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Introduction: Universal HIV testing and treatment aims to identify all people living with HIV and offer them treatment, decreasing the number of individuals with unsuppressed HIV and thus reducing HIV transmission. Longitudinal follow‐up of individuals with and without HIV in a cluster‐randomized trial of communities allowed for the examination of community‐ and individual‐level measures of HIV risk and HIV incidence. Methods: HPTN 071 (PopART) was a three‐arm cluster‐randomized trial conducted between 2013 and 2018 that evaluated the use of two combination HIV prevention strategies implemented at the community level to reduce HIV incidence compared to the standard of care. The trial, conducted in 21 communities in Zambia and South Africa, measured HIV incidence over 36 months in a population cohort of ∼2000 randomly selected adults per community aged 18–44. Multilevel models were used to assess the association between HIV incidence and community‐ and individual‐level socio‐demographic and behavioural risk factors, as well as prevalence of detectable virus (PDV) defined as the estimated proportion of the community with unsuppressed viral load. Results: Overall HIV incidence was 1.49/100 person‐years. Communities with less financial wealth and communities with more individuals reporting having sex partners outside of the community or two or more sexual partners had higher HIV incidence. PDV at 2 years of study was 6.8% and was strongly associated with HIV incidence: for every 50% relative reduction in community PDV, there was a 49% (95% confidence interval [CI]: 37%–58%, p < 0.001) relative decrease in HIV incidence. At the individual level; socio‐economic status, AUDIT score, medical male circumcision and certain sexual behaviours were associated with HIV risk. Conclusions: Using data from the PopART randomized trial, we found several associations of HIV incidence with community‐level measures reflecting the sexual behaviour and socio‐economic make‐up of each community. We also found a strong association between community PDV and HIV incidence supporting the use of PDV as a tool for monitoring progress in controlling the epidemic. Lastly, we found significant individual‐level factors of HIV risk that are generally consistent with previous HIV epidemiological research. These results have the potential to identify high high‐incidence communities, inform structural‐level interventions, and optimize individual‐level interventions for HIV prevention. Clinical Trial Number: ClinicalTrials.gov number, NCT01900977, HPTN 071 [PopArt] [ABSTRACT FROM AUTHOR]

Objective: To describe the associations between socio-economic position and prevalent tuberculosis in the 2010 ZAMSTAR Tuberculosis Prevalence Survey, one of the first large tuberculosis prevalence surveys in Southern Africa in the HIV era.Methods: The main analyses used data on 34 446 individuals in Zambia and 30 017 individuals in South Africa with evaluable tuberculosis culture results. Logistic regression was used to estimate adjusted odds ratios for prevalent TB by two measures of socio-economic position: household wealth, derived from data on assets using principal components analysis, and individual educational attainment. Mediation analysis was used to evaluate potential mechanisms for the observed social gradients.Results: The quartile with highest household wealth index in Zambia and South Africa had, respectively, 0.55 (95% CI 0.33-0.92) times and 0.70 (95% CI 0.54-0.93) times the adjusted odds of prevalent TB of the bottom quartile. College or university-educated individuals in Zambia and South Africa had, respectively, 0.25 (95% CI 0.12-0.54) and 0.42 (95% CI 0.25-0.70) times the adjusted odds of prevalent TB of individuals who had received only primary education. We found little evidence that these associations were mediated via several key proximal risk factors for TB, including HIV status.Conclusion: These data suggest that social determinants of TB remain important even in the context of generalised HIV epidemics. [ABSTRACT FROM AUTHOR]

