Abstract #302358

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JSM 2003 Abstract #302358
Activity Number: 436
Type: Topic Contributed
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #302358
Title: High- and Low-Powered Alternatives for Various Cluster Detection Approaches in the Context of Syndromic Surveillance for Bioterrorism
Author(s): Ken P. Kleinman*+
Companies: Harvard University Medical School
Address: 133 Brookline Ave., Boston, MA, 02215-3920,
Keywords:
Abstract:

We review several approaches to cluster detection in spatio-temporal surveillance, including scan statistics, cu-sum approaches, simple time-series analysis, and small-area modeling. Using heuristic arguments and simulated clusters inserted into real data, we compare and contrast the strengths of each technique to detect variously described clusters. The real data example shows how surveillance, in the case of anthrax, can detect bioterrorism before a single case of anthrax has been definitively diagnosed. The application of these statistical techniques for detecting bioterrorism is discussed. We conclude that very small exposures are essentially undetectable, large exposures can be detected by any of the mentioned techniques, and which intermediate exposures can be detected by which techniques.

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