Objectives Pre-exposure prophylaxis (PrEP) is recommended for preventing HIV infection among individuals at high risk, including men who have sex with men (MSM). Although its individual-level efficacy is proven, questions remain regarding population-level impact of PrEP implementation. Design We developed an agent-based simulation of HIV transmission among MSM, accounting for demographics, sexual contact network, HIV disease stage and use of antiretroviral therapy. We use this framework to compare PrEP delivery strategies in terms of impact on HIV incidence and prevalence. Results The projected reduction in HIV incidence achievable with PrEP reflects both population-level coverage and individual-level adherence (as a proportion of days protected against HIV transmission). For example, provision of PrEP to 40% of HIV-negative MSM reporting more than one sexual partner in the last 12 months, taken with sufficient adherence to provide protection on 40% of days, can reduce HIV incidence by 9.5% (95% uncertainty range: 8–11%) within five years. However, if this could be increased to 80% coverage on 80% of days (e.g., through mass campaigns with a long-acting injectable formulation), a 43% (42–44%) reduction in HIV incidence could be achieved. Delivering PrEP to MSM at high risk for HIV acquisition can augment population-level impact up to 1.8-fold. Conclusions If highly ambitious targets for coverage and adherence can be achieved, PrEP can substantially reduce HIV incidence in the short-term. While the reduction in HIV incidence largely reflects the proportion of person-years protected, the efficiency of PrEP delivery can be enhanced by targeting high-risk populations.
Introduction: As people with HIV age, prevention and management of other communicable and non-communicable diseases (NCDs) will become increasingly important. Integration of screening and treatment for HIV and NCDs is a promising approach for addressing the dual burden of these diseases. The aim of this study was to assess the epidemiological impact and cost-effectiveness of a community-wide integrated programme for screening and treatment of HIV, hypertension and diabetes in Kenya. Methods: Coupling a microsimulation of cardiovascular diseases (CVDs) with a population-based model of HIV dynamics (the Spectrum), we created a hybrid HIV/CVD model. Interventions were modelled from year 2019 (baseline) to 2023, and population was followed to 2033. Analyses were carried at a national level and for three selected regions (Nairobi, Coast and Central). Results: At a national level, the model projected 7.62 million individuals living with untreated hypertension, 692,000 with untreated diabetes and 592,000 individuals in need of ART in year 2018. Improving ART coverage from 68% at baseline to 88% in 2033 reduced HIV incidence by an estimated 64%. Providing NCD treatment to 50% of diagnosed cases from 2019 to 2023 and maintaining them on treatment afterwards could avert 116,000 CVD events and 43,600 CVD deaths in Kenya over the next 15 years. At a regional level, the estimated impact of expanded HIV services was highest in Nairobi region (averting 42,100 HIV infections compared to baseline) while Central region experienced the highest impact of expanded NCD treatment (with a reduction of 22,200 CVD events). The integrated HIV/NCD intervention could avert 7.76 million disabilityadjusted-life-years (DALYs) over 15 years at an estimated cost of $6.68 billion ($445.27 million per year), or $860.30 per DALY averted. At a cost-effectiveness threshold of $2,010 per DALY averted, the probability of cost-effectiveness was 0.92, ranging from 0.71 in Central to 0.92 in Nairobi region. Conclusions: Integrated screening and treatment of HIV and NCDs can be a cost-effective and impactful approach to save lives of people with HIV in Kenya, although important variation exists at the regional level. Containing the substantial costs required for scale-up will be critical for management of HIV and NCDs on a national scale.
In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission (“recent transmission proportion”), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional ‘n-1’ approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the ‘n-1’ technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the ‘n-1’ model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models’ performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data.
Delivering PrEP to MSM who attend STI clinics can improve efficiency and effectiveness. If high levels of adherence can be achieved in this population, STI clinics may be an important venue for PrEP implementation.
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