Background Overall increases in the uptake of HIV testing in the past two decades might hide discrepancies across socioeconomic groups. We used data from population-based surveys done in sub-Saharan Africa to quantify socioeconomic inequalities in uptake of HIV testing, and to establish trends in testing uptake in the past two decades.Methods We analysed data from 16 countries in sub-Saharan Africa where at least one Demographic and Health Survey was done before and after 2008. We assessed the country-specific and sex-specific proportions of participants who had undergone HIV testing in the previous 12 months across wealth and education groups, and quantified socioeconomic inequalities with both the relative and slope indices of inequalities. We assessed time trends in inequalities, and calculated mean results across countries with random-effects meta-analyses.

Objectives: Socioeconomic inequalities in HIV prevention services coverage constitute important barriers to global prevention targets, especially in sub-Saharan Africa (SSA). We aimed at monitoring these inequalities from population-based survey data in 18 SSA countries between 2010 and 2018.Methods: We defined eight HIV indicators aimed at capturing uptake of HIV prevention services among adult participants. Country-specific wealth-related inequalities were measured using the Relative and Slope Index of Inequalities (RII and SII, respectively) and then pooled using random-effects meta-analyses. We compared inequalities between African regions using the Wilcoxon rank-sum test. Results:The sample consisted of 358 591 participants (66% women). Despite variability between countries and indicators, the meta-analysis revealed significant levels of relative and absolute inequalities in six out of eight indicators: HIV-related knowledge, positive attitudes toward people with HIV (PWH), condom use at last sexual intercourse, participation to prevention of mother-to-child transmission programs, medical male circumcision and recent HIV testing. The largest inequalities were reported in condom use, with condom use reported five times more among the richest versus the poorest [RII ¼ 5.02, 95% confidence interval (CI) 2.79-9.05] and in positive attitudes toward PWH, with a 32-percentage point difference between the richest and poorest (SII ¼ 0.32, 95% CI 0.26-0.39). Conversely, no significant inequalities were observed in multipartnership and HIV seropositivity among youth. Overall, inequalities tended to be larger in West and Central vs. East and Southern African countries. Conclusion:Despite efforts to scale-up HIV-prevention programs, socioeconomic inequalities remain substantial over the continuum of HIV primary and secondary prevention in several SSA countries.

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