Clement Adebamowo, B.M. Ch.B. Hons., Sc.D., Shawneequa Callier, J.D., M.A., Oluchi C. Maduka, Ph.D., Simisola Akintola, L.L.B., B.L., L.L.M., Ph.D., Jennifer Kukucka, Christopher G. Arima, J.D., Temidayo Ogundiran, M.B.B.S., M.H.Sc., Ayodele Jegede, Ph.D., Adeola Akintola, M.Sc., Olusegun Adeyemo, M.Sc., and Sally N. Adebamowo, M.B.B.S., M.Sc., Sc.D.
Data science health research is an innovative research method that holds great promise for improving health care access and delivery in African countries. However, the digital equity gap that exists between low- and middle-income countries (LMICs) and high-income countries is widening quickly. Overcoming this gap requires African governments, institutions, and their international partners to invest in ethical and just data science practices to mitigate the effects of Africa’s digital poverty on data science health research. Data science methods applied to health research can exacerbate pre-existing, unresolved ethical dilemmas on the continent while generating new ones. To enable African countries to promote and advance ethical data science health research, we reviewed the challenges, gaps, and opportunities for ethical oversight of data science health research in Nigeria, a prototypical African LMIC. We conclude that existing tools can be modified to respond to the ethical issues generated by current data science methods, whereas regulatory bodies established by law can modify, reinterpret, and change the scope of existing regulations. (Funded by the National Institute of Mental Health/National Institutes of Health under Award Number U01MH127693 and others.)