The incidence of hepatitis C virus (HCV) infections among human immunodeficiency virus (HIV)‐infected men who have sex with men has increased in recent years and is associated with high‐risk sexual behavior. Behavioral interventions that target high‐risk behavior associated with HCV transmission and treatment with direct‐acting antivirals may prevent further HCV infections. We predicted the effect of behavioral and treatment interventions on HCV incidence and prevalence among HIV‐infected men who have sex with men up to 2030 using a HCV transmission model parameterized with data from the Swiss HIV Cohort Study. We assessed behavioral interventions associated with further increase, stabilization, and decrease in the size of the population with high‐risk behavior. Treatment interventions included increase in treatment uptake and use of direct‐acting antivirals. If we assumed that without behavioral interventions high‐risk behavior spread further according to the trends observed over the last decade and that the treatment practice did not change, HCV incidence converged to 10.7/100 person‐years. All assessed behavioral interventions alone resulted in reduced HCV transmissions. Stabilization of high‐risk behavior combined with increased treatment uptake and the use of direct‐acting antivirals reduced incidence by 77% (from 2.2 in 2015 to 0.5/100 person‐years) and prevalence by 81% (from 4.8% in 2015 to 0.9%) over the next 15 years. Increasing treatment uptake was more effective than increasing treatment efficacy to reduce HCV incidence and prevalence. A decrease in high‐risk behavior led to a rapid decline in HCV incidence, independent of treatment interventions. Conclusion: Treatment interventions to curb the HCV epidemic among HIV‐infected men who have sex with men are effective if high‐risk behavior does not increase as it has during the last decade; reducing high‐risk behavior associated with HCV transmission would be the most effective intervention for controlling the HCV epidemic, even if this was not accompanied by an increase in treatment uptake or efficacy. (Hepatology 2016;64:1856‐1869).

The number of patients in need of second-line antiretroviral drugs is increasing in sub-Saharan Africa. We aimed to project the need of second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030. We developed a simulation model for HIV and applied it to each sub-Saharan African country. We used the WHO country intelligence database to estimate the number of adult patients receiving antiretroviral therapy from 2005 to 2014. We fitted the number of adult patients receiving antiretroviral therapy to observed estimates, and predicted first-line and second-line needs between 2015 and 2030. We present results for sub-Saharan Africa, and eight selected countries. We present 18 scenarios, combining the availability of viral load monitoring, speed of antiretroviral scale-up, and rates of retention and switching to second-line. HIV transmission was not included. Depending on the scenario, 8·7-25·6 million people are expected to receive antiretroviral therapy in 2020, of whom 0·5-3·0 million will be receiving second-line antiretroviral therapy. The proportion of patients on treatment receiving second-line therapy was highest (15·6%) in the scenario with perfect retention and immediate switching, no further scale-up, and universal routine viral load monitoring. In 2030, the estimated range of patients receiving antiretroviral therapy will remain constant, but the number of patients receiving second-line antiretroviral therapy will increase to 0·8-4·6 million (6·6-19·6%). The need for second-line antiretroviral therapy was two to three times higher if routine viral load monitoring was implemented throughout the region, compared with a scenario of no further viral load monitoring scale-up. For each monitoring strategy, the future proportion of patients receiving second-line antiretroviral therapy differed only minimally between countries. Donors and countries in sub-Saharan Africa should prepare for a substantial increase in the need for second-line drugs during the next few years as access to viral load monitoring improves. An urgent need exists to decrease the costs of second-line drugs. World Health Organization, Swiss National Science Foundation, National Institutes of Health.

Objectives: HIV ‘treatment as prevention’ (TasP) describes early treatment of HIV-infected patients intended to reduce viral load and transmission. Crucial assumptions for estimating TasP's effectiveness are the underlying estimates of transmission risk. We aimed to determine transmission risk during primary infection, and describe the relation of HIV transmission risk to viral load. Design: A systematic review and meta-analysis. Methods: We searched PubMed and Embase databases for studies that established a relationship between viral load and transmission risk, or primary infection and transmission risk, in serodiscordant couples. We analysed assumptions about the relationship between viral load and transmission risk, and between duration of primary infection and transmission risk. Results: We found 36 eligible articles, based on six different study populations. Studies consistently found that higher viral loads lead to higher HIV transmission rates, but assumptions about the shape of this increase varied from exponential increase to saturation. The assumed duration of primary infection ranged from 1.5 to 12 months; for each additional month, the log₁₀ transmission rate ratio between primary and asymptomatic infection decreased by 0.40. Conclusion: Assumptions and estimates of the relationship between viral load and transmission risk, and the relationship between primary infection and transmission risk, vary substantially and predictions of TasP's effectiveness should take this uncertainty into account.

