Improving ART programme retention and viral suppression are key to maximising impact of treatment as prevention – a modelling study

BMC Infectious Diseases

Research Article

Trevelyan J. McKinley¹  Ian Vernon²  Michael Goldstein²  Richard Hayes³  Ioannis Andrianakis³  Richard G. White³  Nicky McCreesh³  Rebecca N. Nsubuga⁴  Mark Strong⁵  Jeremy E. Oakley⁶ 

[1] College of Engineering, Mathematics and Physical Sciences, University of Exeter, Penryn Campus, TR10 9FE, Penryn, UK;Department of Mathematical Sciences, Durham University, Lower Mountjoy, Stockton Road, DH1 3LE, Durham, UK;London School of Hygiene and Tropical Medicine, Keppel Street, WC1E 7HT, London, UK;MRC/UVRI Research Unit on AIDS, P.O. Box 49, Entebbe, Uganda;School of Health and Related Research, The University of Sheffield, 30 Regent Street, S1 4DA, Sheffield, UK;School of Mathematics and Statistics, University of Sheffield, The Hicks Building, Hounsfield Road, S3 7RH, Sheffield, UK;

关键词: HIV;    ART;    Uganda;    Transmission;    Sub-Saharan Africa;    Retention;   

DOI  :  10.1186/s12879-017-2664-6

 received in 2017-04-25, accepted in 2017-08-01,  发布年份 2017

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY   
© The Author(s). 2017