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Introduction to Statistical Methods for Biosurveillance : With an Emphasis on Syndromic Surveillance / Ronald D. Fricker.

By: Material type: TextTextPublisher: Cambridge : Cambridge University Press, 2013Description: 1 online resource (411 pages) : digital, PDF file(s)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781139047906 (ebook)
Subject(s): Additional physical formats: Print version: : No titleDDC classification:
  • 363.325/3 23
LOC classification:
  • RA652.2.P82 F75 2013
Online resources: Summary: Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.
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Title from publisher's bibliographic system (viewed on 04 Apr 2016).

Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.

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