Statistical Modelling 12(5) (2012), 441–462
Estimating the population prevalence and force of infection directly from antibody titres
K. Bollaerts
Scientific Institute of Public Health
Brussels
Belgium
M. Aerts
Interuniversity Institute for Biostatistics and Statistical Bioinformatics
Hasselt University & Katholieke Univeriteit Leuven
Diepebeek
Belgium
email: marc.aerts@uhasselt.be
Z. Shkedy
Interuniversity Institute for Biostatistics and Statistical Bioinformatics
Hasselt University & Katholieke Univeriteit Leuven
Diepebeek
Belgium
C. Faes
Interuniversity Institute for Biostatistics and Statistical Bioinformatics
Hasselt University & Katholieke Univeriteit Leuven
Diepebeek
Belgium
Y. Van der Stede
Veterinary ad Agrochemical Research Centre
Brussels
Belgium
P. Beutels
Centre for Health Economics Research and Modelling Infectious Diseases
Centre for the Evaluation of Vaccination
Vaccine and Infectious Disease Institute
University of Antwerp
Antwerp
Belgium
Abstract:
The use of threshold values in order to diagnose individual subjects as being ‘susceptible’ or ‘infected or recovered/immune’ for a specific infection is virtually always prone to false positive, false negative or inconclusive classifications. Such misclassifications might lead to biased estimates for epidemiological parameters, such as the prevalence and the force of infection. In this article, we propose to estimate these epidemiological parameters directly from antibody titres, using an underlying mixture model. The method is applied to estimate the Salmonella serological prevalence in pigs and the age-dependent force of infection using serological data on the Varicella-Zoster virus (VZV) in humans. The threshold and direct method are compared through a simulation study.
Keywords:
force of infection; mixture model; serological data; test misclassification; prevalence
Downloads:
The Salmonella dataset is available upon request from the 5th author (Y. Van der Stede); the VZV dataset from the last author. Example data in
zipped archive
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