LSHTM Research Online

Punyacharoensin, N; Edmunds, WJ; De Angelis, D; Delpech, V; Hart, G; Elford, J; Brown, A; Gill, N; White, RG; (2015) Modelling the HIV epidemic among MSM in the United Kingdom: quantifying the contributions to HIV transmission to better inform prevention initiatives. AIDS (London, England), 29 (3). pp. 339-49. ISSN 0269-9370 DOI: 10.1097/QAD.0000000000000525

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Abstract

HIV is a major public health problem among MSM in the United Kingdom with around 2400 new infections annually. We quantified the contribution of biological and behavioural factors. Modelling study. A partnership-based model of HIV transmission among UK MSM aged 15-64 years was developed and calibrated to time series HIV prevalence. The calibration was validated using multiple surveillance datasets. Population-attributable fractions were used to estimate the contribution of behavioural and biological factors to HIV transmission over the period 2001-2002, 2014-2015, and 2019-2020. The contribution of most biological and behavioural factors was relatively constant over time, with the key group sustaining HIV transmission being higher-sexual activity MSM aged below 35 years living with undiagnosed HIV. The effect of primary HIV infection was relatively small with 2014-2015 population-attributable fraction of 10% (3-28%) in comparison with other subsequent asymptomatic stages. Diagnosed men who were not on antiretroviral therapy (ART) currently contributed 26% (14-39%) of net infections, whereas ART-treated MSM accounted for 17% (10-24%). A considerable number of new infections are also likely to occur within long-term relationships. The majority of the new HIV infections among MSM in the United Kingdom during 2001-2020 is expected to be accounted for by a small group of younger and highly sexually active individuals, living with undiagnosed HIV in the asymptomatic stage. Bringing this group into HIV/AIDS care by improving testing uptake is a vital step for preventing onward transmission and will determine the success of using ART as prevention.

Item Type:	Article
Faculty and Department:	Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Research Centre:	Centre for the Mathematical Modelling of Infectious Diseases Centre for Statistical Methodology
PubMed ID:	25686682
Web of Science ID:	347956200010
URI:	http://researchonline.lshtm.ac.uk/id/eprint/2115574

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