Institute of Tropical Medicine Antwerp
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True versus apparent malaria infection prevalence: the contribution of a Bayesian approach

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dc.contributor.author Speybroeck, N.
dc.contributor.author Praet, N.
dc.contributor.author Claes, F.
dc.contributor.author Van Hong, N.
dc.contributor.author Torres, K.
dc.contributor.author Mao, S.
dc.contributor.author Van den Eede, P.
dc.contributor.author Thi Thinh, T.
dc.contributor.author Gamboa, D.
dc.contributor.author Sochantha, T.
dc.contributor.author Thang, N. D.
dc.contributor.author Coosemans, M.
dc.contributor.author Büscher, P.
dc.contributor.author D'Alessandro, U.
dc.contributor.author Berkvens, D.
dc.contributor.author Erhart, A.
dc.date.accessioned 2011-03-23T10:25:55Z
dc.date.available 2011-03-23T10:25:55Z
dc.date.issued 2011
dc.identifier.issn 1932-6203
dc.identifier.doi http://dx.doi.org/10.1371/journal.pone.0016705
dc.identifier.other ITG-A2A
dc.identifier.other ITG-P2A
dc.identifier.other ITG-P7A
dc.identifier.other ITG-P13A
dc.identifier.other ITG-P14A
dc.identifier.other ITG-A15A
dc.identifier.other ITG-PLA
dc.identifier.other MULTI
dc.identifier.other ANIMAL
dc.identifier.other U-VHELM
dc.identifier.other U-VEPID
dc.identifier.other PARAS
dc.identifier.other U-SEROL
dc.identifier.other U-MALAR
dc.identifier.other JIF
dc.identifier.other FTA
dc.identifier.other DOI
dc.identifier.other Electronic
dc.identifier.other Abstract
dc.identifier.other UPD32
dc.identifier.uri http://hdl.handle.net/10390/6529
dc.description.abstract AIMS: To present a new approach for estimating the "true prevalence" of malaria and apply it to datasets from Peru, Vietnam, and Cambodia. METHODS: Bayesian models were developed for estimating both the malaria prevalence using different diagnostic tests (microscopy, PCR & ELISA), without the need of a gold standard, and the tests' characteristics. Several sources of information, i.e. data, expert opinions and other sources of knowledge can be integrated into the model. This approach resulting in an optimal and harmonized estimate of malaria infection prevalence, with no conflict between the different sources of information, was tested on data from Peru, Vietnam and Cambodia. RESULTS: Malaria sero-prevalence was relatively low in all sites, with ELISA showing the highest estimates. The sensitivity of microscopy and ELISA were statistically lower in Vietnam than in the other sites. Similarly, the specificities of microscopy, ELISA and PCR were significantly lower in Vietnam than in the other sites. In Vietnam and Peru, microscopy was closer to the "true" estimate than the other 2 tests while as expected ELISA, with its lower specificity, usually overestimated the prevalence. CONCLUSIONS: Bayesian methods are useful for analyzing prevalence results when no gold standard diagnostic test is available. Though some results are expected, e.g. PCR more sensitive than microscopy, a standardized and context-independent quantification of the diagnostic tests' characteristics (sensitivity and specificity) and the underlying malaria prevalence may be useful for comparing different sites. Indeed, the use of a single diagnostic technique could strongly bias the prevalence estimation. This limitation can be circumvented by using a Bayesian framework taking into account the imperfect characteristics of the currently available diagnostic tests. As discussed in the paper, this approach may further support global malaria burden estimation initiatives. en
dc.language English en
dc.subject Protozoal diseases en
dc.subject Malaria en
dc.subject Plasmodium falciparum en
dc.subject Vectors en
dc.subject Mosquitoes en
dc.subject Anopheles en
dc.subject Epidemiological modeling en
dc.subject Prevalence en
dc.subject Bayes theorem en
dc.subject Estimation en
dc.subject Diagnostics en
dc.subject Microscopy en
dc.subject Polymerase chain reaction en
dc.subject PCR en
dc.subject ELISA en
dc.subject Infection rates en
dc.subject Sensitivity en
dc.subject Specificity en
dc.subject Laboratory techniques and procedures en
dc.subject Peru en
dc.subject America, Latin en
dc.subject Vietnam en
dc.subject Asia, Southeast en
dc.title True versus apparent malaria infection prevalence: the contribution of a Bayesian approach en
dc.type Article-E en
dc.citation.issue 2 en
dc.citation.jtitle PLoS ONE en
dc.citation.volume 6 en
dc.citation.pages e16705 en
dc.identifier.pmid http://www.ncbi.nlm.nih.gov/pubmed/21364745
dc.citation.jabbreviation PLoS ONE en


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