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Abstract Introduction Measuring the coverage of HIV prevention services for key populations (KPs) has consistently been a challenge for national HIV programmes. The current frameworks and measurement methods lack emphasis on effective coverage, occur infrequently, lack timeliness and limit the participation of KPs. The Effective Programme Coverage framework, which utilizes a programme science approach, provides an opportunity to assess gaps in various coverage domains and explore the underlying reasons for these gaps, in order to develop targeted solutions. We have demonstrated the application of this framework in partnership with the KP community in Nairobi, Kenya, using an expanded Polling Booth Survey (ePBS) method. Methods Data were collected between April and May 2023 among female sex workers (FSWs) and men who have sex with men (MSM) using (a) PBS, (b) bio‐behavioural survey and (c) focus group discussions. Data collection and analysis involved both KP community and non‐community researchers. Descriptive analysis was performed, and proportions were used to assess the programme coverage gaps. The data were weighted to account for the sampling design and unequal selection probabilities. Thematic analysis was conducted on the qualitative data. Results The condom programme for FSW and MSM had low availability (60.2% and 50.9%), contact (68.8% and 65.9%) and utilization (52.1% and 43.9%) coverages. The pre‐exposure prophylaxis (PrEP) programme had very low utilization coverage for FSW and MSM (4.4% and 2.8%), while antiretroviral therapy utilization coverage was higher (86.6% and 87.7%). Reasons for coverage gaps included a low peer educator‐to‐peer ratio, longer distance to the clinics, shortage of free condoms supplied by the government, experienced and anticipated side effects related to PrEP, and stigma and discrimination experienced in the facilities. Conclusions The Effective Programme Coverage framework allows programmes to assess coverage gaps and develop solutions and a research agenda targeted at specific domains of coverage with large gaps. The ePBS method works well in collecting data to understand coverage gaps rapidly and allows for the engagement of the KP community.

Abstract Background Despite policies for universal HIV testing and treatment (UTT) regardless of CD4 count, there are still 1.8 million new HIV infections and 1 million AIDS-related deaths annually. The UNAIDS 90-90-90 goals target suppression of HIV viral load in 73% of all HIV-infected people worldwide by 2030. However, achieving these targets may not lead to expected reductions in HIV incidence if the remaining 27% (persons with unsuppressed viral load) are the drivers of HIV transmission through high-risk behaviors. We aim to conduct a systematic review and meta-analysis to understand the demographics, mobility, geographic distribution, and risk profile of adults who are not virologically suppressed in sub-Saharan Africa in the era of UTT. Methods We will review the published and grey literature for study sources that contain data on demographic and behavioral strata of virologically suppressed and unsuppressed populations since 2014. We will search PubMed and Embase using four sets of search terms tailored to identify characteristics associated with virological suppression (or lack thereof) and each of the individual 90-90-90 goals. Record screening and data abstraction will be done independently and in duplicate. We will use random effects meta-regression analyses to estimate the distribution of demographic and risk features among groups not virologically suppressed and for each individual 90-90-90 goal. Discussion The results of our review will help elucidate factors associated with failure to achieve virological suppression in sub-Saharan Africa, as well as factors associated with failure to achieve each of the 90-90-90 goals. These data will help quantify the population-level effects of current HIV treatment interventions to improve strategies for maximizing virological suppression and ending the HIV epidemic. Systematic review registration PROSPERO CRD42018089505.

Objetives. To determine the prevalence of bacterial vaginosis (BV) and associated factors among 18–29-year-old women in 20 Peruvian cities using PREVEN project data. Materials and Methods. In this cross-sectional study, BV was defined using previously provided vaginal discharge samples on slides, which were Gram stained and observed under a microscope to determine the Nugent scores. A BV diagnosis was applied to samples with scores of 7–10. Prevalence ratios (PR) and 95% confidence intervals (95% CI) were estimated using generalized linear models. Results. A total of 6,322 women participated in the epidemiological survey and provided vaginal swabs. The prevalence of BV was 23.7% (95% CI: 22.6–24.7) and was associated with a greater number of sexual partners in the last 12 months (PR: 1.22, 95% CI: 1.03–1.44, p=0.020 for two partners; PR: 1.46, 95% CI: 1.23–1.74, p0.001 for three or more partners), not using a condom during last intercourse (PR: 1.16, 95% CI: 1.01–1.34, p=0.034), being a sierra resident (PR: 1.18, 95% CI: 1.05–1.31, p=0.004), and having abnormal vaginal discharge or a bad smell (PR: 1.20, 95% CI: 1.09–1.33, p0.001). Conclusions. The high prevalence of BV highlights the need to strengthen health services aimed at the detection and treatment of this condition.

In an HIV/AIDS epidemic driven primarily by heterosexual transmission, it is important to have an understanding of the human sexual behaviour patterns that influence transmission. We analysed the distribution and predictors of within-partnership sexual behaviour and condom use in rural Zimbabwe and generated parameters for use in future modelling analyses.A population-based cohort was recruited from a household census in 12 communities. A baseline survey was carried out in 1998-2000 with follow-up surveys after 3 and 5 years. Statistical distributions were fitted to reported within-partnership numbers of total, unprotected and protected sex acts in the past two weeks. Multilevel linear and logistic regression models were constructed to assess predictors of the frequency of unprotected sex and consistent condom use.A normal distribution of ln(sex acts+1) provided the best fit for total and unprotected sex acts for men and women. A negative binomial distribution applied to the untransformed data provided the best fit for protected sex acts. Condom use within partnerships was predominantly bimodal with at least 88% reporting zero or 100% use. Both men and women reported fewer unprotected sex acts with non-regular compared to regular partners (men: 0.26 fewer every two weeks (95% confidence interval 0.18-0.34); women: 0.16 (0.07-0.23)). Never and previously married individuals reported fewer unprotected sex acts than currently married individuals (never married men: 0.64 (0.60-0.67); previously married men: 0.59 (0.50-0.67); never married women: 0.51 (0.45-0.57); previously married women: 0.42 (0.37-0.47)). These variables were also associated with more consistent condom use.We generated parameters that will be useful for defining transmission models of HIV and other STIs, which rely on a valid representation of the underlying sexual network that determines spread of an infection. This will enable a better understanding of the spread of HIV and other STDs in this rural sub-Saharan population.

To explain differences in survival in the first three years of combination anti-retroviral therapy (cART) between HIV treatment centres in The Netherlands.We developed a mathematical simulation model, parameterised using data from the ATHENA cohort that describes patients entering care, being monitored and starting cART. Three scenarios were used to represent three treatment centres with widely varying mortality rates on cART that were differentiated by: (i) the distribution of CD4 counts of patients entering care; (ii) the age distribution of patients entering care; (iii) the average rate of monitoring the patients not on cART. At the level of the treatment centre, the fraction of Dutch MSM dying in the first three years of treatment ranged from 0% to 8%. The mathematical model captured the large variation in observed mortality between the three treatment centres. Manipulating the age-distribution of patients or the frequency of monitoring did not affect the model predictions. In contrast, when the same national average distribution of CD4 count at entry was used in all the scenarios, the variation in predicted mortality between all centres was diminished.Patients entering care with low CD4 counts appears to be the main source of variation in the mortality rates between Dutch treatment centres. Recruiting HIV-infected individuals to care earlier could lead to substantial improvements in cART outcomes. For example, if patients were to present with at least 400 CD4 cells/mm(3), as they do already in some centres, then our model predicts that the mortality in the first three years of cART could be reduced by approximately 20%.