Background:Conventional HIV testing approaches continue to fall short of overcoming barriers to HIV testing, especially among key and priority populations at higher risk of acquiring and transmitting HIV. Artificial intelligence (AI) and machine learning present a unique opportunity to strengthen prioritised HIV testing through risk prediction and enhanced diagnostic tools. Objective:This study discussed stakeholders' views on opportunities, challenges, contextual considerations and an implementation roadmap and strategic recommendations for integrating AI and machine learning into HIV testing in South Africa. Method:This qualitative study recruited 15 stakeholders in Gauteng Province, using individual semi-structured face-to-face interviews. Thematic content analysis was performed, and the Consolidated Framework for Implementation Research was used to map the implementation roadmap of the results. Results:Four superordinate themes were identified: perceived benefits, challenges, ethical considerations and implementation strategies. The study discussed the opportunity to leverage AI to enhance HIV testing through HIV risk prediction, self-testing support and advanced, accurate diagnostics. However, technological access, digital divide, resource constraints, privacy concerns, skill gaps and staff resistance, among other barriers, were noted. Conclusion:The implementation design should incorporate the perspectives of all stakeholders involved in HIV testing to address human factors and ethical concerns surrounding AI use.

Background Oral Pre-Exposure Prophylaxis (PrEP) is a proven method for preventing HIV among women, including adolescent girls and young women who are categorised as priority populations due to a higher risk of HIV acquisition. However, the COVID-19 lockdown disrupted access to healthcare services, including those for HIV prevention and treatment. This study aimed to assess changes in PrEP outcomes before and during the COVID-19 lockdown period among women in the North-West Province, South Africa. Methods We conducted a retrospective analysis of programme data collected by TB HIV Care from December 2018 to December 2021 in the Dr Kenneth Kaunda District to assess changes in PrEP initiation, uptake, and adherence before (December 2018 - February 2020) and during (March 2020 - December 2021) the COVID-19 pandemic among women aged 16 years and above. The Department of Health electronic (Excel) register was used to collect data. The overdispersion tests conducted on three datasets, PrEP initiation, uptake, and adherence, showed significant overdispersion (with p -values less than 0.05). This indicates that the Negative Binomial regression model is more appropriate for these datasets. Additionally, the adherence dataset contained a high percentage of zero outcomes, underscoring the need for a zero-inflated model to address the excess zeros. Consequently, we implemented Bayesian negative binomial regression models for both the PrEP initiation and uptake datasets and a Bayesian Zero-Inflated Negative Binomial (ZINB) regression model for the adherence dataset. Results A total of 1339 women involved in transactional sex were counselled and offered PrEP services. Out of these, 776 were initiated on PrEP with a mean age of 33 years. PrEP initiation demonstrated a significant trend before the lockdown, an immediate effect during the lockdown, and a shift in trends afterwards, with all 95% credible intervals excluding zero. This suggests that the pandemic both disrupted and altered PrEP initiation patterns. The intervention did not lead to a significant increase in PrEP uptake among clients who returned for HIV testing within one month, as the 95% credible intervals included the value of 1. Nonetheless, there was a slight positive trend over time that was statistically significant, indicating a modest increase in uptake. Additionally, none of the estimated parameters for adherence achieved statistical significance, suggesting that the intervention did not have a meaningful impact on adherence levels. Conclusion The study revealed a decline in the initiation, uptake, and adherence to PrEP during the COVID-19 lockdown, although services were maintained through innovative interventions. These findings underscore the necessity for more innovative strategies to enhance PrEP outcomes, ensure effective HIV control, and prepare for potential future pandemics.

