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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/18637

Title: The social contact hypothesis under the assumption of endemic equilibrium: Elucidating the transmission potential of VZV in Europe.
Authors: SANTERMANS, Eva
Melegaro, Alessia
Edmunds, W.J.
FAES, Christel
Beutels, P.
HENS, Niel
Issue Date: 2015
Citation: Epidemics, 11, p. 14-23
Abstract: The basic reproduction number R0 and the effective reproduction number R are pivotal parameters in infectious disease epidemiology, quantifying the transmission potential of an infection in a population. We estimate both parameters from 13 pre-vaccination serological data sets on varicella zoster virus (VZV) in 12 European countries and from population-based social contact surveys under the commonly made assumptions of endemic and demographic equilibrium. The fit to the serology is evaluated using the inferred effective reproduction number R as a model eligibility criterion combined with AIC as a model selection criterion. For only 2 out of 12 countries, the common choice of a constant proportionality factor is sufficient to provide a good fit to the seroprevalence data. For the other countries, an age-specific proportionality factor provides a better fit, assuming physical contacts lasting longer than 15 min are a good proxy for potential varicella transmission events. In all countries, primary infection with VZV most often occurs in early childhood, but there is substantial variation in transmission potential with R0 ranging from 2.8 in England and Wales to 7.6 in The Netherlands. Two non-parametric methods, the maximal information coefficient (MIC) and a random forest approach, are used to explain these differences in R0 in terms of relevant country-specific characteristics. Our results suggest an association with three general factors: inequality in wealth, infant vaccination coverage and child care attendance. This illustrates the need to consider fundamental differences between European countries when formulating and parameterizing infectious disease models.
Notes: Santermans, E (reprint author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. eva.santermans@uhasselt.be
URI: http://hdl.handle.net/1942/18637
DOI: 10.1016/j.epidem.2014.12.005
ISI #: 000354403100003
ISSN: 1755-4365
Category: A1
Type: Journal Contribution
Validation: ecoom, 2016
Appears in Collections: Research publications

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