title: Robust outbreak surveillance of epidemics in Sweden.
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.
authors.affiliation: Statistical Research Unit, Department of Economics, University of Gothenburg, and Department of Occupational and Environmental Medicine, Sahlgrenska University Hospital, SE 40530, Gothenburg, Sweden. marianne.frisen@statistics.gu.se
authors.forename: M
authors.initials: M
authors.lastname: Frisén
authors.forename: E
authors.initials: E
authors.lastname: Andersson
authors.forename: L
authors.initials: L
authors.lastname: Schiöler
mesh_terms: D000818:Animals; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D006801:Humans; D009980:Influenza A virus; D007251:Influenza, Human / Q000453:epidemiology; D015233:Models, Statistical; D011159:Population Surveillance; D013548:Sweden / Q000453:epidemiology; D014406:Tularemia / Q000453:epidemiology