Background 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. Objective 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. Methods 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). Results 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. Conclusions 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. International Registered Report Identifier (IRRID) DERR1-10.2196/63583

Background: Key populations (KPs), particularly female sex workers (FSWs), continue to face significant barriers in accessing HIV-related healthcare services in South Africa. Structural challenges have historically hindered equitable HIV treatment access, worsened by the COVID-19 pandemic. Overburdened clinics, staff shortages, and travel constraints disrupted HIV services and ART adherence. In response, the Differentiated Service Delivery (DSD) model was rapidly scaled up to decentralise care and improve treatment continuity. Objective: To solicit the views of stakeholders regarding their interests, roles and experiences in the implementation of the HIV treatment DSD model among FSWs in South Africa, as well as associated successes and barriers thereof. Methods: We purposively selected and interviewed eight stakeholders, comprising government officials, implementers and sex workers’ advocacy organizations. Thematic analysis was used to explore the perceived impact of DSD models and associated successes and barriers in the current service delivery landscape. Results: The study found that decentralization of DSD models improved access to services for FSWs. However, the criminalization of sex work perpetuates fear and marginalization, while stigma and discrimination within healthcare settings remain significant deterrents to HIV treatment uptake. High mobility among FSWs also disrupts continuity of care, contributing to treatment interruptions and lack of data on loss to follow-up. Participants highlighted the need for legal reform, increased healthcare provider sensitization, and the integration of mental health and psychosocial support in HIV services. Peer-led interventions and digital health innovations, such as biometric systems and electronic medical records, emerged as promising strategies for enhancing patient tracking and retention. Nonetheless, the sustainability of DSD models is threatened by an overreliance on external donor funding and insufficient government ownership. Conclusions: To achieve equitable healthcare access and improved HIV outcomes for KPs, especially FSWs, a multi-pronged, rights-based approach is essential. This must include community engagement, structural and legal reforms, integrated support services, and sustainable financing mechanisms to ensure the long-term impact and scalability of DSD models.

Background: There is a dearth of evidence on the roles and views of stakeholders regarding the sexually transmitted infections (STIs) service provision among key and priority populations (KPPs) within primary healthcare (PHC) settings. Aim: This study assessed the roles and views of stakeholders regarding the STI services scope, content, accessibility, quality, affordability, and availability, as well as associated gaps and successes among KPP within PHC facilities in the Capricorn District of Limpopo Province in South Africa. Methods: An exploratory research design was used. In-depth face-to-face interviews with 18 STI stakeholders were conducted. The STI stakeholders were purposively selected from five PHC facilities. An inductive analytical approach was employed to develop themes and sub-themes. Tesch's step analysis informed the development of the thematic analysis process. Results: The presence of peer counsellors, home-based caregivers, and the operation of STI services day and night in two selected facilities enhanced access and availability of STI services. Consistent in-service training for service providers was implemented to improve service quality and maintain professional competency. Barriers that prevented adequate STI service provision in this study included staff shortages, inadequate filing systems, lack of advanced-diagnostic equipment, and patients' noncompliance with treatment regimens. The successes of the STI service provision were effective STI treatment and services integration within the facilities. Conclusions: The findings of this study have unveiled several methods to increase access and availability to STI services among KPPs in the selected PHC facilities. We recommend gathering responses and experiences from STI service users regarding the current STI service provision to foster innovative and targeted approaches within PHC facilities in Limpopo Province.

Despite notable progress in HIV prevention and treatment, men who have sex with men (MSM) continue to bear a disproportionate burden of HIV, particularly in sub-Saharan Africa, where systemic barriers restrict access to HIV testing. This study draws on data from the 2017 Ghana Men’s Study II (GMS II), to examine the socio-demographic, behavioural, and structural factors influencing HIV testing among MSM. The Ghana Men’s Study II dataset, involving 4095 MSM, was de-identified and analysed using STATA (software version 17). Before the analysis, missing information for categorical variables were treated using the mode imputation technique. Chi-square test was done to describe relevant characteristics of the study population, such as socio-demographic/socio-economic variables and behavioural practices. Multivariable logistic regression analysis was performed for variables with p < 0.05 to determine significant predictors of HIV testing among MSM. All the statistical analyses were performed at a 95% confidence interval, with significant differences at p < 0.05. In multivariable logistic regression analysis, age 25–34 (AOR: 1.43; 95% CI: 1.18–1.74, p < 0.001), having a senior high school education (AOR: 1.69; 95% CI: 1.02–2.80, p = 0.040), tertiary education (AOR: 2.03; 95% CI: 1.17–3.55, p = 0.012), being a light drinker of alcohol (AOR: 1.28; 95% CI: 1.04–1.58, p = 0.020), and having a comprehensive knowledge of HIV (AOR: 1.50; 95% CI: 1.26–1.78, p < 0.001) had higher odds for HIV testing. Other factors such as being a Muslim (AOR: 0.69; 95% CI: 0.54–0.90, p = 0.005) and sold sex to other males (AOR: 0.67; 95% CI: 0.50–0.90, p = 0.007) were also positively associated with HIV testing among Ghanaian MSM. The findings revealed a number of socio-demographic and behavioural factors associated with HIV testing among the MSM population in Ghana.

