Integrating a commuting model with the Bayesian aerosol release detector

Aurel Cami, Garrick L. Wallstrom, William R. Hogan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The Bayesian Aerosol Release Detector (BARD) is a biosurveillance system for detecting and characterizing disease outbreaks caused by aerosol releases of anthrax. A major challenge in modeling a population's exposure to aerosol anthrax is to accurately estimate the exposure level of each individual. In part, this challenge stems from the fact that the only spatial information routinely contained in the biosurveillance databases is the residential administrative unit (e.g., the home zip code of each case). To deal with this problem, nearly all anthrax biosurveillance systems, including BARD, assume that exposure to anthrax would occur at one's residential unit-a limiting assumption. We propose a refined version of BARD, called BARD-C, which incorporates the effect of commuting on a worker's exposure. We also present an experimental study to compare the performances of BARD and BARD-C on semi-synthetic outbreaks generated with an algorithm that also accounts for commuting.

Original languageEnglish (US)
Title of host publicationBiosurveillance and Biosecurity - International Workshop, BioSecure 2008, Proceedings
Pages85-96
Number of pages12
DOIs
StatePublished - Dec 1 2008
EventInternational Workshop on Biosurveillance and Biosecurity, BioSecure 2008 - Raleigh, NC, United States
Duration: Dec 2 2008Dec 2 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5354 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Workshop on Biosurveillance and Biosecurity, BioSecure 2008
CountryUnited States
CityRaleigh, NC
Period12/2/0812/2/08

Keywords

  • Anthrax
  • BARD
  • Biosurveillance
  • Commuting

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Cami, A., Wallstrom, G. L., & Hogan, W. R. (2008). Integrating a commuting model with the Bayesian aerosol release detector. In Biosurveillance and Biosecurity - International Workshop, BioSecure 2008, Proceedings (pp. 85-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5354 LNBI). https://doi.org/10.1007/978-3-540-89746-0_9