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Volume 15, Number 4—April 2009

Research

Enhancing Time-Series Detection Algorithms for Automated Biosurveillance

Jerome I. TokarsComments to Author , 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

Table 1

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
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.

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