Scandinavian Working Papers in Economics

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

No 2007:5: Modeling influenza incidence for the purpose of on-line monitoring

Eva Andersson (), David Bock () and Marianne Frisén ()
Additional contact information
Eva Andersson: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG
David Bock: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG
Marianne Frisén: Statistical Research Unit, Department of Economics, School of Business, Economics and Law, Göteborg University, Postal: Statistical Research Unit, Göteborg University, Box 640, SE 40530 GÖTEBORG

Abstract: We describe and discuss statistical models of Swedish influenza data, with special focus on aspects which are important in on-line monitoring. Earlier suggested statistical models are reviewed and the possibility of using them to describe the variation in influenza-like illness (ILI) and laboratory diagnoses (LDI) is discussed. Exponential functions were found to work better than earlier suggested models for describing the influenza incidence. However, the parameters of the estimated functions varied considerably between years. For monitoring purposes we need models which focus on stable indicators of the change at the outbreak and at the peak.

For outbreak detection we focus on ILI data. Instead of a parametric estimate of the baseline (which could be very uncertain,), we suggest a model utilizing the monotonicity property of a rise in the incidence. For ILI data at the outbreak, Poisson distributions can be used as a first approximation.

To confirm that the peak has occurred and the decline has started, we focus on LDI data. A Gaussian distribution is a reasonable approximation near the peak. In view of the variability of the shape of the peak, we suggest that a detection system use the monotonicity properties of a peak.

Keywords: monitoring; influenza; surveillance

JEL-codes: C10

20 pages, November 27, 2007

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Published as
Eva Andersson, David Bock and Marianne Frisén, (2008), 'Modeling influenza incidence for the purpose of on-line monitoring', Statistical Methods in Medical Research, vol 17, no 4, pages 421-438

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