Bioterrorism event detection based on the Markov switching model: A simulated anthrax outbreak study

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

The threat of infectious disease outbreaks and bioterrorism attacks has stimulated the development of syndromic surveillance systems, which focus on using pre-diagnostic data such as emergency department chief complaints and over-the-counter (OTC) drug sales to detect bioterrorism events in a timely manner. A key function of syndromic surveillance systems is detecting possible bioterrorism events from time series data. In this paper, we propose a novel temporal outbreak detection method based on the Markov switching model, a special case of hidden Markov models. The model is motivated to address several computational problems with existing detection schemes concerning the inconsistency in parameter estimation and the resulting undesired detection performance. Preliminary evaluation using simulated outbreaks injected on authentic time series shows that our method outperforms benchmark methods in terms of outbreak detection speed and detection sensitivity at given levels of false alarm rates.

Original languageEnglish (US)
Pages76-81
Number of pages6
DOIs
StatePublished - Sep 22 2008
EventIEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008 - Taipei, Taiwan, Province of China
Duration: Jun 17 2008Jun 20 2008

Other

OtherIEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008
CountryTaiwan, Province of China
CityTaipei
Period6/17/086/20/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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    Lu, H. M., Zeng, D., & Chen, H. (2008). Bioterrorism event detection based on the Markov switching model: A simulated anthrax outbreak study. 76-81. Paper presented at IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008, Taipei, Taiwan, Province of China. https://doi.org/10.1109/ISI.2008.4565033