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Statistical methods for the prospective detection of infectious disease outbreaks: a review

Authors


Steffen Unkel, Department of Mathematics and Statistics, Faculty of Mathematics, Computing and Technology, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK.
E-mail: S.Unkel@open.ac.uk

Abstract

Summary.  Unusual clusters of disease must be detected rapidly for effective public health interventions to be introduced. Over the past decade there has been a surge in interest in statistical methods for the early detection of infectious disease outbreaks. This growth in interest has given rise to much new methodological work, ranging across the spectrum of statistical methods. The paper presents a comprehensive review of the statistical approaches that have been proposed. Applications to both laboratory and syndromic surveillance data are provided to illustrate the various methods.

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