Skip directly to site content Skip directly to page options Skip directly to A-Z link Skip directly to A-Z link Skip directly to A-Z link

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.

Main Article

Page created: December 10, 2010
Page updated: December 10, 2010
Page reviewed: December 10, 2010
The conclusions, findings, and opinions expressed by authors contributing to this journal do not necessarily reflect the official position of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
file_external