Advancing AI and data science for health in Africa: education, collaboration, and applications for global health priorities

Abstract

Background: Africa faces a shortage of health data scientists. Despite bearing 25% of the global disease burden, it has only 3% of the world's healthcare workforce and even less health data science expertise. As artificial intelligence and data science transform global healthcare, from disease surveillance to precision medicine, this capacity gap poses a significant threat to Africa's ability to address its health challenges and harness its growing young population for health innovation. Methods: We describe the WASHA Takwimu program, a multi-institutional capacity-building initiative funded by the National Institutes of Health (NIH) Data Science Initiative for Africa (DSI Africa) consortium. Operating through a hub-and-spoke model anchored by the University of KwaZulu-Natal (UKZN), Harvard T. H. Chan School of Public Health, and Heidelberg Institute of Global Health, the project has spoke partners in Ghana, Nigeria, Tanzania, and Uganda. The program delivers training through multiple modalities: master's degrees, postdoctoral fellowships, short courses, and professional development activities. The curriculum integrates data science methods with applications in global health priority domains, including health systems strengthening and food systems, climate change, and planetary health, using competency-based, application-focused, and digitally enhanced approaches. Results: From 2020 to 2024, WASHA Takwimu (Kiswahili for "Ignite Data") trained postdoctoral fellows, doctoral students, and other early-career researchers and practitioners across five African countries. The program has supported the development of a Master of Health Data Science program at UKZN and contributed to faculty capacity and curriculum development for a similar program at Makerere University. Key achievements include successful faculty exchanges replacing costly international student placements, integration of technological innovations in learning delivery, and strategic partnerships with national research and policy organizations which connect training to policy-relevant applications. Critical lessons have been learned regarding infrastructure constraints, data governance challenges, gender inequality in participation, and the importance of managing student expectations while maintaining rigorous entry requirements. Implications: WASHA Takwimu demonstrates that network-based approaches combining graduate training, faculty development, and stakeholder engagement can build sustainable health data science capacity in Africa. The program's hub-and-spoke model offers a replicable framework balancing centralized coordination with distributed implementation, while the Master's programs provide adaptable templates for building similar educational offerings at other African institutions. However, consolidating current achievements must precede ambitious expansion. Strategic priorities include strengthening partnerships with national research councils and Ministries of Health, addressing persistent gender disparities, deepening private sector engagement, and progressively developing PhD programs. As Africa's population approaches 2.5 billion by 2050, investments in health data science capacity will prove essential for addressing continental health priorities and positioning African institutions as global leaders.