Abstract While multi-level theories and frameworks have become a cornerstone in broader efforts to address HIV inequities, little is known regarding their application in adolescent and young adult (AYA) HIV research. To address this gap, we conducted a scoping review to assess the use and application of multi-level theories and frameworks in AYA HIV prevention and care and treatment empirical research. We systematically searched five databases for articles published between 2010 and May 2020, screened abstracts, and reviewed eligible full-text articles for inclusion. Of the 5890 citations identified, 1706 underwent full-text review and 88 met the inclusion criteria: 70 focused on HIV prevention, with only 14 on care and treatment, 2 on both HIV prevention and care and treatment, and 2 on HIV-affected AYA. Most authors described the theory-based multi-level framework as informing their data analysis, with only 12 describing it as informing/guiding an intervention. More than seventy different multi-level theories were described, with 38% utilizing socio-ecological models or the eco-developmental theory. Findings were used to inform the adaptation of an AYA World Health Organization multi-level framework specifically to guide AYA HIV research.
Physical, social, economic, and political environments can increase harm and risk among people who use drugs. These factors may be exacerbated in urban environments with a history of systemic inequality toward African Americans. However, racialized risk environment models have rarely been used within substance use research. To fill this gap, the current qualitative study sought to describe the racialized risk environment of an African American sample of 21 adults with a history of illicit drug use living in Baltimore, MD. Semi-structured interviews were conducted. Data were analyzed using qualitative content analysis to identify themes related to illicit drug use, neighborhood context, violence, social interactions, and income generation. Themes related to the physical (e.g., the increased visibility of drug markets), social (e.g., normalization of drug use within social networks), and economic (e.g., financial hardships) risk environments emerged from this sample. These perceptions and themes can aid in developing and refining substance use programming within racialized settings.
In South Africa, there is no centralized HIV surveillance system where key populations (KPs) data, including gay men and other men who have sex with men, female sex workers, transgender persons, people who use drugs, and incarcerated persons, are stored in South Africa despite being on higher risk of HIV acquisition and transmission than the general population. Data on KPs are being collected on a smaller scale by numerous stakeholders and managed in silos. There exists an opportunity to harness a variety of data, such as empirical, contextual, observational, and programmatic data, for evaluating the potential impact of HIV responses among KPs in South Africa. This study aimed to leverage and harness big heterogeneous data on HIV among KPs and harmonize and analyze it to inform a targeted HIV response for greater impact in Sub-Saharan Africa. The Boloka data repository initiative has 5 stages. There will be engagement of a wide range of stakeholders to facilitate the acquisition of data (stage 1). Through these engagements, different data types will be collated (stage 2). The data will be filtered and screened to enable high-quality analyses (stage 3). The collated data will be stored in the Boloka data repository (stage 4). The Boloka data repository will be made accessible to stakeholders and authorized users (stage 5). The protocol was funded by the South African Medical Research Council following external peer reviews (December 2022). The study received initial ethics approval (May 2022), renewal (June 2023), and amendment (July 2024) from the University of Johannesburg (UJ) Research Ethics Committee. The research team has been recruited, onboarded, and received non-web-based internet ethics training (January 2023). A list of current and potential data partners has been compiled (January 2023 to date). Data sharing or user agreements have been signed with several data partners (August 2023 to date). Survey and routine data have been and are being secured (January 5, 2023). In (September 2024) we received Ghana Men Study data. The data transfer agreement between the Pan African Centre for Epidemics Research and the Perinatal HIV Research Unit was finalized (October 2024), and we are anticipating receiving data by (December 2024). In total, 7 abstracts are underway, with 1 abstract completed the analysis and expected to submit the full article to the peer-reviewed journal in early January 2024. As of March 2025, we expect to submit the remaining 6 full articles. A truly "complete" data infrastructure that systematically and rigorously integrates diverse data for KPs will not only improve our understanding of local epidemics but will also improve HIV interventions and policies. Furthermore, it will inform future research directions and become an incredible institutional mechanism for epidemiological and public health training in South Africa and Sub-Saharan Africa. DERR1-10.2196/63583.
Key population HIV programmes in sub-Saharan Africa require epidemiological information to ensure equitable and universal access to effective services. We aimed to consolidate and harmonise survey data among female sex workers, men who have sex with men, people who inject drugs, and transgender people to estimate key population size, HIV prevalence, and antiretroviral therapy (ART) coverage for countries in mainland sub-Saharan Africa.