Background:The global targets for HIV testing for achieving the Joint United Nations Programme on HIV/AIDS (UNAIDS) 95-95-95 targets are still short. Identifying gaps and opportunities for HIV testing uptake is crucial in fast-tracking the second (initiate people living with HIV on antiretroviral therapy) and third (viral suppression) UNAIDS goals. Machine learning and health technologies can precisely predict high-risk individuals and facilitate more effective and efficient HIV testing methods. Despite this advancement, there exists a research gap regarding the extent to which such technologies are integrated into HIV testing strategies worldwide. Objective:The study aimed to examine the characteristics, citation patterns, and contents of published studies applying machine learning and emerging health technologies in HIV testing from 2000 to 2024. Methods:This bibliometric analysis identified relevant studies using machine learning and emerging health technologies in HIV testing from the Web of Science database using synonymous keywords. The Bibliometrix R package was used to analyze the characteristics, citation patterns, and contents of 266 articles. The VOSviewer software was used to conduct network visualization. The analysis focused on the yearly growth rate, citation analysis, keywords, institutions, countries, authorship, and collaboration patterns. Key themes and topics were driven by the authors' most frequent keywords, which aided the content analysis. Results:The analysis revealed a scientific annual growth rate of 15.68%, with an international coauthorship of 8.22% and an average citation count of 17.47 per document. The most relevant sources were from high-impact journals such as the Journal of Internet Medicine Research, JMIR mHealth and uHealth, JMIR Research Protocols, mHealth, AIDS Care-Psychological and Socio-Medical Aspects of AI, and BMC Public Health, and PLOS One. The United States of America, China, South Africa, the United Kingdom, and Australia produced the highest number of contributions. Collaboration analysis showed significant networks among universities in high-income countries, including the University of North Carolina, Emory University, the University of Michigan, San Diego State University, the University of Pennsylvania, and the London School of Hygiene and Tropical Medicine. The discrepancy highlights missed opportunities in strategic partnerships between high-income and low-income countries. The results further demonstrate that machine learning and health technologies enhance the effective and efficient implementation of innovative HIV testing methods, including HIV self-testing among priority populations. Conclusions:This study identifies trends and hotspots of machine learning and health technology research in relation to HIV testing across various countries, institutions, journals, and authors. The trends are higher in high-income countries with a greater focus on technology applications for HIV self-testing among young people and priority populations. These insights will inform future researchers about the dynamics of research outputs and help them make scholarly decisions to address research gaps in this field.

