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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.

Background Key populations (KP), including men who have sex with men (MSM), female sex workers (FSW), and transgender women (TGW), experience a disproportionate burden of HIV, even in generalized epidemics like South Africa. Given this disproportionate burden and unique barriers to accessing health services, sustained provision of care is particularly relevant. It is unclear how the COVID-19 pandemic and its associated restrictions may have impacted this delivery. In this study, we aimed to describe patterns of engagement in HIV prevention and treatment services among KP in South Africa and assess the impact of different COVID-19 restriction levels on service delivery. Methods We leveraged programmatic data collected by the US President’s Emergency Plan for AIDS Relief (PEPFAR)-supported KP partners in South Africa. We divided data into three discrete time periods based on national COVID-19 restriction periods: (i) Pre-restriction period, (ii) High-level restriction period, and (iii) After-high level restriction period. Primary outcomes included monthly total HIV tests, new HIV cases identified, new initiations of pre-exposure prophylaxis (PrEP), and new enrollments in antiretroviral therapy (ART). We conducted interrupted time series segmented regression analyses to estimate the impact of COVID-19 restrictions on HIV prevention and treatment service utilization. Results Between January 2018 and June 2022, there were a total of 231,086 HIV tests, 27,051 HIV positive cases, 27,656 pre-exposure prophylaxis (PrEP) initiations, and 15,949 antiretroviral therapy initiations among MSM, FSW and TGW in PEPFAR-supported KP programs in South Africa. We recorded 90,457 total HIV tests during the ‘pre-restriction’ period, with 13,593 confirmed new HIV diagnoses; 26,134 total HIV tests with 2,771 new diagnoses during the ‘high-level restriction’ period; and 114,495 HIV tests with 10,687 new diagnoses during the after high-level restriction period. Our Poisson regression model estimates indicate an immediate and significant decrease in service engagement at the onset of COVID-19 restrictions, including declines in HIV testing, treatment, and PrEP use, which persisted. As programs adjusted to the new restrictions, there was a gradual rebound in service engagement, particularly among MSM and FSW. Towards the end of the high-level restriction period, with some aspects of daily life returning to normal but others still restricted, there was more variability. Some indicators continued to improve, while others stagnated or decreased. Conclusion Service provision rebounded from the initial shock created by pandemic-related restrictions, and HIV services were largely maintained for KP in South Africa. These results suggest that HIV service delivery among programs designed for KP was able to be flexible and resilient to the evolving restrictions. The results of this study can inform plans for future pandemics and large-scale disruptions to the delivery of HIV services.

Background Sexual and gender minority (SGM) persons experience substantial mental health disparities throughout the life course, including increased vulnerability to depression and suicide. Few existing studies, however, have explored how pervasive experiences of SGM-related stigma, discrimination, and trauma (i.e., minority stress) contribute to adverse mental health outcomes among diverse sub-populations of SGM adults living in rural areas of the United States. This paper describes the protocol for a prospective cohort study, “Rural Exploration and Approaches for LGBTQ + Mental Health (REALM),” that will explore minority stress in relation to mental health conditions and suicidal behaviors among rural SGM adults. Methods Online processes will be used to recruit and enroll a diverse sample of up to 2,500 SGM adults aged 18 + living in rural counties and small metropolitan areas in the United States to complete an online baseline survey. This will include: up to 1,000 cisgender sexual minority persons (up to n  = 500 each cisgender women and cisgender men); and up to 1,500 gender minority persons (up to n  = 500 persons who were assigned male at birth and identify as a woman, female, and/or transfeminine; up to n  = 500 persons who were assigned female at birth and identify as a man, male, and/or transmasculine; and up to n  = 500 persons who identify as some other gender, including non-binary, gender non-conforming, and/or agender regardless of sex assigned at birth). All enrolled participants will subsequently be followed over a 12-month period, with repeated surveys at three-month intervals. Included survey measures will focus on sociodemographic information, mental health, substance use, suicidal behaviors, minority stressors, psychological processes, and other related risk and protective factors. Discussion This study presents a critical opportunity to better understand how minority stress contributes to adverse mental health outcomes among populations that remain underrepresented in research and programs in 2024. Results will be used to create more targeted, acceptable, and impactful intervention content and strategies that mitigate stigma, promote mental health, and prevent suicidal behaviors among rural SGM adults.

