Estimating infectious disease parameters from data on social contacts and serological status

Nele Goeyvaerts, Niel Hens, Benson Ogunjimi, Marc Aerts, Ziv Shkedy, Pierre Van Damme and Philippe Beutels

Journal of the Royal Statistical Society Series C, 2010, vol. 59, issue 2, 255-277

Abstract: Summary. In dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so‐called ‘who acquires infection from whom’ matrix. These imposed mixing patterns are based on prior knowledge of age‐related social mixing behaviour rather than observations. Alternatively, we can assume that transmission rates for infections transmitted predominantly through non‐sexual social contacts are proportional to rates of conversational contact which can be estimated from a contact survey. In general, however, contacts reported in social contact surveys are proxies of those events by which transmission may occur and there may be age‐specific characteristics that are related to susceptibility and infectiousness which are not captured by the contact rates. Therefore, we model transmission as the product of two age‐specific variables: the age‐specific contact rate and an age‐specific proportionality factor, which entails an improvement of fit for the seroprevalence of the varicella zoster virus in Belgium. Furthermore, we address the effect on the estimation of the basic reproduction number, using non‐parametric bootstrapping to account for different sources of variability and using multimodel inference to deal with model selection uncertainty. The method proposed makes it possible to obtain important information on transmission dynamics that cannot be inferred from approaches that have been traditionally applied hitherto.

Date: 2010
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