A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data
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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.
KeywordsData Stream Syndromic Surveillance Multiple Stream Real Food Slaughter House
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- 1.Burkom, H.S., et al.: Public health monitoring tools for multiple data streams. MMWR Morbidity and Mortality Weekly Report (August 2005)Google Scholar
- 2.Dubrawski, A., et al.: Monitoring food safety by detecting patterns in consumer complaints. In: Proceedings of the National Conference on Artificial Intelligence AAAI/IAAI (2006)Google Scholar
- 3.Fisher, R.: Statistical methods for research workers. Oliver and Loyd, Edinburgh (1925)Google Scholar
- 4.Protecting against agroterrorism. GAO-05-214. Technical report, Government Accountability Office (March 2005)Google Scholar
- 5.Neill, D.B., Moore, A.W., Cooper, G.F.: A multivariate bayesian scan statistic. In: National Syndromic Surveillance Conference (2006)Google Scholar
- 6.Wagner, M.M., Moore, A.W., Aryel, R.M.: Handbook of Biosurveillance. Academic Press, London (2006)Google Scholar