OBJECTIVES:Intimate partner violence (IPV) and sexually transmitted infections (STIs) continue to be public health challenges globally and in South Africa. However, studies examining the relationship between IPV and STIs, and the potential age disparities among South African women are lacking. Therefore, this study aimed to determine the association between varying forms of IPV (sexual, physical, and emotional) and STI diagnosis among South African women and assess the potential age disparities in this relationship. METHODS:Data were obtained from the 2017 South African National HIV Prevalence, Incidence, Behaviour and Communication National Household Cross-sectional Survey (N = 8505). Crude and multivariable logistic regression models (adjusting for ethnicity, education, and region) were used to determine the association between different forms of IPV and STIs in the past year (N = 8505). Models were stratified by age group (15-24, 25-34, 35-44, 45-49 years). RESULTS:Sexual (adjusted odds ratio [aOR], 2.97; 95% confidence interval [CI], 1.78-4.95), physical (aOR, 2.45; 95% CI, 1.78-3.37) and emotional IPV (aOR, 2.70; 95% CI, 2.01-3.61) were associated with STIs in the overall study population. However, disparities by age group existed. Adolescent girls and young women aged 15 to 24 years and women aged 25 to 34 years who experienced sexual IPV were 4 times and 3 times as likely to report STIs compared with adolescent girls and young women and women aged 25 to 34 years who did not experience sexual IPV (aOR, 3.58 [95% CI, 1.14-11.3]; aOR, 2.65 [95% CI, 1.19-5.92], respectively). Older women, aged 45 to 49 years, who experienced sexual IPV were 7 times as likely to report STIs (aOR, 6.92; 95% CI, 1.58-30.4). Similar patterns were seen for women exposed to emotional and physical IPV. CONCLUSIONS:Intimate partner violence interventions are warranted for women IPV survivors across the age spectrum, which may help to reduce the incidence of STIs.

The Fourth Industrial Revolution (4IR) has significantly impacted healthcare, including sexually transmitted infection (STI) management in Sub-Saharan Africa (SSA), particularly among key populations (KPs) with limited access to health services. This review investigates 4IR technologies, including artificial intelligence (AI) and machine learning (ML), that assist in diagnosing, treating, and managing STIs across SSA. By leveraging affordable and accessible solutions, 4IR tools support KPs who are disproportionately affected by STIs. Following systematic review guidelines using Covidence, this study examined 20 relevant studies conducted across 20 SSA countries, with Ethiopia, South Africa, and Zimbabwe emerging as the most researched nations. All the studies reviewed used secondary data and favored supervised ML models, with random forest and XGBoost frequently demonstrating high performance. These tools assist in tracking access to services, predicting risks of STI/HIV, and developing models for community HIV clusters. While AI has enhanced the accuracy of diagnostics and the efficiency of management, several challenges persist, including ethical concerns, issues with data quality, and a lack of expertise in implementation. There are few real-world applications or pilot projects in SSA. Notably, most of the studies primarily focus on the development, validation, or technical evaluation of the ML methods rather than their practical application or implementation. As a result, the actual impact of these approaches on the point of care remains unclear. This review highlights the effectiveness of various AI and ML methods in managing HIV and STIs through detection, diagnosis, treatment, and monitoring. The study strengthens knowledge on the practical application of 4IR technologies in diagnosing, treating, and managing STIs across SSA. Understanding this has potential to improve sexual health outcomes, address gaps in STI diagnosis, and surpass the limitations of traditional syndromic management approaches.

BackgroundHIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goal of ending AIDS by 2030. Despite the availability of relevant survey data, there exists a research gap in using machine learning (ML) to analyze and predict HIV testing among adults in South Africa. Further investigation is needed to bridge this knowledge gap and inform evidence-based interventions to improve HIV testing. ObjectiveThis study aims to determine consistent predictors of HIV testing by applying supervised ML algorithms in repeated adult population-based surveys in South Africa. MethodsA retrospective analysis of multiwave cross-sectional survey data will be conducted to determine the predictors of HIV testing among South African adults aged 18 years and older. A supervised ML technique will be applied across the five cycles of the South African National HIV Prevalence, Incidence, Behavior, and Communication Survey (SABSSM) surveys. The Human Science Research Council (HSRC) conducted the SABSSM surveys in 2002, 2005, 2008, 2012, and 2017. The available SABSSM datasets will be imported to RStudio (version 4.3.2; Posit Software, PBC) to clean and remove outliers. A chi-square test will be conducted to select important predictors of HIV testing. Each dataset will be split into 80% training and 20% test samples. Logistic regression, support vector machines, random forests, and decision trees will be used. A cross-validation technique will be used to divide the training sample into k-folds, including a validation set, and models will be trained on each fold. The models’ performance will be evaluated on the validation set using evaluation metrics such as accuracy, precision, recall, F1-score, area under curve-receiver operating characteristics, and confusion matrix. ResultsThe SABSSM datasets are open access datasets available on the HSRC database. Ethics approval for this study was obtained from the University of Johannesburg Research and Ethics Committee on April 23, 2024 (REC-2725-2024). The authors were given access to all five SABSSM datasets by the HSRC on August 20, 2024. The datasets were explored to identify the independent variables likely influencing HIV testing uptake. The findings of this study will determine consistent variables predicting HIV testing uptake among the South African adult population over the course of 20 years. Furthermore, this study will evaluate and compare the performance metrics of the 4 different ML algorithms, and the best model will be used to develop an HIV testing predictive model. ConclusionsThis study will contribute to existing knowledge and deepen understanding of factors linked to HIV testing beyond traditional methods. Consequently, the findings would inform evidence-based policy recommendations that can guide policy makers to formulate more effective and targeted public health approaches toward strengthening HIV testing. International Registered Report Identifier (IRRID)DERR1-10.2196/59916

