Assessing the Early Aberration Reporting System's Ability to Locally Detect the 2009 Influenza Pandemic

Hagen Katie S., Fricker Ronald D, Hanni Krista D., Barnes Susan and Michie Kristy
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Hagen Katie S.: U.S. Navy
Fricker Ronald D: Naval Postgraduate School
Hanni Krista D.: Monterey County Health Department
Barnes Susan: Monterey County Health Department
Michie Kristy: Monterey County Health Department

Statistics, Politics and Policy, 2011, vol. 2, issue 1, 30

Abstract: The Early Aberration Reporting System (EARS) is used by some local health departments (LHDs) to monitor emergency room and clinic data for disease outbreaks. Using actual chief complaint data from local public health clinics, we evaluate how EARS—both the baseline system distributed by the CDC and two variants implemented by one LHD—perform at locally detecting the 2009 influenza A H1N1 pandemic. We also compare the EARS methods to a CUSUM-based method. We find that the baseline EARS system performed poorly in comparison to one of the LHD variants and the CUSUM-based method. These results suggest that changes in how syndromes are defined can substantially improve EARS performance. The results also show that incorporating algorithms that use more historical data will improve EARS performance for routine surveillance by local health departments.

Keywords: biosurveillance; syndromic surveillance; H1N1; influenza (search for similar items in EconPapers)
Date: 2011
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DOI: 10.2202/2151-7509.1018

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