Introduction: HIV controllers have low viral loads (VL) without antiretroviral treatment (ART). We evaluated viraemic control in a community‐randomized trial conducted in Zambia and South Africa that evaluated the impact of a combination prevention intervention on HIV incidence (HPTN 071 [PopART]; 2013–2018). Methods: VL and antiretroviral (ARV) drug testing were performed using plasma samples collected 2 years after enrolment for 4072 participants who were HIV positive at the start of the study intervention. ARV drug use was assessed using a qualitative laboratory assay that detects 22 ARV drugs in five drug classes. Participants were classified as non‐controllers if they had a VL ≥2000 copies/ml with no ARV drugs detected at this visit. Additional VL and ARV drug testing was performed at a second annual study visit to confirm controller status. Participants were classified as controllers if they had VLs <2000 with no ARV drugs detected at both visits. Non‐controllers who had ARV drugs detected at either visit were excluded from the analysis to minimize potential confounders associated with ARV drug access and uptake. Results: The final cohort included 126 viraemic controllers and 766 non‐controllers who had no ARV drugs detected. The prevalence of controllers among the 4072 persons assessed was 3.1% (95% confidence interval [CI]: 2.6%, 3.6%). This should be considered a minimum estimate, since high rates of ARV drug use in the parent study limited the ability to identify controllers. Among the 892 participants in the final cohort, controller status was associated with biological sex (female > male, p = 0.027). There was no significant association between controller status and age, study country or herpes simplex virus type 2 (HSV‐2) status at study enrolment. Conclusions: To our knowledge, this report presents the first large‐scale, population‐level study evaluating the prevalence of viraemic control and associated factors in Africa. A key advantage of this study was that a biomedical assessment was used to assess ARV drug use (vs. self‐reported data). This study identified a large cohort of HIV controllers and non‐controllers not taking ARV drugs, providing a unique repository of longitudinal samples for additional research. This cohort may be useful for further studies investigating the mechanisms of virologic control. [ABSTRACT FROM AUTHOR]

Introduction: To investigate the association between individual and community‐level measures of HIV stigma and HIV incidence within the 21 communities participating in the HPTN (071) PopART trial in Zambia and South Africa. Methods: Secondary analysis of data from a population‐based cohort followed‐up over 36 months between 2013 and 2018. The outcome was rate of incident HIV infection among individuals who were HIV negative at cohort entry. Individual‐level exposures, measured in a random sample of all participants, were: (1) perception of stigma in the community, (2) perception of stigma in health settings and (3) fear and judgement towards people living with HIV. Individual‐level analyses were conducted with adjusted, individual‐level Poisson regression. Community‐level HIV stigma exposures drew on data reported by people living with HIV, health workers and community members. We used linear regression to explore the association between HIV stigma and community‐level HIV incidence. Results: Among 8172 individuals who were HIV negative and answered individual‐level stigma questions at enrolment to the cohort, there was no evidence of a statistically significant association between any domain of HIV stigma and risk of incident HIV infection. Among the full cohort of 26,110 individuals among whom HIV incidence was measured, there was no evidence that community‐level HIV incidence was associated with any domain of HIV stigma. Conclusions: HIV stigma is often cited as a barrier to the effectiveness of HIV prevention programming. However, in the setting for the HPTN 071 "PopART trial," measured stigma alone was not associated with the risk of HIV infection. [ABSTRACT FROM AUTHOR]

Introduction: Integrating standardized measures of HIV stigma and discrimination into research studies of emerging HIV prevention approaches could enhance uptake and retention of these approaches, and care and treatment for people living with HIV (PLHIV), by informing stigma mitigation strategies. We sought to develop a succinct set of measures to capture key domains of stigma for use in research on HIV prevention technologies. Methods: From 2013 to 2015, we collected baseline data on HIV stigma from three populations (PLHIV (N = 4053), community members (N = 5782) and health workers (N = 1560)) in 21 study communities in South Africa and Zambia participating in the HPTN 071 (PopART) cluster‐randomized trial. Forty questions were adapted from a harmonized set of measures developed in a consultative, global process. Informed by theory and factor analysis, we developed seven scales, with values ranging from 0 to 3, based on a 4‐point agreement Likert, and calculated means to assess different aspects of stigma. Higher means reflected more stigma. We developed two measures capturing percentages of PLHIV who reported experiencing any stigma in communities or healthcare settings in the past 12 months. We validated our measures by examining reliability using Cronbach's alpha and comparing the distribution of responses across characteristics previously associated with HIV stigma. Results: Thirty‐five questions ultimately contributed to seven scales and two experience measures. All scales demonstrated acceptable to very good internal consistency. Among PLHIV, a scale captured internalized stigma, and experience measures demonstrated that 22.0% of PLHIV experienced stigma in the community and 7.1% in healthcare settings. Three scales for community members assessed fear and judgement, perceived stigma in the community and perceived stigma in healthcare settings. Similarly, health worker scales assessed fear and judgement, perceived stigma in the community and perceived co‐worker stigma in healthcare settings. A higher proportion of community members and health workers reported perceived stigma than the proportion of PLHIV who reported experiences of stigma. Conclusions: We developed novel, valid measures that allowed for triangulation of HIV stigma across three populations in a large‐scale study. Such comparisons will illuminate how stigma influences and is influenced by programmatic changes to HIV service delivery over time. [ABSTRACT FROM AUTHOR]