Background: The global community has set an ambitious goal of ending HIV as a public health risk by 2030. To achieve this, South Africa must have a robust routine health information management information system (RHIMS) that provides programmatic data disaggregated by key populations (KPs) to enable effective HIV response. Objectives: To explore key stakeholders’ perspectives regarding the incorporation of KPs unique identifier codes (UICs) in the RHIMS in terms of opportunities, procedures, vulnerabilities, challenges, and considerations for enhancement in tracking the HIV care cascade in South Africa. Method: We conducted an exploratory, descriptive study that had three phases. First, we conducted stakeholder analysis and mapping using the power-interest matrix (Phase one). Second, we performed a qualitative document analysis (Phase two). Third, we conducted in-depth interviews with 20 stakeholders (Phase three). Results: We mapped 100 stakeholders according to their power and interest regarding the KPs UICs inclusion in RHIMS, with the South African National AIDS Council and the National Department of Health being the primary stakeholders. Stakeholders highlighted the KPs UIC facilitators as District Health Information System (DHIS) policy support, integration with TIER.Net and DHIS, data security, improved monitoring and evaluation, and KP-targeted programming. Stakeholders also cited resistance to change, stigma and discrimination, data privacy, and security as key concerns for the inclusion of KPs UICs in the RHIMS. Conclusion: Stakeholders support the inclusion of KPs UICs in public health data collection tools, emphasising its role in improving monitoring and evaluation, resource allocation, and KP-specific programming.

South Africa’s health system was affected by the various mitigation measures implemented to control the rapid spread of the COVID-19 pandemic. However, innovative interventions were introduced to ensure service continuity. This study sought to explore the perspectives of stakeholders regarding the pre-exposure prophylaxis (PrEP) innovative interventions implemented during the COVID-19 lockdown period among adolescent girls and young women (AGYW), as well as their successes and improvements. We selected and interviewed 12 PrEP stakeholders, including professional nurses, case managers, peer educators, and counselors from the TB HIV Care programme in the Dr. Kenneth Kaunda District, in the North-West Province. The qualitative questions explored (1) how PrEP services were disrupted during the lockdown period, (2) how the disruptions were managed, and (3) the challenges and successes of the innovative interventions implemented. The interviews were audio-taped, transcribed, and thematically analyzed through Tesch’s eight steps of analysis. The stakeholders confirmed that COVID-19 disruptions affected the provision of PrEP services in terms of recruitment, counseling, HIV testing, and adherence support offered in different community hotspots. Responding to these difficulties, alternative avenues such as social media platforms were implemented and used for service continuity. The themes that emerged were organized into the following two categories: PrEP services provided during and after the COVID-19 lockdown period, as well as the successes and challenges. The current study provides further insight into COVID-19, aiming to inform preparations for future pandemics. Innovative PrEP interventions alleviated COVID-19 disruptions in some settings and improved HIV services, but this was not the case in the selected study area.

