Data driven HIV programming to maximise health benefits

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dc.date.accessioned 2023-02-16T22:01:22Z
dc.date.available 2023-02-16T22:01:22Z
dc.date.issued 2020-09-20 en
dc.identifier.uri http://hdl.handle.net/20.500.11910/15443
dc.description.abstract From the perspective of the ongoing COVID-19 pandemic, where evidence on effective prevention and treatment interventions for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is limited, the near perfect efficacy of antiretroviral therapy (ART) for HIV treatment is enviable. ART prevents individual level HIV-associated morbidity and mortality, restoring life expectancy to near normal, and prevents transmissions by decreasing viral load to undetectable levels. To translate ART efficacy to population level health benefits, the Joint United Nations Programme on HIV/AIDS (UNAIDS) set goals to diagnose 90% of people living with HIV, link 90% of those diagnosed to ART, and achieve 90% viral suppression among people on ART by 2020. In the 6 years since UNAIDS set the 90-90-90 goal, four large community randomised trials tested ART as a strategy to decrease HIV incidence with mixed results. en
dc.format.medium Print en
dc.subject HIV/AIDS en
dc.subject COVID-19 en
dc.subject ANTIRETROVIRAL THERAPY (ART) en
dc.subject CLINICAL RESEARCH en
dc.title Data driven HIV programming to maximise health benefits en
dc.type Journal Article en
dc.description.version Y en
dc.ProjectNumber N/A en
dc.Volume 7(10) en
dc.BudgetYear 2020/21 en
dc.ResearchGroup Impact Centre en
dc.SourceTitle Lancet HIV en
dc.ArchiveNumber 11585 en
dc.PageNumber e662-e663 en
dc.outputnumber 10710 en
dc.bibliographictitle Barnabas, R.V. & Van Rooyen, H. (2020) Data driven HIV programming to maximise health benefits. Lancet HIV. 7(10):e662-e663. http://hdl.handle.net/20.500.11910/15443 en
dc.publicationyear 2020 en
dc.contributor.author1 Barnabas, R.V. en
dc.contributor.author2 Van Rooyen, H. en


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