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dc.contributor.authorKosack, C
dc.contributor.authorShanks, L
dc.contributor.authorBeelaert, G
dc.contributor.authorBenson, T
dc.contributor.authorSavane, A
dc.contributor.authorNg'ang'a, A
dc.contributor.authorAndre, B
dc.contributor.authorZahinda, J
dc.contributor.authorFransen, K
dc.contributor.authorPage, A
dc.date.accessioned2017-08-05T20:46:13Z
dc.date.available2017-08-05T20:46:13Z
dc.date.issued2017-07-26
dc.date.submitted2017-07-31
dc.identifier.citationDesigning HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in sub-Saharan Africa. 2017 J. Clin. Microbiol.en
dc.identifier.issn1098-660X
dc.identifier.pmid28747371
dc.identifier.doi10.1128/JCM.00962-17
dc.identifier.urihttp://hdl.handle.net/10144/618982
dc.description.abstractOur objective was to evaluate the performance of HIV testing algorithms based on WHO recommendations, using data from specimens collected at six HIV testing and counselling sites in sub-Saharan Africa (Guinea, Conakry; Kitgum and Arua, Uganda; Homa Bay, Kenya; Douala, Cameroun; Baraka, Democratic Republic of Congo). A total of 2780 samples, including 1306 HIV-positive, were included in the analysis. HIV testing algorithms were designed using Determine as a first test. Second and third rapid diagnostic tests (RDT) were selected based on site-specific performance, adhering where possible to the WHO-recommended minimum requirements of sensitivity and specificity of ≥99%. The threshold for specificity was reduced to 98% or 96% if necessary. We also simulated algorithms consisting of one RDT followed by a simple confirmatory assay. The positive predictive values (PPV) of the simulated algorithms varied from 75.8%-100% using strategies recommended for high-prevalence settings; 98.7%-100% using strategies recommended for low-prevalence settings; and 98.1%-100% using a rapid test followed by a simple confirmatory assay. Although we were able to design algorithms that met the recommended PPV of ≥99% in five of six sites using the applicable high prevalence strategy, options were often very limited due to sub-optimal performance of individual RDTs and to shared false-reactive results. These results underscore the impact of the sequence of HIV tests and of shared false-reactivity on algorithm performance. Where it is not possible to identify tests that meet WHO-recommended specifications, the low-prevalence strategy may be more suitable.
dc.language.isoenen
dc.publisherAmerican Society for Microbiologyen
dc.rightsPublished by the American Society for Microbiology - Archived on this site with kind permission from the American Society for Microbiologyen
dc.titleDesigning HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in sub-Saharan Africaen
dc.identifier.journalJournal of Clinical Microbiologyen
refterms.dateFOA2019-03-04T13:32:08Z
html.description.abstractOur objective was to evaluate the performance of HIV testing algorithms based on WHO recommendations, using data from specimens collected at six HIV testing and counselling sites in sub-Saharan Africa (Guinea, Conakry; Kitgum and Arua, Uganda; Homa Bay, Kenya; Douala, Cameroun; Baraka, Democratic Republic of Congo). A total of 2780 samples, including 1306 HIV-positive, were included in the analysis. HIV testing algorithms were designed using Determine as a first test. Second and third rapid diagnostic tests (RDT) were selected based on site-specific performance, adhering where possible to the WHO-recommended minimum requirements of sensitivity and specificity of ≥99%. The threshold for specificity was reduced to 98% or 96% if necessary. We also simulated algorithms consisting of one RDT followed by a simple confirmatory assay. The positive predictive values (PPV) of the simulated algorithms varied from 75.8%-100% using strategies recommended for high-prevalence settings; 98.7%-100% using strategies recommended for low-prevalence settings; and 98.1%-100% using a rapid test followed by a simple confirmatory assay. Although we were able to design algorithms that met the recommended PPV of ≥99% in five of six sites using the applicable high prevalence strategy, options were often very limited due to sub-optimal performance of individual RDTs and to shared false-reactive results. These results underscore the impact of the sequence of HIV tests and of shared false-reactivity on algorithm performance. Where it is not possible to identify tests that meet WHO-recommended specifications, the low-prevalence strategy may be more suitable.


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