Influenza-like Illness Surveillance at the National Level

1. Influenza-like Illness Surveillance at the National Level Lynnette Brammer, MPH Epidemiology and Prevention Branch Influenza Division National Center for Immunization and Respiratory Diseases Centers for Disease Control and Prevention

2. ILINet — Outpatient Influenza-Like Illness Surveillance Network • National outpatient ILI surveillance piloted in 1982 • CDC run system • Family practice only • Shift to a CDC – state collaborative system began with the 1997-98 season • States are responsible for recruiting and maintaining contact with participating outpatient sites • CDC is responsible for developing and maintaining reporting and data feedback systems • Data are simultaneously available to both CDC and states

3. ILINet — Outpatient Influenza-Like Illness Surveillance Network • Report weekly the total number of patient visits for any reason and the number of patients with ILI by age group (0–4, 5–24, 25–49, 50–64, and >64 years) • ILI definition: fever ≥100oF AND cough and/or sore throat (without a known cause other than influenza) • Can submit respiratory specimens from a subset of ILI patients to their public health laboratory for virologic testing

4. ILINet — Outpatient Influenza-Like Illness Surveillance Network • ~ 3,000 primary care sites enrolled for the 2013-14 influenza season • All 50 states, DC, Puerto Rico, and Virgin Islands participate

5. ILINet — Outpatient Influenza-Like Illness Surveillance Network • Mix of practice types enrolled • Varies by state • System allows enrollment of any practice type that may provide primary care • Family practice, pediatrics, internal medicine, OB/Gyn, emergency medicine, student health, urgent care, and other • For the 2012-13 influenza season collected information on approximately 35 million patient encounters • Estimated coverage: ~5% of primary care/ED visits

6. ILINet — Outpatient Influenza-Like Illness Surveillance Network • Mix of manually compiled data and electronic data • Electronic data are a mix of chief complaint and ICD coded data • Definition used to pull electronic data should match case definition as closely as possible • It should match trend and magnitude of manually collected data • Because of the large volume of data from most electronically reporting sites, we need historical data to include for baseline development

7. ILINet Composition by Practice Type — 2013-14 Season Number of Sites Number of Visits

8. DATA ANALYSIS

9. ILINet Data Analysis - Traditional • Percentage of visits for ILI weighted by state population • National and regional baselines: mean percentage of patient visits for ILI during non-influenza weeks for the previous three seasons plus two standard deviations • A non-influenza week is defined as periods of ≥ 2 consecutive weeks in which each week accounted for less than 2% of the season’s total number of influenza positive tests

10. ILINet – Data Analysis – State Activity Levels • An extension of national and regional baseline development • Each reporting site has its own baseline – site- or practice-type specific • Jurisdiction-level baselines are adjusted each week based on which sites provide data • Weighted sum of the baseline ratios for each contributing provider • Activity level based on number of standard deviations from mean • 1 = less than mean, 10 = > 8 SD

11. ILINet – Data Analysis – State Activity Levels • Allows for direct state-to-state comparison of ILI activity levels • No numbers or percentages that might differ from state reported data

13. ILINet Data Analysis – CBSA Level – Internal use only

14. ILINet Data Sharing • All data are available to state influenza surveillance coordinators • National and regional aggregate visit and ILI numbers and weighted and unweighted percentages are available on CDC Web site using FluView and FluView Interactive • State ILI activity levels are also available • Both data downloads and graphics are available

15. ILINet — Weaknesses • A lot of work for a lot of people • Correct data interpretation is not straightforward • Large volume sites may drown out signals from smaller sites

16. ILINet — Strengths • Allows early detection of relatively mild illness • Most helpful system in early stage of the 2009 pandemic • Broad geographic coverage • Urban and rural areas • Collaborative system • Shared workload • Shared monitoring • Linked to virologic data • Flexible reporting • Network of primary care providers with interest in respiratory illness and with contacts to public health • Facilitates early event reporting by the astute clinician