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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
HPTN 071 (PopART): A cluster-randomized trial of the population impact of an HIV combination prevention intervention including universal testing and treatment: Mathematical model
PLoS ONE, Volume 9, No. 1, Article e84511, Year 2014
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Description
Background: The HPTN 052 trial confirmed that antiretroviral therapy (ART) can nearly eliminate HIV transmission from successfully treated HIV-infected individuals within couples. Here, we present the mathematical modeling used to inform the design and monitoring of a new trial aiming to test whether widespread provision of ART is feasible and can substantially reduce population-level HIV incidence. Methods and Findings: The HPTN 071 (PopART) trial is a three-arm cluster-randomized trial of 21 large population clusters in Zambia and South Africa, starting in 2013. A combination prevention package including home-based voluntary testing and counseling, and ART for HIV positive individuals, will be delivered in arms A and B, with ART offered universally in arm A and according to national guidelines in arm B. Arm C will be the control arm. The primary endpoint is the cumulative threeyear HIV incidence. We developed a mathematical model of heterosexual HIV transmission, informed by recent data on HIV-1 natural history. We focused on realistically modeling the intervention package. Parameters were calibrated to data previously collected in these communities and national surveillance data. We predict that, if targets are reached, HIV incidence over three years will drop by.60% in arm A and.25% in arm B, relative to arm C. The considerable uncertainty in the predicted reduction in incidence justifies the need for a trial. The main drivers of this uncertainty are possible community-level behavioral changes associated with the intervention, uptake of testing and treatment, as well as ART retention and adherence. Conclusions: The HPTN 071 (PopART) trial intervention could reduce HIV population-level incidence by.60% over three years. This intervention could serve as a paradigm for national or supra-national implementation. Our analysis highlights the role mathematical modeling can play in trial development and monitoring, and more widely in evaluating the impact of treatment as prevention. © 2014 Cori et al.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC3893126/bin/pone.0084511.s001.pdf
Authors & Co-Authors
Cori, Anne
Unknown Affiliation
Ayles, Helen Mary
Unknown Affiliation
Beyers, Nulda
Unknown Affiliation
Schaap, Ab
Unknown Affiliation
Floyd, Sian
Unknown Affiliation
Sabapathy, Kalpana
Unknown Affiliation
Eaton, Jeffrey William
Unknown Affiliation
Hauck, Katharina
Unknown Affiliation
Smith, Peter C.
Unknown Affiliation
Griffith, Sam B.
Unknown Affiliation
Moore, Ayana T.
Unknown Affiliation
Donnell, Deborah J.
Unknown Affiliation
Vermund, Sten Havlor
Unknown Affiliation
Fidler, Sarah J.
Unknown Affiliation
Hayes, Richard John
Unknown Affiliation
Fraser, Christophe
Unknown Affiliation
Statistics
Citations: 109
Authors: 16
Affiliations: 9
Identifiers
Doi:
10.1371/journal.pone.0084511
e-ISSN:
19326203
Research Areas
Infectious Diseases
Study Design
Randomised Control Trial
Cross Sectional Study
Cohort Study
Study Locations
South Africa
Zambia