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

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Listed:
  • Nele Goeyvaerts
  • Niel Hens
  • Benson Ogunjimi
  • Marc Aerts
  • Ziv Shkedy
  • Pierre Van Damme
  • Philippe Beutels

Abstract

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. Copyright (c) 2010 Royal Statistical Society.

Suggested Citation

  • Nele Goeyvaerts & Niel Hens & Benson Ogunjimi & Marc Aerts & Ziv Shkedy & Pierre Van Damme & Philippe Beutels, 2010. "Estimating infectious disease parameters from data on social contacts and serological status," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 255-277.
  • Handle: RePEc:bla:jorssc:v:59:y:2010:i:2:p:255-277
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    1. H. J. Whitaker & C. P. Farrington, 2004. "Infections with Varying Contact Rates: Application to Varicella," Biometrics, The International Biometric Society, vol. 60(3), pages 615-623, September.
    2. C. P. Farrington & M. N. Kanaan & N. J. Gay, 2001. "Estimation of the basic reproduction number for infectious diseases from age-stratified serological survey data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(3), pages 251-292.
    3. Farrington, C. Paddy & Whitaker, Heather J., 2005. "Contact Surface Models for Infectious Diseases: Estimation From Serologic Survey Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 370-379, June.
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