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A Temporal Extension of the Bayesian Aerosol Release Detector

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Biosurveillance and Biosecurity (BioSecure 2008)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 5354))

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Abstract

Early detection of bio-terrorist attacks is an important problem in public health surveillance. In this paper, we focus on the detection and characterization of outdoor aerosol releases of Bacillus anthracis. Recent research has shown promising results of early detection using Bayesian inference from syndromic data in conjunction with meteorological and geographical data [1]. Here we propose an extension of this algorithm that models multiple days of syndromic data to better exploit the temporal characteristics of anthrax outbreaks. Motivations, mechanism and evaluation of our proposed algorithm are described and discussed. An improvement is shown in timeliness of detection on simulated outdoor aerosol Bacillus anthracis releases.

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References

  1. Hogan, W.R., et al.: The Bayesian aerosol release detector: an algorithm for detecting and characterizing outbreaks caused by an atmospheric release of Bacillus anthracis. Statistics in Medicine 26(29), 5225–5252 (2007)

    Article  MathSciNet  Google Scholar 

  2. Kaufmann, A.F., Meltzer, M.I., Schmid, G.P.: The economic impact of a bioterrorist attack: are prevention and postattack intervention programs justifiable? Emerging Infectious Diseases 3(2), 83–94 (1997)

    Article  Google Scholar 

  3. Wagner, M.M., et al.: The emerging science of very early detection of disease outbreaks. Journal of Public Health Management & Practice 7(6), 51–59 (2001)

    Article  Google Scholar 

  4. Buckeridge, D.L., et al.: Evaluating detection of an inhalational anthrax outbreak. Emerging Infectious Diseases 12(12), 1942–1949 (2006)

    Article  Google Scholar 

  5. Heffernan, R., et al.: Syndromic surveillance in public health practice, New York City [erratum appears in Emerg Infect Dis. 2006 September 12(9):1472]. Emerging Infectious Diseases 10(5), 858–864 (2004)

    Article  Google Scholar 

  6. Mandl, K.D., et al.: Implementing syndromic surveillance: a practical guide informed by the early experience. Journal of the American Medical Informatics Association 11(2), 141–150 (2004)

    Article  Google Scholar 

  7. Lewis, M.D., et al.: Disease outbreak detection system using syndromic data in the greater Washington DC area [see comment]. American Journal of Preventive Medicine 23(3), 180–186 (2002)

    Article  Google Scholar 

  8. Lombardo, J.: The ESSENCE disease surveillance test bed for the National Capital Area. Johns Hopkins APL Technical Digest, 327–334 (2003)

    Google Scholar 

  9. Tsui, F.C., et al.: Technical description of RODS: a real-time public health surveillance system. Journal of the American Medical Informatics Association 10(5), 399–408 (2003)

    Article  Google Scholar 

  10. Wagner, M.M., et al.: Design of a national retail data monitor for public health surveillance. Journal of the American Medical Informatics Association 10(5), 409–418 (2003)

    Article  Google Scholar 

  11. Tuner’s Method (Accessed 2005 March 15) (2002), http://www.webmet.com/met_monitoring/641.html

  12. Buckeridge, D.L., et al.: Algorithms for rapid outbreak detection: a research synthesis. Journal of Biomedical Informatics 38(2), 99–113 (2005)

    Article  Google Scholar 

  13. Wong, W.K., et al.: WSARE: What’s Strange About Recent Events? Journal of Urban Health 80(2 suppl 1), 66–75 (2003)

    Google Scholar 

  14. Fawcett, T., Provost, F.: Activity monitoring: noticing interesting changes in behavior. In: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, San Diego (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15260, USA

    Xiaohui Kong, Garrick L. Wallstrom & William R. Hogan

Authors
  1. Xiaohui Kong
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  2. Garrick L. Wallstrom
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  3. William R. Hogan
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Editor information

Editors and Affiliations

  1. MIS Department, University of Arizona and Chinese Academy of Sciences, Tucson, AZ, USA

    Daniel Zeng

  2. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  3. US CDC, National Center for Public Health Informatics, Atlanta, GA, USA

    Henry Rolka

  4. University of Washington, Health Sciences Building, 1959 NE Pacific St., WA 98195, Seattle, USA

    Bill Lober

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© 2008 Springer-Verlag Berlin Heidelberg

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Kong, X., Wallstrom, G.L., Hogan, W.R. (2008). A Temporal Extension of the Bayesian Aerosol Release Detector. In: Zeng, D., Chen, H., Rolka, H., Lober, B. (eds) Biosurveillance and Biosecurity . BioSecure 2008. Lecture Notes in Computer Science(), vol 5354. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89746-0_10

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  • DOI: https://doi.org/10.1007/978-3-540-89746-0_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89745-3

  • Online ISBN: 978-3-540-89746-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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