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. 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. 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. 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. 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.

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.

Sexual economic exchanges, including sex work and transactional sex, have been consistently associated with HIV acquisition among young women in sub-Saharan Africa. Heterogeneity in HIV vulnerability across overlapping types of sexual economic exchange has not been sufficiently explored, limiting appropriate and effective linkage to prevention interventions. From January 2017 to May 2018, cross-sectional data were captured at screening for entry into an HIV incidence cohort in Kisumu, Kenya. Men and women aged 18–35 years completed a socio-behavioral questionnaire. Latent class analysis was used to classify sexually active women into discrete groups based on self-identification of occupational sex and other sexual exchanges, including exchange for money, gifts, food, school fees, substances, shelter/rent, and/or clothing. Profiles examined characteristics within and across typologies. Mixed logistic regression models assessed demographic and socio-behavioral characteristics associated with probabilistic class membership. A total of 1063 participants were screened, of whom 536 (50.4%) were sexually active women (median age: 27 years [interquartile range 23–30]). Sexual economic exchange was reported by 403 (77.2%) sexually active women, who most commonly reported recent exchange of sex for money (73.9%), gifts (19.6%), food (25.9%), and substances (17.7%); 44.6% reported selling sex as a primary or secondary occupation. Three profiles of sexual economic exchange were identified, each with distinct demographic, behavioral, and occupational characteristics: exchange for money and other necessities (23.3% prevalence), exchange for primarily money (38.2% prevalence), and sex comprising limited or no exchange (38.4% prevalence). In mixture modeling, as compared to limited or no exchange, exchange for money and other necessities, and exchange for primarily money were both associated with increased age, higher number of partners, and partners at least 10 years older. Heterogeneous patterns of sexual economic exchange were observed among women in Kenya reflect the different motivations and pathways by which women exchange sex. Female sex workers are often considered a homogeneous group, but these data highlight the need for differentiated services based on the diverse needs of women who engage in sexual economic exchange.

Purpose of Review Big Data Science can be used to pragmatically guide the allocation of resources within the context of national HIV programs and inform priorities for intervention. In this review, we discuss the importance of grounding Big Data Science in the principles of equity and social justice to optimize the efficiency and effectiveness of the global HIV response. Recent Findings Social, ethical, and legal considerations of Big Data Science have been identified in the context of HIV research. However, efforts to mitigate these challenges have been limited. Consequences include disciplinary silos within the field of HIV, a lack of meaningful engagement and ownership with and by communities, and potential misinterpretation or misappropriation of analyses that could further exacerbate health inequities. Summary Big Data Science can support the HIV response by helping to identify gaps in previously undiscovered or understudied pathways to HIV acquisition and onward transmission, including the consequences for health outcomes and associated comorbidities. However, in the absence of a guiding framework for equity, alongside meaningful collaboration with communities through balanced partnerships, a reliance on big data could continue to reinforce inequities within and across marginalized populations.

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.

Partnering with young people to conduct research is fundamental to community mobilization. Recent restrictions on in-person interactions and engagement presented limitations for continued partnership with young people. To present a practical strategy and lessons learned to facilitate community-engaged research with youth in a virtual setting. Based on youth engagement tenets, the TEAM (tailor the compensation package, ensure meetings are accessible, accommodate personal needs, and maintain the structure of in-person meetings) strategy was used to adapt the partnership to a virtual setting. Three lessons are discussed 1) the importance of maintaining social connectedness, 2) maximizing flexibility, and 3) focusing on creativity and competency building. The COVID pandemic forced researchers to rethink previous engagement practices that relied heavily on in-person interactions to be sustainable. The TEAM strategy is one way to successfully adapt practices and engage young people in virtual settings.