Assessing the Early Aberration Reporting System's Ability to Locally Detect the 2009 Influenza Pandemic
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Authors
Hagen, Katie S.
Fricker, Ronald D. Jr.
Hanni, Krista D.
Michie, Kristy
Barnes, Susan
Subjects
biosurveillance, syndromic surveillance, H1N1, influenza
Advisors
Date of Issue
2011
Date
2011
Publisher
Language
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.
Type
Article
Description
Statistics, Politics, and Policy, 2, issue 1, article 1.
The article of record as published may be found at http://dx.doi.org/10.2202/2151-7509.1018
The article of record as published may be found at http://dx.doi.org/10.2202/2151-7509.1018
Series/Report No
Department
Operations Research
Organization
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NPS Report Number
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Funding
Format
Citation
Hagen, K.S., R.D. Fricker, Jr., K. Hanni, S. Barnes, and K. Michie (2011). Assessing the Early Aberration Reporting System's Ability to Locally Detect the 2009 Influenza Pandemic, Statistics, Politics, and Policy, 2, issue 1, article 1.
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.