ArticleBMC infectious diseases2017
Improving ART programme retention and viral suppression are key to maximising impact of treatment as prevention - a modelling study.
Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Cost-Effectiveness of Differentiated Service Delivery for HIV Treatment: A Combined Mathematical Modeling Study of Four African Settings.Open forum infectious diseases · 2026Article
- Identifying gaps in the HIV treatment cascade in Africa: a model comparison study.The Lancet. Global health · 2025Article
- Prevalence and Determinants of Viral Suppression in Young People Living with HIV on Antiretroviral Therapy in Southern Africa: A Cross-Sectional Analysis of HIV Survey Data of 2020 and 2021.AIDS and behavior · 2025Article
- Scaling up a brief alcohol intervention to prevent HIV infection in Vietnam: a cluster randomized, implementation trial.Implementation science : IS · 2024Article
- Transmission reduction, health benefits, and upper-bound costs of interventions to improve retention on antiretroviral therapy: a combined analysis of three mathematical models.The Lancet. Global health · 2022Article
- Article
- Baseline CD4 and mortality trends in the South African human immunodeficiency virus programme: Analysis of routine data.Southern African journal of HIV medicine · 2019Article
- Mathematical modelling to inform 'treat all' implementation in sub-Saharan Africa: a scoping review.Journal of virus eradication · 2018Article
- Choice of time horizon critical in estimating costs and effects of changes to HIV programmes.PloS one · 2018Article
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Authors and funding
10 authors.
Funding
Abstract
backgroundUNAIDS calls for fewer than 500,000 new HIV infections/year by 2020, with treatment-as-prevention being a key part of their strategy for achieving the target. A better understanding of the contribution to transmission of people at different stages of the care pathway can help focus intervention services at populations where they may have the greatest effect. We investigate this using Uganda as a case study.
methodsAn individual-based HIV/ART model was fitted using history matching. 100 model fits were generated to account for uncertainties in sexual behaviour, HIV epidemiology, and ART coverage up to 2015 in Uganda. A number of different ART scale-up intervention scenarios were simulated between 2016 and 2030. The incidence and proportion of transmission over time from people with primary infection, post-primary ART-naïve infection, and people currently or previously on ART was calculated.
resultsIn all scenarios, the proportion of transmission by ART-naïve people decreases, from 70% (61%-79%) in 2015 to between 23% (15%-40%) and 47% (35%-61%) in 2030. The proportion of transmission by people on ART increases from 7.8% (3.5%-13%) to between 14% (7.0%-24%) and 38% (21%-55%). The proportion of transmission by ART dropouts increases from 22% (15%-33%) to between 31% (23%-43%) and 56% (43%-70%).
conclusionsPeople who are currently or previously on ART are likely to play an increasingly large role in transmission as ART coverage increases in Uganda. Improving retention on ART, and ensuring that people on ART remain virally suppressed, will be key in reducing HIV incidence in Uganda.
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