Background WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. Methods We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. Findings All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6–12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. Interpretation The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per μL, and then at a CD4 cell count lower than 500 cells per μL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. Funding Bill & Melinda Gates Foundation, WHO.

Background: Monitoring of HIV viral load in patients on combination antiretroviral therapy (ART) is not generally available in resource-limited settings. We examined the cost-effectiveness of qualitative point-of-care viral load tests (POC-VL) in sub-Saharan Africa. Design: Mathematical model based on longitudinal data from the Gugulethu and Khayelitsha township ART programmes in Cape Town, South Africa. Methods: Cohorts of patients on ART monitored by POC-VL, CD4 cell count or clinically were simulated. Scenario A considered the more accurate detection of treatment failure with POC-VL only, and scenario B also considered the effect on HIV transmission. Scenario C further assumed that the risk of virologic failure is halved with POC-VL due to improved adherence. We estimated the change in costs per quality-adjusted life-year gained (incremental cost-effectiveness ratios, ICERs) of POC-VL compared with CD4 and clinical monitoring. Results: POC-VL tests with detection limits less than 1000 copies/ml increased costs due to unnecessary switches to second-line ART, without improving survival. Assuming POC-VL unit costs between US$5 and US$20 and detection limits between 1000 and 10 000 copies/ml, the ICER of POC-VL was US$4010–US$9230 compared with clinical and US$5960–US$25540 compared with CD4 cell count monitoring. In Scenario B, the corresponding ICERs were US$2450–US$5830 and US$2230–US$10380. In Scenario C, the ICER ranged between US$960 and US$2500 compared with clinical monitoring and between cost-saving and US$2460 compared with CD4 monitoring. Conclusion: The cost-effectiveness of POC-VL for monitoring ART is improved by a higher detection limit, by taking the reduction in new HIV infections into account and assuming that failure of first-line ART is reduced due to targeted adherence counselling.

Background: Tuberculosis (TB) is the leading cause of death in South Africa. The burden of disease varies by age, with peaks in TB notification rates in the HIV-negative population at ages 0-5, 20-24, and 45-49 years. There is little variation between age groups in the rates in the HIV-positive population. The drivers of this age pattern remain unknown. Methods: We developed an age-structured simulation model of Mycobacterium tuberculosis (Mtb) transmission in Cape Town, South Africa. We considered five states of TB progression: susceptible, infected (latent TB), active TB, treated TB, and treatment default. Latently infected individuals could be re-infected; a previous Mtb infection slowed progression to active disease. We further considered three states of HIV progression: HIV negative, HIV positive, on antiretroviral therapy. To parameterize the model, we analysed treatment outcomes from the Cape Town electronic TB register, social mixing patterns from a Cape Town community and used literature estimates for other parameters. To investigate the main drivers behind the age patterns, we conducted sensitivity analyses on all parameters related to the age structure. Results: The model replicated the age patterns in HIV-negative TB notification rates of Cape Town in 2009. Simulated TB notification rate in HIV-negative patients was 1000/100,000 person-years (pyrs) in children aged <5 years and decreased to 51/100,000 in children 5-15 years. The peak in early adulthood occurred at 25-29 years (463/100,000 pyrs). After a subsequent decline, simulated TB notification rates gradually increased from the age of 30 years. Sensitivity analyses showed that the dip after the early adult peak was due to the protective effect of latent TB and that retreatment TB was mainly responsible for the rise in TB notification rates from the age of 30 years. Conclusion: The protective effect of a first latent infection on subsequent infections and the faster progression in previously treated patients are the key determinants of the age-structure of TB notification rates in Cape Town. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.