology for early detection of a covert biological attack • Defense Advanced Research Projects Agency (DARPA) • Began in fy 2001

17. LATER DETECTION EARLY DETECTION GOLD STANDARDS NON TRADITIONAL MEDICAL INTELLIGENCE BIOSENSORS Vets OTC Pharm Tests ordered Test Results Test Results Zoos Absenteeism Complaints Diagnosis Utilities ANIMALS HUMAN BEHAVIORS NON TRADITIONAL USES CLINICAL DATA Sentinel MD Agribusiness Poison Centers Influenza isolates Environmental Coughs 911 Calls Pollen counts Investi- gations Web Queries Medical Examiner Humidity Traffic EMS Runs Survey Temperature Nurse Calls Public Transport Wind Speed/ direct. Limited Utility Some Potential Promising ER Visits Cafeteria Prescriptions Allergy Index Video Surv Radiograph Reports Pollution Newsgroup Biosurveillance Data Space

18. BioSense (under development) • Complementary project to President’s initiatives BioWatch and BioShield. • Focuses on disease symptoms related to syndromic categories (BT agents) • Data source examples: • Patient encounter (ICD9, outpatient) • OTC sales of home health remedies • Lab tests ordered • Nurse call line

19. CDC – BioSense Surveillance for BT Non-traditional data Early detection Evaluation of algorithms Privacy protection DARPA – BioAlirt Surveillance for BT Non-traditional data Early detection Evaluation of algorithms Privacy protection Common Interests/Challenges

20. Themes (system) • Local vs. Regional vs. National vs. Global focus • Interoperability / Transportability • Interdisciplinary science and technologies • Culturalism • Language • Social networks • Case/Adverse Event definitions • Information/knowledge management • Leadership

21. Themes (functionality) • Timeliness for response potential • Data quality factors • System evaluation • Data access • Standards • Signal detection thresholds • Analytic methodologies

22. Analytic Obstacles/Opportunities • ‘Opportunistic’ data • ‘Syndromes’ • Empirical inductive inference • Evaluation of utility and public health value • Multiple data streams in time • Multivariate time series ( uncharacterized transfer functions) • Time alignment • Differential quality