Research Reports,
University of Gothenburg, Statistical Research Unit, School of Business, Economics and Law

Abstract: Outbreak detection is of interest for several diseases and syndromes. The aim is to detect the progressing increase in the incidence as soon as possible after the onset of the outbreak. A semiparametric method is applied to Swedish data on tularemia and influenza. The method is constructed to detect a change from a constant level to a monotonically increasing incidence. If seasonal effects are present, the residuals from a model incorporating this can be used. The properties of the method are evaluated by application to Swedish influenza data on tularemia and influenza and by simulations. The suggested method is compared with subjective judgments and with other algorithms. The conclusion is that the method works well. A user-friendly computer program is described.

Keywords: Computer program; Exponential family; Influenza; Monitoring; Ordered regression; Subjective judgment; Tularemia

JEL-codes: C10

20 pages, January 1, 2007

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Published as

Marianne Frisén, Eva Andersson and Linus Schiöler, (2009), 'Robust outbreak surveillance of epidemics in Sweden', Statistics in Medicine, pages 476-493

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