Abstract Background Key population HIV programmes in sub-Saharan Africa (SSA) require epidemiologic information to ensure equitable and universal access to effective services. We consolidated survey data among female sex workers (FSW), gay men and other men who have sex with men (MSM), people who inject drugs (PWID), and transgender people to estimate key population size, HIV prevalence, and antiretroviral therapy (ART) coverage for countries in mainland SSA. Methods Key population size estimates (KPSE), HIV prevalence, and ART coverage data from 39 SSA countries between 2010-2023 were collated from existing databases and verified against source documents. We used Bayesian mixed-effects spatial regression to model urban KPSE as a proportion of the gender/year/area-matched 15-49 years adult population. We modelled subnational key population HIV prevalence and ART coverage with age/gender/year/province-matched total population estimates as predictors. Findings We extracted 2065 key population size, 1183 HIV prevalence, and 259 ART coverage data points. Across national urban populations, a median of 1.65% of adult cisgender women were FSW (interquartile range [IQR]=1.35-1.91%), 0.89% of men were MSM (IQR=0.77-0.95%), 0.32% of men injected drugs (IQR=0.31-0.34%), and 0.10% of women were transgender (IQR=0.06-0.12%). HIV prevalence among key populations was, on average, 4 to 6 times higher than matched total population prevalence, and ART coverage was correlated with, but lower than, total population ART coverage with wide heterogeneity in relative ART coverage across studies. Across SSA, key populations were estimated as 1.2% (95% credible interval [CrI]: 0.9, 1.6) of the total population aged 15-49 years but 6.1% (95% CrI: 4.5, 8.2) of people living with HIV. Interpretation Key populations in SSA experience higher HIV prevalence and lower ART coverage, underscoring the need for focused prevention and treatment services. In 2024, limited data availability and heterogeneity constrain precise estimates for programming and monitoring trends. Strengthening key population surveys and routine data within national HIV strategic information systems would support more precise estimates. Funding UNAIDS, BMGF, NIH Research in Context Evidence before this study Key populations, including female sex workers (FSW), gay men and other men who have sex with men (MSM), people who inject drugs (PWID), and transgender people, are at higher risk of HIV infection, including in sub-Saharan Africa (SSA). Delivering appropriate HIV prevention and treatment services for key populations and monitoring an equitable HIV response requires robust information on key population size, HIV prevalence, the treatment cascade, and new HIV infections. For this reason, key population surveys, including population size estimation and bio-behavioural surveys, are a standard component of comprehensive national HIV surveillance. Several complementary ongoing initiatives consolidate HIV data on key populations to support programme planning and implementation, global advocacy, and research. These include the Key Population Atlas and Global AIDS Monitoring (Joint United Nations Programme on HIV/AIDS [UNAIDS]), databases maintained by the US Centers for Disease Control and Prevention (CDC) and The Global Fund to Fight AIDS, Tuberculosis and Malaria (The Global Fund), and the Global.HIV initiative (Johns Hopkins University). These include similar data sources, but vary in scope, inclusion criteria, data elements recorded, and linkage to and validation against primary source reports. Incomplete recording of key methodological details limits appraisal and formal evidence synthesis, and therefore utility of data for strategic planning. Many other research studies have systematically reviewed, analysed, and extrapolated key population survey data in sub-Saharan Africa in single countries or across multiple countries. These studies have tended to focus on specific outcomes or population groups of interest, and primarily comprise an appraisal of peer-reviewed literature. Added value of this study We consolidated and deduplicated data collected between 2010-2023 from existing key population survey databases maintained by the UNAIDS Key Population Atlas, UNAIDS Global AIDS Monitoring, US CDC, and the Global Fund. We obtained published and grey literature surveillance reports from the Johns Hopkins University Global.HIV repository, additional web-based searches, and engagement with country HIV strategic information teams, and validated each observation of key population size, HIV prevalence, or ART coverage against primary surveillance reports. We used regression to characterise the relationship between key population and total population HIV indicators and extrapolated key population size estimates (KPSE), HIV prevalence, and ART coverage data to national-level estimates for all countries in mainland SSA. This exercise was the most comprehensive effort to date to consolidate key population HIV data in SSA. We analysed over 3000 observations from 126 KPSE, 217 HIV prevalence, and 62 ART coverage studies. We estimated that across urban populations aged 15-49 years in SSA countries, a median of 1.65% of cisgender women were FSW; 0.89% of men have sex with men; 0.32% of men injected drugs; and 0.10% of women were transgender. This translated to 3.7 million FSW, 1.9 million MSM, 770,000 PWID, and 230,000 transgender women (TGW) in SSA who require comprehensive HIV prevention or treatment services. FSW, MSM, PWID, and TGW together were estimated as 1.2% of the population aged 15-49 years, but comprised 6.1% of people living with HIV. ART coverage among members of key populations living with HIV increased with total population ART coverage, but was lower for all key populations. We identified large gaps in data availability. Of the four key populations and three indicators studied, only Mozambique had data for all twelve indicators. Data were particularly sparse for transgender populations and PWID. Implications of all the available evidence Key populations experience higher HIV prevalence and lower ART coverage across all settings in sub-Saharan Africa than the total population. Extrapolated national estimates provide a foundation for planning appropriate key population-focused services for HIV prevention and treatment in all settings, including those with no or limited data. However, large data availability gaps driven by discriminatory practices and punitive policies against key populations, inconsistency of existing data, and consequent wide uncertainty ranges around estimates limit the ability of existing data to guide granular programmatic planning and target setting for key population services and to monitor trends. More consistent surveillance implementation and improved routine surveillance through HIV prevention and treatment programmes for key populations would support monitoring equitable and equal programme access, as outlined in the Global AIDS Strategy 2021-2026 developed by UNAIDS, its co-sponsors, and other partners to end HIV/AIDS as a public health threat by 2030.