The impacts of COVID-19 among men who have sex with men (MSM), who face limited access to HIV services due to stigma, discrimination, and violence, need to be assessed and quantified in terms of HIV treatment outcomes for future pandemic preparedness. This study aimed to evaluate the effects of the COVID-19 lockdown on the HIV treatment cascade among MSM in selected provinces of South Africa using routine programme data after the implementation of differentiated service delivery (DSD) models. An interrupted time series analysis was employed to observe the trends and patterns of HIV treatment outcomes among MSM in Gauteng, Mpumalanga, and KwaZulu-Natal from 1 January 2018 to 31 December 2022. Interrupted time series analysis was applied to quantify changes in the accessibility and utilisation of HIV treatment services using the R software version 4.4.1. The segmented regression models showed a decrease followed by an upward trend in all HIV treatment outcomes. After the implementation of the DSD model, significant increases in positive HIV tests (estimate = 0.001572; p < 0.001), linkage to HIV care (estimate = 0.001486; p < 0.001), ART initiations (estimate = 0.001003; p = 0.004), ART collection (estimate = 0.001748; p < 0.001), and taking viral load tests (estimate = 0.001109; p = 0.001) were observed. There was an overall increase in all HIV treatment outcomes during the COVID-19 lockdown in light of the DSD model.

Several studies conducted worldwide have reported on the effectiveness of consistent condom use with lubricants in preventing HIV transmission and acquisition; however, men who have sex with men (MSM) in Ghana continue to be disproportionately affected by the HIV burden. They are stigmatized, discriminated against, and criminalized, leading to social isolation, reduced access to health care, and inadequate targeted interventions. The dissemination of HIV prevention tools such as condoms and lubricants is also mainly focused on the general population, and this approach overlooks the specific needs and vulnerabilities of MSM. This study aimed to determine the prevalence and associated factors of consistent condom use with lubricants among MSM in Ghana. We analyzed cross-sectional data from the Ghana Men’s Study II dataset involving 4095 MSM aged 18 years and above. De-identified data were imported into STATA (College Station, TX, USA, software version 17) for data analysis. Descriptive analysis was performed to describe relevant characteristics of the study population. Multivariable logistic regression analysis was performed for significant variables in bivariate analysis to determine the associated factors of consistent condom use with lubricants. All the statistical analyses were performed at a 95% confidence interval, with significant differences at p < 0.05. The prevalence of consistent condom use with lubricants during penetrative anal sex was highest with male partners (44.9%), followed by female partners (40.0%), and all sexual partners (38.9%), respectively. In multivariable logistic regression analysis, having a senior high school education (AOR: 1.76; 95% CI: 0.88–3.12, p = 0.039), tertiary education or higher (AOR: 2.24; 95% CI: 0.86–3.23, p = 0.041), being an insertive sex partner (AOR: 1.26; 95% CI: 1.02–1.56, p = 0.029), being a sex worker (AOR: 1.41; 95% CI: 1.00–1.98, p = 0.048), buying sex from other males (AOR: 1.32; 95% CI: 1.03–1.70, p = 0.027), being a light drinker (AOR: 0.54; 95% CI: 0.42–0.68, p < 0.001), being a moderate drinker (AOR: 0.48; 95% CI: 0.30–0.78, p = 0.003), and possessing good HIV knowledge (AOR: 1.79; 95% CI: 1.46–2.20, p < 0.001) had higher odds of consistent condom use with lubricants. Being Islamic (AOR: 0.65; 95% CI: 0.49–0.87, p = 0.004), having a low income (AOR: 0.57; 95% CI: 0.42–0.77, p < 0.001), and easy access (AOR: 0.52; 95% CI: 0.37–0.72, p < 0.001) to condoms were positively associated with consistent condom use. This study found a low prevalence of consistent condom use with lubricants among the MSM population in Ghana. The study also found a range of socio-demographic, behavioral, and structural factors associated with consistent condom use with lubricants. This calls for very specific and unique public health interventions, such as developing a predictive model to identify and mitigate barriers to consistent condom use with lubricants.

