Document Detail

Estimating the prevalence of infections in vector populations using pools of samples.
MedLine Citation:
PMID:  22486773     Owner:  NLM     Status:  Publisher    
Several statistical methods have been proposed for estimating the infection prevalence based on pooled samples, but these methods generally presume the application of perfect diagnostic tests, which in practice do not exist. To optimize prevalence estimation based on pooled samples, currently available and new statistical models were described and compared. Three groups were tested: (a) Frequentist models, (b) Monte Carlo Markov-Chain (MCMC) Bayesian models, and (c) Exact Bayesian Computation (EBC) models. Simulated data allowed the comparison of the models, including testing the performance under complex situations such as imperfect tests with a sensitivity varying according to the pool weight. In addition, all models were applied to data derived from the literature, to demonstrate the influence of the model on real-prevalence estimates. All models were implemented in the freely available R and OpenBUGS software and are presented in Appendix S1. Bayesian models can flexibly take into account the imperfect sensitivity and specificity of the diagnostic test (as well as the influence of pool-related or external variables) and are therefore the method of choice for calculating population prevalence based on pooled samples. However, when using such complex models, very precise information on test characteristics is needed, which may in general not be available.
N Speybroeck; C J Williams; K B Lafia; B Devleesschauwer; D Berkvens
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-4-8
Journal Detail:
Title:  Medical and veterinary entomology     Volume:  -     ISSN:  1365-2915     ISO Abbreviation:  -     Publication Date:  2012 Apr 
Date Detail:
Created Date:  2012-4-10     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8708682     Medline TA:  Med Vet Entomol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2012 The Authors. Medical and Veterinary Entomology © 2012 The Royal Entomological Society.
Institut de Recherche Santé et Société (IRSS), Université catholique de Louvain, Brussels, Belgium Department of Statistics, University of Idaho, Moscow, ID, U.S.A. Faculty of Agricultural Sciences, University of Abomey Calavi, Cotonou, Benin Department of Virology, Parasitology and Immunology, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium and Department of Animal Health, Institute of Tropical Medicine, Antwerp, Belgium.
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