BACKGROUND: We examined the epidemiology and transmission potential of HIV population viral load (VL) in 12 sub-Saharan African countries. METHODS: We analyzed data from Population-based HIV Impact Assessments (PHIAs), large national household-based surveys conducted between 2015 and 2019 in Cameroon, Cote d'Ivoire, Eswatini, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe. Blood-based biomarkers included HIV serology, recency of HIV infection, and VL. We estimated the number of people living with HIV (PLHIV) with suppressed viral load (<1,000 HIV-1 RNA copies/mL) and with unsuppressed viral load (viremic), the prevalence of unsuppressed HIV (population viremia), sex-specific HIV transmission ratios (number female incident HIV-1 infections/number unsuppressed male PLHIV per 100 persons-years [PY] and vice versa) and examined correlations between a variety of VL metrics and incident HIV. Country sample sizes ranged from 10,016 (Eswatini) to 30,637 (Rwanda); estimates were weighted and restricted to participants 15 years and older. RESULTS: The proportion of female PLHIV with viral suppression was higher than that among males in all countries, however, the number of unsuppressed females outnumbered that of unsuppressed males in all countries due to higher overall female HIV prevalence, with ratios ranging from 1.08 to 2.10 (median: 1.43). The spatial distribution of HIV seroprevalence, viremia prevalence, and number of unsuppressed adults often differed substantially within the same countries. The 1% and 5% of PLHIV with the highest VL on average accounted for 34% and 66%, respectively, of countries' total VL. HIV transmission ratios varied widely across countries and were higher for male-to-female (range: 2.3-28.3/100 PY) than for female-to-male transmission (range: 1.5-10.6/100 PY). In all countries mean log10 VL among unsuppressed males was higher than that among females. Correlations between VL measures and incident HIV varied, were weaker for VL metrics among females compared to males and were strongest for the number of unsuppressed PLHIV per 100 HIV-negative adults (R2 = 0.92). CONCLUSIONS: Despite higher proportions of viral suppression, female unsuppressed PLHIV outnumbered males in all countries examined. Unsuppressed male PLHIV have consistently higher VL and a higher risk of transmitting HIV than females. Just 5% of PLHIV account for almost two-thirds of countries' total VL. Population-level VL metrics help monitor the epidemic and highlight key programmatic gaps in these African countries.

BACKGROUND: HIV-1 incidence calculation currently includes recency classification by HIV-1 incidence assay and unsuppressed viral load (VL ≥ 1000 copies/mL) in a recent infection testing algorithm (RITA). However, persons with recent classification not virally suppressed and taking antiretroviral (ARV) medication may be misclassified. SETTING: We used data from 13 African household surveys to describe the impact of an ARV-adjusted RITA on HIV-1 incidence estimates. METHODS: HIV-seropositive samples were tested for recency using the HIV-1 Limiting Antigen (LAg)-Avidity enzyme immunoassay, HIV-1 viral load, ARVs used in each country, and ARV drug resistance. LAg-recent result was defined as normalized optical density values ≤1.5. We compared HIV-1 incidence estimates using 2 RITA: RITA1: LAg-recent + VL ≥ 1000 copies/mL and RITA2: RITA1 + undetectable ARV. We explored RITA2 with self-reported ARV use and with clinical history. RESULTS: Overall, 357 adult HIV-positive participants were classified as having recent infection with RITA1. RITA2 reclassified 55 (15.4%) persons with detectable ARV as having long-term infection. Those with detectable ARV were significantly more likely to be aware of their HIV-positive status (84% vs. 10%) and had higher levels of drug resistance (74% vs. 26%) than those without detectable ARV. RITA2 incidence was lower than RITA1 incidence (range, 0%-30% decrease), resulting in decreased estimated new infections from 390,000 to 341,000 across the 13 countries. Incidence estimates were similar using detectable or self-reported ARV (R2 > 0.995). CONCLUSIONS: Including ARV in RITA2 improved the accuracy of HIV-1 incidence estimates by removing participants with likely long-term HIV infection.

BACKGROUND: Identifying men living with HIV in sub-Saharan Africa (SSA) is critical to end the epidemic. We describe the underlying factors of unawareness among men aged 15-59 years who ever tested for HIV in 13 SSA countries. METHODS: Using pooled data from the nationally representative Population-based HIV Impact Assessments, we fit a log-binomial regression model to identify characteristics related to HIV positivity among HIV-positive unaware and HIV-negative men ever tested for HIV. RESULTS: A total of 114,776 men were interviewed and tested for HIV; 4.4% were HIV-positive. Of those, 33.7% were unaware of their HIV-positive status, (range: 20.2%-58.7%, in Rwanda and Cote d'Ivoire). Most unaware men reported they had ever received an HIV test (63.0%). Age, region, marital status, and education were significantly associated with HIV positivity. Men who had HIV-positive sexual partners (adjusted prevalence ratio [aPR]: 5.73; confidence interval [95% CI]: 4.13 to 7.95) or sexual partners with unknown HIV status (aPR: 2.32; 95% CI: 1.89 to 2.84) were more likely to be HIV-positive unaware, as were men who tested more than 12 months compared with HIV-negative men who tested within 12 months before the interview (aPR: 1.58; 95% CI: 1.31 to 1.91). Tuberculosis diagnosis and not being circumcised were also associated with HIV positivity. CONCLUSION: Targeting subgroups of men at risk for infection who once tested negative could improve yield of testing programs. Interventions include improving partner testing, frequency of testing, outreach and educational strategies, and availability of HIV testing where men are accessing routine health services.

OBJECTIVES: Achieving the Sustainable Development Goals will require data-driven public health action. There are limited publications on national health information systems that continuously generate health data. Given the need to develop these systems, we summarised their current status in low-income and middle-income countries. SETTING: The survey team jointly developed a questionnaire covering policy, planning, legislation and organisation of case reporting, patient monitoring and civil registration and vital statistics (CRVS) systems. From January until May 2017, we administered the questionnaire to key informants in 51 Centers for Disease Control country offices. Countries were aggregated for descriptive analyses in Microsoft Excel. RESULTS: Key informants in 15 countries responded to the questionnaire. Several key informants did not answer all questions, leading to different denominators across questions. The Ministry of Health coordinated case reporting, patient monitoring and CRVS systems in 93% (14/15), 93% (13/14) and 53% (8/15) of responding countries, respectively. Domestic financing supported case reporting, patient monitoring and CRVS systems in 86% (12/14), 75% (9/12) and 92% (11/12) of responding countries, respectively. The most common uses for system-generated data were to guide programme response in 100% (15/15) of countries for case reporting, to calculate service coverage in 92% (12/13) of countries for patient monitoring and to estimate the national burden of disease in 83% (10/12) of countries for CRVS. Systems with an electronic component were being used for case reporting, patient monitoring, birth registration and death registration in 87% (13/15), 92% (11/12), 77% (10/13) and 64% (7/11) of responding countries, respectively. CONCLUSIONS: Most responding countries have a solid foundation for policy, planning, legislation and organisation of health information systems. Further evaluation is needed to assess the quality of data generated from systems. Periodic evaluations may be useful in monitoring progress in strengthening and harmonising these systems over time.