Modeling influenza incidence for the purpose of on-line monitoring
(), David Bock
() and Marianne Frisén
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; (follow links to similar papers)
JEL-Codes: C10; (follow links to similar papers)
20 pages, November 27, 2007
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- This paper is published as:
Andersson, Eva, 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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