Several machine learning (ML) techniques have demonstrated efficacy in precisely forecasting HIV risk and identifying the most eligible individuals for HIV testing in various countries. Nevertheless, there is a data gap on the utility of ML algorithms in strengthening HIV testing worldwide. This systematic review aimed to evaluate how effectively ML algorithms can enhance the efficiency and accuracy of HIV testing interventions and to identify key outcomes, successes, gaps, opportunities, and limitations in their implementation. This review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A comprehensive literature search was conducted via PubMed, Google Scholar, Web of Science, Science Direct, Scopus, and Gale OneFile databases. Out of the 845 identified articles, 51 studies were eligible. More than 75% of the articles included in this review were conducted in the Americas and various parts of Sub-Saharan Africa, and a few were from Europe, Asia, and Australia. The most common algorithms applied were logistic regression, deep learning, support vector machine, random forest, extreme gradient booster, decision tree, and the least absolute shrinkage selection operator model. The findings demonstrate that ML techniques exhibit higher accuracy in predicting HIV risk/testing compared to traditional approaches. Machine learning models enhance early prediction of HIV transmission, facilitate viable testing strategies to improve the efficiency of testing services, and optimize resource allocation, ultimately leading to improved HIV testing. This review points to the positive impact of ML in enhancing early prediction of HIV spread, optimizing HIV testing approaches, improving efficiency, and eventually enhancing the accuracy of HIV diagnosis. We strongly recommend the integration of ML into HIV testing programs for efficient and accurate HIV testing.

Although South Africa was the first country to register and roll out oral pre-exposure prophylaxis (PrEP) biomedical human immunodeficiency virus (HIV) prevention intervention in sub-Saharan Africa (SSA), its uptake remains low, particularly among adolescent girls and young women (AGYW). The uptake of PrEP may have worsened during the Coronavirus disease 2019 (COVID-19) pandemic. Some innovative interventions to improve PrEP uptake among AGYW have been implemented. This study aims to evaluate the effectiveness of PrEP innovative interventions implemented during COVID-19 towards reducing the risk of HIV infection among AGYW in South Africa. An exploratory, descriptive design will be conducted to carry out four study objectives. Firstly, to carry out a systematic review of innovative PrEP interventions implemented during COVID-19 in SSA countries. Secondly, to conduct a stakeholder analysis to identify PrEP stakeholders and interview them on their views on the implemented interventions. Thirdly, to assess the implementation outcomes of the innovative interventions using document reviews and Consolidated Framework for Implementation Research. Fourthly, to develop a framework for an improved PrEP service delivery among AGYW. Qualitative data will be captured in ATLAS.ti software (Technical University, Berlin, Germany) version 23 and analysed via thematic analysis. A statistical software package (STATA) version 18 (College Station, TX, USA) will be used to capture quantitative data and analyse them via descriptive analysis. The generated evidence will be used towards the development of framework, guidelines, and policies to strengthen the uptake of, scale-up, and adherence to PrEP among AGYW.

Men who have sex with men (MSM) in sub-Saharan Africa (SSA) are disproportionately affected by the human immunodeficiency virus (HIV) compared to adult men in the general population. Unprotected anal sexual intercourse is a high-risk behavior for HIV infection. This makes the correct and consistent use of condoms with condom-compatible lubricants crucial in reducing further HIV acquisition amongst the MSM population in SSA. However, consolidated data on the scope of the consistency of condom use with lubricants among MSM in SSA is lacking. In this regard, it was necessary to consolidate existing evidence on consistent condom usage with lubricants, as well as associated context-specific factors among the MSM population in SSA. A systematic review was conceptualized and registered with the International Prospective Register of Systematic Reviews (registration number: CRD42023437904). It was compiled following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) principles and guidelines between July 2023 and June 2024. We searched PubMed, Scopus, ScienceDirect, Google Scholar, and governmental and non-governmental institutions to find published and gray literature relevant to the review objectives from 2005 to June 2024. Studies conducted in SSA, published in English, focusing on MSM aged ≥15 years and also reported condom and lubricant use were considered for this review. Following the removal of duplicates and ineligible articles, 40 studies out of 202 reviewed were selected for the study. The most common study designs were cross-sectional surveys (n = 32) followed by prospective cohorts (n = 4), integrated bio-behavioral surveillance surveys (n = 3), and intervention studies (n = 1). Of the 40 eligible studies included in this review, half (n = 20) reported consistent use of condoms but without lubricants, three reported consistent use of condoms with lubricants but did not specify the lubricant type, six reported consistent condom use with water-based condom-compatible lubricants, and 11 reported only condom use but not consistent usage. Factors linked to consistent condom use with lubricants among MSM from various studies included higher educational level, knowing one’s HIV status, accessibility challenges, and older age. Having a high level of self-worth and HIV risk-reduction counseling was also associated with a consistency of condom use amongst MSM who engaged in receptive anal sex. This review indicates that only a few studies reported consistent condom use with lubricants and water-based compatible lubricants.

