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Estimating the prevalence of infections in vector populations using pools of samples

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Abstract
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.
Keywords
prevalence, pool of samples, model, arthropod vector, POLYMERASE-CHAIN-REACTION, ONCHOCERCA-VOLVULUS INFECTION, DISEASE PREVALENCE, BAYESIAN-INFERENCE, REGRESSION-MODELS, DIAGNOSTIC-TESTS, JOHNES-DISEASE, BORNE DISEASES, TRANSMISSION, SPECIFICITY

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Chicago
Speybroeck, Niko, Christopher J Williams, Kora Brice Lafia, Brecht Devleesschauwer, and Dirk Berkvens. 2012. “Estimating the Prevalence of Infections in Vector Populations Using Pools of Samples.” Medical and Veterinary Entomology 26 (4): 361–371.
APA
Speybroeck, Niko, Williams, C. J., Lafia, K. B., Devleesschauwer, B., & Berkvens, D. (2012). Estimating the prevalence of infections in vector populations using pools of samples. MEDICAL AND VETERINARY ENTOMOLOGY, 26(4), 361–371.
Vancouver
1.
Speybroeck N, Williams CJ, Lafia KB, Devleesschauwer B, Berkvens D. Estimating the prevalence of infections in vector populations using pools of samples. MEDICAL AND VETERINARY ENTOMOLOGY. 2012;26(4):361–71.
MLA
Speybroeck, Niko, Christopher J Williams, Kora Brice Lafia, et al. “Estimating the Prevalence of Infections in Vector Populations Using Pools of Samples.” MEDICAL AND VETERINARY ENTOMOLOGY 26.4 (2012): 361–371. Print.
@article{2084274,
  abstract     = {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.},
  author       = {Speybroeck, Niko and Williams, Christopher J and Lafia, Kora Brice and Devleesschauwer, Brecht and Berkvens, Dirk},
  issn         = {0269-283X},
  journal      = {MEDICAL AND VETERINARY ENTOMOLOGY},
  keyword      = {prevalence,pool of samples,model,arthropod vector,POLYMERASE-CHAIN-REACTION,ONCHOCERCA-VOLVULUS INFECTION,DISEASE PREVALENCE,BAYESIAN-INFERENCE,REGRESSION-MODELS,DIAGNOSTIC-TESTS,JOHNES-DISEASE,BORNE DISEASES,TRANSMISSION,SPECIFICITY},
  language     = {eng},
  number       = {4},
  pages        = {361--371},
  title        = {Estimating the prevalence of infections in vector populations using pools of samples},
  url          = {http://dx.doi.org/10.1111/j.1365-2915.2012.01015.x},
  volume       = {26},
  year         = {2012},
}

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