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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18867

Title: Estimating dynamic transmission model parameters for seasonal influenza by fitting to age and season-specific influenza-like illness incidence
Authors: Goeyvaerts, Nele
Willem, Lander
Van Kerckhove, Kim
Vandendijck, Yannick
Hanquet, Germaine
Beutels, Phillipe
Hens, Niel
Issue Date: 2015
Citation: Epidemics, 13, p. 1-9
Abstract: Dynamic transmission models are essential to design and evaluate control strategies for airborne infections. Our objective was to develop a dynamic transmission model for seasonal influenza allowing to evaluate the impact of vaccinating specific age groups on the incidence of infection, disease and mortality. Projections based on such models heavily rely on assumed ‘input’ parameter values. In previous seasonal influenza models, these parameter values were commonly chosen ad hoc, ignoring between-season variability and without formal model validation or sensitivity analyses. We propose to directly estimate the parameters by fitting the model to age-specific influenza-like illness (ILI) incidence data over multiple influenza seasons. We used a weighted least squares (WLS) criterion to assess model fit and applied our method to Belgian ILI data over six influenza seasons. After exploring parameter importance using symbolic regression, we evaluated a set of candidate models of differing complexity according to the number of season-specific parameters. The transmission parameters (average R0, seasonal amplitude and timing of the seasonal peak), waning rates and the scale factor used for WLS optimization, influenced the fit to the observed ILI incidence the most. Our results demonstrate the importance of between-season variability in influenza transmission and our estimates are in line with the classification of influenza seasons according to intensity and vaccine matching.
Notes: Corresponding author at: Interuniversity Institute for Biostatistics and statistical Bioinformatics, Hasselt University, Agoralaan Gebouw D, B3590 Diepenbeek, Belgium. Tel.: +32 11 268294. E-mail address: nele.goeyvaerts@uhasselt.be (N. Goeyvaerts).
URI: http://hdl.handle.net/1942/18867
DOI: 10.1016/j.epidem.2015.04.002
ISI #: 000365890900001
ISSN: 1755-4365
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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