Primary healthcare facilities lack routine diagnostic screening due to resource limitations and dependence on syndromic management, resulting in an unprecedented prevalence and incidence of sexually transmitted infections (STIs), particularly among key and priority populations. Specific focuses are essential to strengthen current STI control measures. Therefore, this article describes the protocol for evaluating STI programme among key and priority populations in selected primary healthcare facilities in South Africa. We will employ an exploratory, descriptive research design to assess the STI programme in terms of its facility operations, functions, scope, gaps, delivery services, STI surveillance methods, and indicators in the selected primary healthcare facilities. A purposive sample of 15–20 STI programme stakeholders will be selected from five primary healthcare facilities in Limpopo Province, South Africa. The programme evaluation will use the World Health Organization assessment checklist tool, a globally recognised and validated instrument comprising open- and closed-ended questions to assess the STI programme. This tool, known for its credibility and reliability, ensures the study’s validity. Quantitative data will be captured on STATA software (College Station, TX, USA) version 18 for descriptive analysis and presented as the mean and standard deviation for continuous variables, proportions and percentages for categorical variables. A p ≤ 0.05 will demonstrate a statistically significant level. Thematic content analysis will be conducted for the qualitative data using Atlas. ti software (Technical University, Berlin, Germany) version 23.1. The study’s results will inform new approaches to strengthen STI coverage, service delivery, and linkage to care.

Introduction Despite having the world’s largest HIV epidemic, Sub-Saharan Africa (SSA) including South Africa (SA) has not yet achieved the 95-95-95 targets. To meet these targets, accurate and reliable key populations (KPs) disaggregated data is critical for guiding the HIV response. The inclusion of KPs Unique Identifier Code (UIC) on country’s routine health information management systems (RHIMS) can improve targeted resource allocation, reporting, and accountability. There is a gap in comprehensive review on how countries that implemented the unique identifier code went about in doing so. Methods and analysis A three-step search strategy will be utilized to get both published and unpublished documents. First, an initial search of MEDLINE identified keywords and MeSH terms. Second, a systematic search of electronic bibliographic databases including MEDLINE, PubMed, Scopus, PLOS ONE and Google Scholar, and thirdly, searching the reference list of all included reviews (hand-searching journals and reference tracking). Studies that meet the following PICO (Population, Intervention, Comparison, Outcome) criteria will be included: P: Published and unpublished materials reporting on key populations, namely men who have sex with men (MSM), sex workers (SW), people who inject/use drugs (PWI/UD), and transgender (TG); I: biometric fingerprint, alphanumeric code and any KPs UIC system; C: no unique identifier system; and O: KPs-specific 95-95-95 HIV cascade, KPs knowing HIV status, KPs on ART, ART adherence and Viral load suppression. This protocol was prepared using the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). References will be managed through ENDNOTE version 21 software. Two authors will screen the studies using Covidence software version 2.0 for inclusion according to the prescribed eligibility criteria. Differences will be addressed by consensus and with the assistance of an experienced third reviewer. Ethics and dissemination This review will summarize findings from published studies containing non-identifiable data. The results will be disseminated via preprints, open-access peer-reviewed journals, and conference presentations. PROSPERO registration number CRD42023440656 View this table: ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study did not receive any funding ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: N/A I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data will be made available upon request made to the corresponding author