Abstract

IntroductionHeterogeneity of sociodemographics and risk behaviours across the HIV treatment cascade could influence the public health impact of universal ART in sub‐Saharan Africa if those not virologically suppressed are more likely to be part of a risk group contributing to onward infections. Sociodemographic and risk heterogeneity across the treatment cascade has not yet been comprehensively described or quantified and we seek to systematically review and synthesize research on this topic among adults in Africa.MethodsWe conducted a systematic review of peer‐reviewed literature in Embase and MEDLINE databases as well as grey literature sources published in English between 2014 and 2018. We included studies that included people living with HIV (PLHIV) aged ≥15 years, and reported a 90‐90‐90 outcome: awareness of HIV‐positive status, ART use among those diagnosed or viral suppression among those on ART. We summarized measures of association between sociodemographics, within each outcome, and as a composite measure of population‐wide viral suppression.Results and discussionFrom 3533 screened titles, we extracted data from 92 studies (50 peer‐reviewed, 42 grey sources). Of included studies, 32 reported on awareness, 53 on ART use, 32 on viral suppression and 23 on population‐wide viral suppression. The majority of studies were conducted in South Africa, Uganda, and Malawi and reported data for age and gender. When stratified, PLHIV ages 15 to 24 years had lower median achievement of the treatment cascade (60‐49‐81), as compared to PLHIV ≥25 years (70‐63‐91). Men also had lower median achievement of the treatment cascade (66‐72‐85), compared to women (79‐76‐89). For population‐wide viral suppression, women aged ≥45 years had achieved the 73% target, while the lowest medians were among 15‐ to 24‐year‐old men (37%) and women (49%).ConclusionsConsiderable heterogeneity exists by age and gender for achieving the HIV 90‐90‐90 treatment goals. These results may inform delivery of HIV testing and treatment in sub‐Saharan Africa, as targeting youth and men could be a strategic way to maximize the population‐level impact of ART.

Highlights

  • Heterogeneity of sociodemographics and risk behaviours across the HIV treatment cascade could influence the public health impact of universal antiretroviral therapy (ART) in sub‐Saharan Africa if those not virologically suppressed are more likely to be part of a risk group contributing to onward infections

  • In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS) introduced the 90‐90‐90 goals as targets for achieving viral load suppression among people living with HIV (PLHIV) by 2020 [1]

  • Assessing the association of diagnosis, ART use and viral suppression with risk behaviour and sociodemographic factors will allow for a better understanding of the population‐level effectiveness of universal testing and treatment (UTT) in reducing HIV incidence, and provide a focus for improving programmes

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Summary

| INTRODUCTION

In 2014, the Joint United Nations Programme on HIV/AIDS (UNAIDS) introduced the 90‐90‐90 goals as targets for achieving viral load suppression among people living with HIV (PLHIV) by 2020 [1]. Given the mixed results from recent cluster randomized trials of the population‐level effect of UTT on incidence declines and observed ongoing HIV incidence across populations, the UTT strategy and 90‐90‐90 goals may not be reaching all PLHIV [4,5,6]. Models to date have not parameterized the treatment cascade as a function of risk based on empirical observations, despite some evidence that PLHIV who are not receiving ART or achieving viral load suppression are younger, male, highly mobile, and exhibit more risky sexual behaviour, and are more likely to transmit HIV to others [13]. Assessing the association of diagnosis, ART use and viral suppression with risk behaviour and sociodemographic factors will allow for a better understanding of the population‐level effectiveness of UTT in reducing HIV incidence, and provide a focus for improving programmes. The exposures of interest were selected a priori and included the following: age, gender, geography, urban/rural residence, occupation, distance from facility, relationship status, age at sexual debut, recency of infection, CD4 count, education, income or wealth, migration status, mobility (i.e. time spent away from residence), mental health, identification with a key or priority population group (pregnant women, discordant couples, people who inject drugs, transactional/commercial sex workers, gay, bisexual and other men who have sex with men, and transgender individuals) and sexual risk behaviours (number of concurrent partners, condom‐use, age‐discordant relationships)

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