Suchergebnisse

AbstractIntroductionEast African cross‐border areas are visited by mobile and vulnerable populations, such as men, female sex workers, men who have sex with men, truck drivers, fisher folks and young women. These groups may not benefit from traditional HIV prevention interventions available at the health facilities where they live, but may benefit from services offered at public venues identified as places where people meet new sexual partners (e.g. bars, nightclubs, transportation hubs and guest houses). The goal of this analysis was to estimate availability, access and uptake of prevention services by populations who visit these venues.MethodsWe collected cross‐sectional data using the Priorities for Local AIDS Control Efforts sampling method at cross‐border locations near or along the land and lake borders of Kenya, Rwanda, Tanzania and Uganda from June 2016–February 2017. This bio‐behavioural survey captured information from a probability sample of 11,428 individuals at 833 venues across all areas. Data were weighted using survey sampling weights and analysed using methods to account for the complex sampling design.ResultsAmong the 85.6% of persons who had access to condoms, 60.5% did not use a condom at their last anal or vaginal sexual encounter. Venues visited by high percentages of persons living with HIV were not more likely than other venues to offer condoms. In 12 of the 22 cross‐border areas, male or female condoms were available at less than 33% of the venues visited by persons having difficulty accessing condoms. In 17 of the 22 cross‐border areas, education outreach visits in the preceding six months occurred at less than 50% of the venues where participants had low effective use of condoms.ConclusionsIndividuals visiting venues in cross‐border areas report poor access to and low effective use of condoms and other prevention services. Availability of HIV prevention services differed by venue and population type and cross‐border area, suggesting opportunities for more granular targeting of HIV prevention interventions and transnational coordination of HIV programming.

AbstractIntroductionHIV care and treatment in cross‐border areas in East Africa face challenges perhaps not seen to the same extent in other geographic areas, particularly for mobile and migrant populations. Here, we estimate the proportion of people with HIV found in these cross‐border areas in each stage of the HIV care and treatment cascade, including the proportion who knows their status, the proportion on treatment and the proportion virally suppressed.MethodsParticipants (n = 11,410) working or socializing in public places in selected East Africa cross border areas were recruited between June 2016 and February 2017 using the Priorities for Local AIDS Control Efforts method and administered a behavioural survey and rapid HIV test. This approach was designed to recruit a stratified random sample of people found in public spaces or venues in each cross border area. For participants testing positive for HIV, viral load was measured from dried blood spots. The proportion in each step of the cascade was estimated using inverse probability weights to account for the sampling design and informative HIV test refusals. Estimates are reported separately for residents of the cross border areas and non‐residents found in those areas.ResultsOverall, 43% of participants with HIV found in cross‐border areas knew their status, 87% of those participants were on antiretroviral therapy (ART), and 80% of participants on ART were virally suppressed. About 20% of people with HIV found in cross border areas were sampled outside their subdistrict or subcounty of residence. While both resident and non‐resident individuals who knew their status were likely to be on ART (85% and 96% respectively), people on ART recruited outside their area of residence were less likely to be suppressed (64% suppressed; 95% CI: 43, 81) compared to residents (84% suppressed; 95% CI: 75, 93).ConclusionsPeople living in or travelling through cross‐border areas may face barriers in learning their HIV status. Moreover, while non‐residents were more likely to be on treatment than residents, they were less likely to be suppressed, suggesting gaps in continuity of care for people in East Africa travelling outside their area of residence despite timely initiation of treatment.

AbstractIntroductionThe HIV Prevention 2025 Roadmap, developed by UNAIDS, recommends the adoption of a precision prevention approach focused on priority populations and geographies. With reduction in new HIV acquisitions in many countries, designing a differentiated HIV prevention response, using a Programme Science approach, based on the understanding of the epidemic and transmission dynamics at a sub‐national level, is critical.MethodsTo support strategic planning, an epidemic appraisal at the sub‐national level across 47 counties, with the 2019 population ranging from 0.14 million in Lamu to 4.40 million in Nairobi City, was conducted in Kenya using several existing data sources. Using 2021 Spectrum/EPP/Naomi model estimates of national and sub‐national HIV incidence and prevalence, counties with high HIV incidence and prevalence were identified for geographic prioritization. The size of local key population (KP) networks and HIV prevalence in key and general populations were used to define epidemic typology and prioritize populations for HIV prevention programmes. Analysis of routine programme monitoring data for 2021 was used to assess coverage gaps in HIV prevention programmes, including prevention of vertical transmission, anti‐retroviral therapy, KP programmes, adolescent girls and young women programme, and voluntary male medical circumcision programme.ResultsTen counties with more than 1000 incident acquisitions in 2021 accounted for 57% of new acquisitions. Twenty‐four counties were grouped into the concentrated epidemic type—due to their low prevalence in the general population, high prevalence in KPs and relatively higher density of female sex workers and men who have sex with men populations. Four counties reflected a generalized epidemic, where HIV prevalence was more than 10% and 30%, respectively, among the general and key populations. The remaining 19 counties were classified as having mixed epidemics. Gaps in programmes were identified and counties where these gaps need to be addressed were also prioritized.ConclusionsThe HIV burden in Kenya is unevenly distributed and hence the mix of prevention strategies may vary according to the epidemic typology of the county. Prioritization of programmes based not only on disease burden and epidemic typology, but also on the prevailing gaps in coverage for reducing inequities is a key aspect of this appraisal.

AbstractIntroductionMeasuring 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.MethodsData 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.ResultsThe 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.ConclusionsThe 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.