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The article analyzes the scale-up of human immunodeficiency virus (HIV) antiretroviral therapy and estimation of averted infections and HIV-related deaths in Uganda from 2004 to 2022. The study calculated mother-to-child transmission (MTCT) as the number of HIV-exposed infants during pregnancy or the breastfeeding period with positive HIV test result. It estimated the number of infections and deaths averted in the absence of the President's Emergency Plan for AIDS Relief (PEPFAR)

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. [ABSTRACT FROM AUTHOR]

Large public-health training events may result in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Universal SARS-CoV-2 testing during trainings for the Uganda Population-based HIV Impact Assessment identified 28 of 475 (5.9%) individuals with coronavirus disease 2019 (COVID-19) among attendees; most (89.3%) were asymptomatic. Until COVID-19 vaccine is readily available for staff and participants, 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. [ABSTRACT FROM AUTHOR]

Background: The End TB Strategy aims to reduce new tuberculosis (TB) cases by 90% and TB-related deaths by 95% between 2015 - 2035. We determined the trend of case notification rates (CNRs) and treatment outcomes of TB cases with and without HIV co-infection in rural Uganda to provide an interim evaluation of progress towards this global target in rural settings., Methods: We extracted retrospective programmatic data on notified TB cases and treatment outcomes from 2015 - 2019 for eight districts in rural Uganda from the District Health Information System 2. We estimated CNRs as the number of TB cases per 100,000 population. Treatment success rate (TSR) was calculated as the sum of TB cure and treatment completion for each year. Trends were estimated using the Mann-Kendall test., Results: A total of 11,804 TB cases, of which 5,811 (49.2%) were HIV co-infected, were notified. The overall TB CNR increased by 3.7-fold from 37.7 to 141.3 cases per 100,000 population in 2015 and 2019 respectively. The increment was observed among people with HIV (from 204.7 to 730.2 per 100,000, p = 0.028) and HIV-uninfected individuals (from 19.9 to 78.7 per 100,000, p = 0.028). There was a decline in the TSR among HIV-negative TB cases from 82.1% in 2015 to 63.9% in 2019 (p = 0.086). Conversely, there was an increase in the TSR among HIV co-infected TB cases (from 69.9% to 81.9%, p = 0.807)., Conclusion: The CNR increased among people with and without HIV while the TSR reduced among HIV-negative TB cases. There is need to refocus programs to address barriers to treatment success among HIV-negative TB cases., (© 2022. The Author(s).)