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A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data

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Intelligence and Security Informatics: Biosurveillance (BioSurveillance 2007)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4506))

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Abstract

This paper reviews the results of a study into combining evidence from multiple streams of surveillance data in order to improve timeliness and specificity of detection of bio-events. In the experiments we used three streams of real food- and agriculture-safety related data that is being routinely collected at slaughter houses across the nation, and which carry mutually complementary information about potential outbreaks of bio-events. The results indicate that: (1) Non-specific aggregation of p-values produced by event detectors set on individual streams of data can lead to superior detection power over that of the individual detectors, and (2) Design of multi-stream detectors tailored to the particular characteristics of the events of interest can further improve timeliness and specificity of detection. In a practical setup, we recommend combining a set of specific multi-stream detectors focused on individual types of predictable and definable scenarios of interest, with non-specific multi-stream detectors, to account for both anticipated and emerging types of bio-events.

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Daniel Zeng Ivan Gotham Ken Komatsu Cecil Lynch Mark Thurmond David Madigan Bill Lober James Kvach Hsinchun Chen

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© 2007 Springer Berlin Heidelberg

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Roure, J., Dubrawski, A., Schneider, J. (2007). A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data. In: Zeng, D., et al. Intelligence and Security Informatics: Biosurveillance. BioSurveillance 2007. Lecture Notes in Computer Science, vol 4506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72608-1_12

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  • DOI: https://doi.org/10.1007/978-3-540-72608-1_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72607-4

  • Online ISBN: 978-3-540-72608-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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