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 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 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 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