An Improved Algorithm for Outbreak Detection in Multiple Surveillance Systems

Angela Noufaily, Doyo Enki, Paddy Farrington, Paul Garthwaite, Nick Andrews, Andre Charlett


A large scale multiple statistical surveillance system for infectious disease outbreaks has been in operation in England and Wales for nearly two decades. This system uses a robust quasi-Poisson regression algorithm to identify aberrances in weekly counts of isolates reported to the Health Protection Agency. We review the performance of the system to reduce the number of false reports, while retaining good power to detect genuine outbreaks. Several improvements are suggested relating to the treatment of trends, seasonality, reweighting of baselines and error structure. The new system greatly reduces the numbers of alarms while maintaining good overall performance.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *