Table 1

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

Jerome I. Tokars

, Howard Burkom, Jian Xing, Roseanne English, Steven Bloom, Kenneth Cox, and Julie A. Pavlin

Author affiliations: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (J.I. Tokars, J. Xing, R. English); The Johns Hopkins University, Baltimore, Maryland, USA (H. Burkom); Science Applications Incorporated, San Diego, California, USA (S. Bloom); Department of Defense, Washington, DC, USA (K. Cox); Armed Forces Research Institute of Medical Sciences, Bangkok, Thailand (J.A. Pavlin)

Main Article

Distribution of hospital emergency department visits and mean count per day, by syndrome and dataset, for selected BioSense data used in algorithm modification study*

Syndrome	Department of Defense clinic diagnosis		Hospital emergency department chief complaint
Syndrome	Mean count/d	% Facility–syndrome days	Mean count/d	% Facility–syndrome days
Botulism-like	2.5	3.8	0.9	1.8
Fever	4.4	10.1	6.3	14.3
Gastrointestinal	8.9	13.7	14.5	14.7
Hemorrhagic	2.2	5.7	2.6	13.6
Localized cutaneous lesion	3.0	10.8	2.6	13.2
Lymphadenitits	1.1	4.8	NA	0†
Neurologic	3.6	10.6	5.2	14.4
Rash	4.3	11.2	2.2	13.1
Respiratory	26.0	16.0	20.0	14.7
Severe injury and death	2.2	2.6	NA	0†
Specific infection	3.2	10.7	NA‡	0‡
All	7.7	100	7.8	100

*NA, not applicable.
†Facilities were not included because none had mean counts >0.5 for syndromes.
‡Chief complaint data are not assigned to this syndrome.

Main Article

Page created: December 10, 2010

Page updated: December 10, 2010

Page reviewed: December 10, 2010

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