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.

Background: Testing for HIV using rapid test devices assists in determining HIV status and ascertains if treatment is required. Rapid HIV quality assurance (QA) training is conducted to ensure accuracy of test results in non-laboratory settings. Objectives: This study aimed to determine the factors associated with the accuracy of rapid HIV testing among primary healthcare (PHC) workers who received HIV testing QA training in the Eastern Cape, South Africa. Method: A cross-sectional analytical study design was used to purposively recruit 167 PHC workers with prior training on HIV testing QA. Data were collected in 2022 using a self-administered questionnaire. STATA version 17.0 was used for data analysis. Results: Tester accuracy measured by a proficiency testing (PT) score of greater than 80% was achieved among 64.7% of the testers. Comprehensive HIV QA training was significantly associated with a PT score of greater than 80% (P = 0.001). On multivariable analyses, a PT score of greater than 80% was less likely with rural facilities (adjusted odd ratios [aOR] = 0.56, 95% confidence interval [CI]: 0.36–0.92, P = 0.020), Grade 12 education (aOR = 0.40, 95% CI: 0.19–0.85, P = 0.017), mentorship (aOR = 0.55, 95% CI: 0.35–0.85, P = 0.008), and attitudes towards inaccurate HIV results (aOR = 0.13, 95% CI: 0.02–0.82, P = 0.03); while implementation of QA processes (aOR = 3.94, 95% CI: 1.22–12.74, P = 0.022) and elements of QA in the HIV Testing Services register (aOR = 4.93, 95% CI: 1.45–16.74, P = 0.011) were associated with a PT score of greater than 80%. Conclusion: Exposure to comprehensive rapid HIV QA training were associated with higher tester accuracy. A framework for QA training is required for standardisation of training in the country.

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