Titlebook: Infectious Disease Informatics; Syndromic Surveillan Hsinchun Chen,Daniel Zeng,Ping Yan Book 2010 Springer-Verlag US 2010 Information Techn

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Data Analysis and Outbreak Detectionoutbreaks. At the core of these analysis components is the automated process of detecting aberration or data anomalies in the public health surveillance data, which often have prominent temporal and spatial data elements, by statistical analysis or data mining techniques. These methods are also capa

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System Assessment and Evaluationn outbreak or recognize a bioterrorism attack. Knowing the error rate of a system can help make decisions regarding how much effort is needed to investigate an alarm. The performance of the algorithms for outbreak characterization determines the amount of information they provide (e.g., sets of affe

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ESSENCElied Physics Laboratory (JHU/APL) in collaboration with the Maryland Department of Health and Mental Hygiene, the District of Columbia Department of Health, and the Virginia Department of Health under the sponsorship of the Defense Advanced Research Projects Agency (DARPA). It is now used in the Dep

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New York City Syndromic Surveillance Systemsomes) since 1995 (Heffernan et al., 2004a). The DOHMH syndromic surveillance system consists of (ED)-visits-based surveillance system and a few other complementary surveillance systems for Emergency Medical Services (EMS) ambulance dispatch calls, retail pharmacy sales, and work absenteeism data. Th