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dc.contributor.authorFricker, Ronald D. Jr.
dc.contributor.authorChang, Joseph T.
dc.dateMarch 31, 2008
dc.date.accessioned2014-02-06T00:07:06Z
dc.date.available2014-02-06T00:07:06Z
dc.date.issued2008-03
dc.identifier.citationFricker, R.D., Jr., and J.T. Chang (2008). A Spatio-temporal Methodology for Real-time Biosurveillance, Quality Engineering, 20, 465-477.en_US
dc.identifier.urihttp://hdl.handle.net/10945/38770
dc.descriptionQuality Engineering, 20, 465-477.en_US
dc.description.abstractIn this paper we introduce a new spatio-temporal methodology for biosurveillance entitled the Repeated Two-sample Rank (RTR) procedure. It is designed to sequentially incorporate information from individual observations and thus can operate on data in real-time as it arrives into an automated biosurveillance system. In addition, upon a signal of a possible outbreak, the methodology suggests a way to graphically indicate the likely outbreak location, and the output can subsequently be used to track the spread of an outbreak. Thus, the methodology can be used for both early event detection and situational awareness in automated biosurveillance systems.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. As such, it is in the public domain, and under the provisions of Title 17, United States Code, Section 105, may not be copyrighted.en_US
dc.titleA Spatio-temporal Methodology for Real-time Biosurveillanceen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Researchen_US
dc.subject.authorIn this paper we introduce a new spatio-temporal methodology for biosurveillance entitled the Repeated Two-sample Rank (RTR) procedure. It is designed to sequentially incorporate information from individual observations and thus can operate on data in real-time as it arrives into an automated biosurveillance system. In addition, upon a signal of a possible outbreak, the methodology suggests a way to graphically indicate the likely outbreak location, and the output can subsequently be used to track the spread of an outbreak. Thus, the methodology can be used for both early event detection and situational awareness in automated biosurveillance systemsen_US


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