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Texas ILINet Structure and Operation 2002-2008 86 th Annual Texas Public Health Association Conference April 21-23, 2010 South Padre Island, Texas Gary Heseltine MD MPH Infectious Disease Control Unit Chronic Illnesses Demand Chronic Attention

Texas ILINet Structure and Operation 2002-2008 86 th Annual Texas Public Health Association Conference April 21-23, 2010 South Padre Island, Texas Gary

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Texas ILINet Structure and Operation 2002-2008

86th Annual Texas Public Health Association ConferenceApril 21-23, 2010

South Padre Island, Texas

Gary Heseltine MD MPHInfectious Disease Control Unit

Chronic Illnesses Demand Chronic Attention

Overview

• What is ILINet• What is the structure of ILINet– Where does the data come from– Who is represented

• How does ILINet operate– Data handling– Stability of operation

• Possible Improvements to ILINet

Influenza Like Illness (ILI) Net• CDC hosted syndromic reporting system – Fever > 100o F and cough or sore throat

• Clinicians report weekly– Total number patient visits– Total number of patients diagnosed with ILI• Cases divided into 4 age strata

• Statewide weekly ILI index– Combine data from all clinicians

ILIindex= total ILI patients/total patient visits

Texas ILI Index: What Does It Mean?

ILINet Evolution

Year Reporters ILI Patients Total Visits Counties Report/County

2002 13 1,237 79,852 9 1.44

2003 44 8,232 184,848 31 1.42

2004 69 18,244 517,845 33 2.09

2005 101 24,020 696,806 42 2.40

2006 111 39,607 1,018,809 52 2.13

2007 123 41,963 1,018,790 61 2.02

2008 124 34,335 1,041,898 58 2.14

Total 167,638 4,558,848

Reporters

Total Number of Weekly Submissions by Reporter 2002-2008

Weighting

8

Tuning Surveillance Levels

Weightcounty

Weightblock

Data Viewcounty

Data Viewblock

ILINet Data: Two Issues

1. ILINet data reported to the state does not reflect county populations– Weight county contributions to reflect underlying

population proportion– Use sampling index to guide resource allocation and

recruiting for ILINet to obtain proportionality

2. Sampling method itself: non-probability– Clinicians (reporters) are volunteers- bias– Convenience sample - bias– Use a probability sample to correct for ILINet sampling

bias before submission to the state