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Argus

  • Hsinchun Chen
  • Daniel Zeng
  • Ping Yan
Part of the Integrated Series in Information Systems book series (ISIS, volume 21)

Abstract

Project Argus creates and implements a biological event detection and tracking capability that provides early warning alerts on a global scale. Argus currently manages between 2,200 and 3,300 active, socially disruptive biological event case files with update report threading for approximately 175 countries and over 130 disease entities. It posits a sophisticated scaling of outbreak severity based not only on disease metrics but also on sociological and governmental reactions in the face of mild to severe epidemics (Chute, 2008).

The system relies on Internet technologies as “harvesting engines” to capture information relevant to the definitional criteria for biological-outbreak severity metrics. Official disease reports from WHO or unofficial international health status reports from ProMED are collected as indicators of possible biological events. The association of media activities and the biological events are shown in Figure 13-1. Figure 13-2 depicts the Argus system's biological event detection and tracking process.

Keywords

Definitional Criterion Social Disruption Tracking Capability Outbreak Severity Severe Epidemic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Important Readings:

  1. 1.
    Wilson, James M. V. (2007). “Argus: A Global Detection and Tracking System for Biological Events.” Advances in Disease Surveillance 4(21).Google Scholar
  2. 2.
    Chute, C. G. (2008). “Biosurveillance, Classification, and Semantic Health Technologies.” Journal of the American Medical Informatics Association 15(2), pp 172–173.PubMedCrossRefGoogle Scholar

References

  1. Chute, C.G. 2008. "Biosurveillance, Classification, and Semantic Health Technologies," Journal of the American Medical Informatics Association (15:2), pp 172–173.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Hsinchun Chen
    • 1
  • Daniel Zeng
    • 2
    • 3
  • Ping Yan
    • 2
  1. 1.Department of Management Information SystemsEller College of Management University of ArizonaTucsonUSA
  2. 2.Department of Management Information SystemsEller College of Management University of ArizonaTucsonUSA
  3. 3.Chinese Academy of SciencesBeijingChina

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