alexa Robust outbreak surveillance of epidemics in Sweden.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Health & Medical Informatics

Author(s): Frisn M, Andersson E, Schiler L

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Abstract Outbreak detection is of interest in connection with several diseases and syndromes. The aim is to detect the progressive increase in the incidence as soon as possible after the onset of the outbreak. A semiparametric method is applied to Swedish data on tularaemia 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 these can be used. The properties of the method are evaluated by application to Swedish data on tularaemia and influenza and by simulations. The suggested method is compared with subjective judgments as well as with other algorithms. The conclusion is that the method works well. A user-friendly computer program is described. Copyright (c) 2008 John Wiley & Sons, Ltd. This article was published in Stat Med and referenced in Journal of Health & Medical Informatics

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