Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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On the estimation of epidemiological parameters from serological survey data using Bayesian mixture modelling
Emanuele Del Fava, Piero Manfredi, Ziv Shkedy

Last modified: 2018-05-31

Abstract


In the context of serological surveys for the estimation of important epidemiological functions, mixture models offer an alternative and more accurate approach than the conventional one based on the diagnostic assay’s cut-off points. In this work, we propose an innovative Bayesian mixture model for the estimation of flexible models for the age-specific seroprevalence and force of infection (or incidence rate). In order to account for the possible waning of immunity by age, we propose a Bayesian variable selection approach to determine the best age-specific model for the mean and the variance of the seropositive subpopulation. Our methodology is applied to a sample of antibody titres to varicella from Italy. Our results confirm that mixture models are a flexible and highly customisable tool, adapt to be systematically used in serological surveys.

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