BACKGROUND Estimating the size of key populations, including female sex workers (FSW) and men who have sex with men (MSM), can inform planning and resource allocation for HIV programs at local and national levels. In geographic areas where direct population size estimates (PSEs) for key populations have not been collected, small area estimation (SAE) can help fill in gaps using supplemental data sources known as auxiliary data. However, routinely collected program data have not historically been used as auxiliary data to generate subnational estimates for key populations, including in Namibia. OBJECTIVE To systematically generate regional size estimates for FSW and MSM in Namibia, we used a consensus-informed estimation approach with local stakeholders that included the integration of routinely collected HIV program data provided by key populations’ HIV service providers. METHODS We used quarterly program data reported by key population implementing partners, including counts of the number of individuals accessing HIV services over time, to weight existing PSEs collected through bio-behavioral surveys using a Bayesian triangulation approach. SAEs were generated through simple imputation, stratified imputation, and multivariable Poisson regression models. We selected final estimates using an iterative qualitative ranking process with local key population implementing partners. RESULTS Extrapolated national estimates for FSW ranged from 4777 to 13,148 across Namibia, comprising 1.5% to 3.6% of female individuals aged between 15 and 49 years. For MSM, estimates ranged from 4611 to 10,171, comprising 0.7% to 1.5% of male individuals aged between 15 and 49 years. After the inclusion of program data as priors, the estimated proportion of FSW derived from simple imputation increased from 1.9% to 2.8%, and the proportion of MSM decreased from 1.5% to 0.75%. When stratified imputation was implemented using HIV prevalence to inform strata, the inclusion of program data increased the proportion of FSW from 2.6% to 4.0% in regions with high prevalence and decreased the proportion from 1.4% to 1.2% in regions with low prevalence. When population density was used to inform strata, the inclusion of program data also increased the proportion of FSW in high-density regions (from 1.1% to 3.4%) and decreased the proportion of MSM in all regions. CONCLUSIONS Using SAE approaches, we combined epidemiologic and program data to generate subnational size estimates for key populations in Namibia. Overall, estimates were highly sensitive to the inclusion of program data. Program data represent a supplemental source of information that can be used to align PSEs with real-world HIV programs, particularly in regions where population-based data collection methods are challenging to implement. Future work is needed to determine how best to include and validate program data in target settings and in key population size estimation studies, ultimately bridging research with practice to support a more comprehensive HIV response.
The objectives of this study are to (1) characterize patterns of preventive behaviors 3 months after the COVID-19 pandemic was declared a national emergency in the USA and (2) identify how health beliefs (e.g., perceived risk of infection, perceived risk of death upon infection, and perceived effectiveness of CDC-recommended preventive behaviors) and sociodemographic characteristics are associated with preventive behaviors. Data were obtained from two waves of the Understanding America Study (UAS) conducted in March (wave 1) and May to June of 2020 (wave 2) (n = 4445); UAS is a nationally representative panel of US adults. We conducted a latent class analysis (LCA) using wave 2 data to identify our outcome, patterns of 10 COVID-preventive behaviors (e.g., wearing a facemask, handwashing, social distancing), and then used a three-step regression (R3STEP) to test associations between the likelihood of class membership with (1) health beliefs and sociodemographic characteristics (age, sex, race/ethnicity, and educational attainment) in bivariate models and (2) health beliefs adjusted for sociodemographic characteristics in multivariate models. The LCA identified a three-class model of preventive behaviors characterized by high likelihood of engagement in the set of preventive behaviors ("high"), low likelihood of the preventive behaviors ("low"), or engagement in some behaviors ("mixed"). Respondents of older age (i.e., age 50 or older) and those with higher levels of educational attainment (i.e., a 4-year college degree or higher) were less likely to be in the low engagement versus the mixed engagement class compared to those who are younger (18–29) and have lower levels of educational attainment (i.e., high school), respectively. Women (compared to men) and respondents who were Black and/or Hispanic/Latinx (compared to White) were more likely to be in the high (vs. mixed) engagement class. In separate models adjusted for sociodemographic characteristics, respondents with a high perceived risk of infection, high perceived risk of death, and high perceived effectiveness of COVID-preventive behaviors were statistically significantly less likely to be in the low engagement relative to the mixed engagement class. Engagement in COVID-preventive behaviors varies by sociodemographic characteristics (i.e., age, sex, race/ethnicity and educational attainment) and health beliefs (i.e., perceived risk of infection, perceived risk of death, and perceived effectiveness of CDC-recommended behaviors). Our findings highlight the potential utility of using health beliefs to inform targeted prevention efforts to help reduce the spread of COVID-19 and future pandemics.
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