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A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease

C. P. Farrington, N. J. Andrews, A. D. Beale and M. A. Catchpole
Journal of the Royal Statistical Society. Series A (Statistics in Society)
Vol. 159, No. 3 (1996), pp. 547-563
Published by: Wiley for the Royal Statistical Society
DOI: 10.2307/2983331
Stable URL: http://www.jstor.org/stable/2983331
Page Count: 17
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A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease
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Abstract

Outbreaks of infectious diseases must be detected early for effective control measures to be introduced. When dealing with large amounts of data, automated procedures can usefully supplement traditional surveillance methods, provided that the wide variety of patterns and frequencies of infections are taken into account. This paper describes a robust system developed to process weekly reports of infections received at the Communicable Disease Surveillance Centre. A simple regression algorithm is used to calculate suitable thresholds. Organisms exceeding their threshold are then flagged for further investigation.

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