Universidad Peruana Cayetano Heredia

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 Fajardo, Katherine Jessica
dc.contributor.author Mao, S.
dc.contributor.author van den Eede, P.
dc.contributor.author Thinh, T.T.
dc.contributor.author Gamboa Vilela, Dionicia Baziliza
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 2022-01-18T19:34:38Z
dc.date.available 2022-01-18T19:34:38Z
dc.date.issued 2011
dc.identifier.uri https://hdl.handle.net/20.500.12866/11085
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_US
dc.language.iso eng
dc.publisher Public Library of Science
dc.relation.ispartofseries PLoS ONE
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Humans en_US
dc.subject Peru en_US
dc.subject statistical model en_US
dc.subject controlled study en_US
dc.subject polymerase chain reaction en_US
dc.subject diagnostic test en_US
dc.subject geographic distribution en_US
dc.subject Malaria en_US
dc.subject Prevalence en_US
dc.subject statistics en_US
dc.subject evaluation en_US
dc.subject quantitative analysis en_US
dc.subject Sensitivity and Specificity en_US
dc.subject standard en_US
dc.subject Diagnosis, Differential en_US
dc.subject enzyme linked immunosorbent assay en_US
dc.subject Diagnostic Tests, Routine en_US
dc.subject intermethod comparison en_US
dc.subject Bayes Theorem en_US
dc.subject Vietnam en_US
dc.subject seroprevalence en_US
dc.subject mathematical computing en_US
dc.subject Cambodia en_US
dc.subject process optimization en_US
dc.subject biomicroscopy en_US
dc.title True versus apparent Malaria infection prevalence: The contribution of a Bayesian approach en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1371/journal.pone.0016705
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.01.00
dc.relation.issn 1932-6203


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