We report that unsuccessful treatment outcomes were 11.8% for tuberculosis (TB) disease and 21.8% for TB infection among persons deprived of liberty in Uganda Prisons Service facilities. Remedial efforts should include enhancing referral networks to ensure treatment continuity, strengthening data systems for complete outcome documentation, and prioritizing short-course treatment regimens.

INTRODUCTION: Population-based biomarker surveys are the gold standard for estimating HIV prevalence but are susceptible to substantial non-participation (up to 30%). Analytical missing data methods, including inverse-probability weighting (IPW) and multiple imputation (MI), are biased when data are missing-not-at-random, for example when people living with HIV more frequently decline participation. Heckman-type selection models can, under certain assumptions, recover unbiased prevalence estimates in such scenarios. METHODS: We pooled data from 142,706 participants aged 15-49 years from nationally representative cross-sectional Population-based HIV Impact Assessments in seven countries in sub-Saharan Africa, conducted between 2015 and 2018 in Tanzania, Uganda, Malawi, Zambia, Zimbabwe, Lesotho and Eswatini. We compared sex-stratified HIV prevalence estimates from unadjusted, IPW, MI and selection models, controlling for household and individual-level predictors of non-participation, and assessed the sensitivity of selection models to the copula function specifying the correlation between study participation and HIV status. RESULTS: In total, 84.1% of participants provided a blood sample to determine HIV serostatus (range: 76% in Malawi to 95% in Uganda). HIV prevalence estimates from selection models diverged from IPW and MI models by up to 5% in Lesotho, without substantial precision loss. In Tanzania, the IPW model yielded lower HIV prevalence estimates among males than the best-fitting copula selection model (3.8% vs. 7.9%). CONCLUSIONS: We demonstrate how HIV prevalence estimates from selection models can differ from those obtained under missing-at-random assumptions. Further benefits include exploration of plausible relationships between participation and outcome. While selection models require additional assumptions and careful specification, they are an important tool for triangulating prevalence estimates in surveys with substantial missing data due to non-participation.

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.

Large public-health training events may result in SARS-CoV-2 transmission. Universal SARS-CoV-2 testing during trainings for the Uganda Population-based HIV Impact Assessment identified 28/475 (5.9%) individuals with COVID-19 among attendees; most (89.3%) were asymptomatic. Effective COVID-19 mitigation measures, along with SARS-CoV-2 testing, are recommended for in-person trainings, particularly when trainees will have subsequent contact with survey participants.

BACKGROUND: Male circumcision (MC) offers men lifelong partial protection from heterosexually-acquired HIV infection. The impact of MC on HIV incidence has not been quantified in nationally-representative samples. Data from the Population-based HIV Impact Assessments (PHIAs) were used to compare incidence by MC status in countries implementing voluntary medical MC (VMMC) programs. METHODS: Data were pooled from PHIAs conducted in Eswatini, Lesotho, Malawi, Namibia, Tanzania, Uganda, Zambia and Zimbabwe from 2015-2017. Incidence was measured using a recent infection testing algorithm, and analyzed by self-reported MC status distinguishing between medical and non-medical MC. Country, marital status, urban setting, sexual risk behaviors, and mean population HIV viral load among women as an indicator of treatment scale-up were included in a random effects logistic regression model using pooled survey weights. Analyses were age-stratified (15-34 and 35-59 years). Annualized incidence rates and 95% confidence intervals (CIs) and incidence differences were calculated between medically circumcised and uncircumcised men. RESULTS: Men 15-34 years reporting medical MC had lower HIV incidence than uncircumcised men (0.04% [95% CI: 0.00, 0.10%] versus 0.34% [95% CI: 0.10, 0.57%], respectively; p-value = 0.01); whereas among men 35-59 years, there was no significant incidence difference (1.36% [95% CI: 0.32, 2.39%] versus 0.55% [95% CI: 0.14, 0.67%], respectively; p-value = 0.14). DISCUSSION: Medical MC was associated with lower HIV incidence in men aged 15-34 years in nationally-representative surveys in Africa. These findings are consistent with the expected ongoing VMMC program impact and highlight the importance of VMMC for the HIV response in Africa.

BACKGROUND: Remarkable success in the prevention and treatment of pediatric HIV infection has been achieved in the past decade. Large differences remain between the estimated number of children living with HIV (CLHIV) and those identified through national HIV programs. We evaluated the number of CLHIV and those on treatment in Lesotho, Malawi, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. METHODS: We assessed the total number of CLHIV, CLHIV on antiretroviral treatment (ART), and national and regional ART coverage gaps using 3 data sources: (1) Joint United Nations Programme on HIV/AIDS model-based estimates and national program data used as input values in the models, (2) population-based HIV impact surveys (PHIA), and (3) program data from the President's Emergency Plan for AIDS Relief (PEPFAR)-supported clinics. RESULTS: Across the 7 countries, HIV prevalence among children aged 0-14 years ranged from 0.4% (Uncertainty Bounds (UB) 0.2%-0.6%) to 2.8% (UB: 2.2%-3.4%) according to the PHIA surveys, resulting in estimates of 520,000 (UB: 460,000-580,000) CLHIV in 2016-2017 in the 7 countries. This compared with Spectrum estimates of pediatric HIV prevalence ranging from 0.5% (UB: 0.5%-0.6%) to 3.5% (UB: 3.0%-4.0%) representing 480,000 (UB: 390,000-550,000) CLHIV. CLHIV not on treatment according to the PEPFAR, PHIA, and Spectrum for the countries stood at 48% (UB: 25%-60%), 49% (UB: 37%-50%), and 38% (UB: 24%-47%), respectively. Of 78 regions examined across 7 countries, 33% of regions (PHIA data) or 41% of regions (PEPFAR data) had met the ART coverage target of 81%. CONCLUSIONS: There are substantial gaps in the coverage of HIV treatment in CLHIV in the 7 countries studied according to all sources. There is continued need to identify, engage, and treat infants and children. Important inconsistencies in estimates across the 3 sources warrant in-depth investigation.