Mathematical models for the study of HIV spread and control amongst men who have sex with men.

For a quarter of century, mathematical models have been used to study the spread and control of HIV amongst men who have sex with men (MSM). We searched MEDLINE and EMBASE databases up to the end of 2010 and reviewed this literature to summarise the methodologies used, key model developments, and the recommended strategies for HIV control amongst MSM. Of 742 studies identified, 127 studies met the inclusion criteria. Most studies employed deterministic modelling methods (80%). Over time we saw an increase in model complexity regarding antiretroviral therapy (ART), and a corresponding decrease in complexity regarding sexual behaviours. Formal estimation of model parameters was carried out in only a small proportion of the studies (22%) while model validation was considered by an even smaller proportion (17%), somewhat reducing confidence in the findings from the studies. Nonetheless, a number of common conclusions emerged, including (1) identification of the importance of assumptions regarding changes in infectivity and sexual contact rates on the impact of ART on HIV incidence, that subsequently led to empirical studies to gather these data, and (2) recommendation that multiple strategies would be required for effective HIV control amongst MSM. The role of mathematical models in studying epidemics is clear, and the lack of formal inference and validation highlights the need for further developments in this area. Improved methodologies for parameter estimation and systematic sensitivity analysis will help generate predictions that more fully express uncertainty, allowing better informed decision making in public health.

Effect of pre-exposure prophylaxis and combination HIV prevention for men who have sex with men in the UK: a mathematical modelling study.

BACKGROUND: HIV transmission in men who have sex with men (MSM) in the UK has shown no sign of decreasing in the past decade. Additional prevention measures are needed. We aimed to estimate the effect of various potential interventions implemented individually and in combination on prevention of HIV infection. METHODS: We extended a deterministic partnership-based mathematical model for HIV transmission, informed by detailed behavioural and surveillance data, to assess the effect of seven different HIV interventions implemented in MSM (aged 15-64 years) in the UK during 2014-20, including increasing rates of HIV testing, test-and-treat programmes, pre-exposure prophylaxis (PrEP), and sexual behavioural changes. We did sensitivity analyses on risk compensation. FINDINGS: We predicted a baseline of 16 955 new infections (IQR 13 156-21 669) in MSM in the UK during 2014-20. At a coverage of ≤50%, testing twice a year outperformed all other interventions. Of all intervention combinations, only the combined effect of test and treat and annual HIV testing (61·8%, IQR 47·2-81·8, of total incidence) was greater than the sum of effects of the two interventions individually (32·6%, 23·7-46·0, and 23·9%, 16·5-33·3, respectively). Simultaneous PrEP, expansion of HIV testing, and initiation of test-and-treat programme in 25% of high-activity MSM could save 7399 (IQR 5587-9813) UK MSM from HIV infection (43·6%, IQR 32·9-57·9, of total incidence). An increase in unsafe sex or sexual partners to 50% or more could substantially reduce the effect of interventions, but is unlikely to negate the prevention benefit completely. INTERPRETATION: PrEP could prevent a large number of new HIV infections if other key strategies including HIV testing and treatment are simultaneously expanded and improved. Without PrEP, HIV incidence in MSM in the UK is unlikely to decrease substantially by the end of this decade. FUNDING: Health Protection Agency (now Public Health England).

Modelling the HIV epidemic among MSM in the United Kingdom: quantifying the contributions to HIV transmission to better inform prevention initiatives.

OBJECTIVES: 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. DESIGN: Modelling study. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Trends in three decades of HIV/AIDS epidemic in Thailand by nonparametric backcalculation method.

OBJECTIVES: To reconstruct the past HIV incidence and prevalence in Thailand from 1980 to 2008 and predict the country's AIDS incidence from 2009 to 2011. METHODS: Nonparametric backcalculation was adopted utilizing 100 quarterly observed new AIDS counts excluding pediatric cases. The accuracy of data was enhanced through a series of data adjustments using the weight method to account for several surveillance reporting issues. The mixture of time-dependent distributions allowed the effects of age at seroconversion and antiretroviral therapy to be incorporated simultaneously. Sensitivity analyses were conducted to assess model variations that were subject to major uncertainties. Future AIDS incidence was projected for various predetermined HIV incidence patterns. RESULTS: HIV incidence in Thailand reached its peak in 1992 with approximately 115,000 cases. A steep decline thereafter discontinued in 1997 and was followed by another strike of 42,000 cases in 1999. The second surge, which happened concurrently with the major economic crisis, brought on 60,000 new infections. As of December 2008, more than 1 million individuals had been infected and around 430,000 adults were living with HIV corresponding to a prevalence rate of 1.2%. The incidence rate had become less than 0.1% since 2002. The backcalculated estimates were dominated by postulated median AIDS progression time and adjustments to surveillance data. CONCLUSION: Our analysis indicated that, thus far, the 1990s was the most severe era of HIV/AIDS epidemic in Thailand with two HIV incidence peaks. A drop in new infections led to a decrease in recent AIDS incidence, and this tendency is likely to remain unchanged until 2011, if not further.