In this paper, we described the huge potential that Data Science Health Research (DSHR) holds to transform healthcare delivery and research outcomes for African populations through the application of novel computational methods and technologies to large-scale datasets. Some of these benefits include the development of groundbreaking strategies for disease surveillance, precision medicine, and public health interventions that could help African countries leapfrog legacy healthcare systems.

The paper also examined critical challenges facing data science health research in Africa such as substantial ethical governance risks that threaten to undermine these anticipated benefits, substantial underrepresentation of African populations in existing datasets, which renders algorithms potentially inaccurate and unstable when applied to African communities. Further concerns include the capacity of existing institutional and national health research ethics committees to adequately review and oversee complex data science projects, the need for culturally appropriate regulations and enforcement mechanisms, persistent digital inequity that widens the data gap between Africa and high-income countries, and the risk of algorithmic bias and extractive research practices. The paper discussed emerging efforts to build ethical governance frameworks through programs like the DS-I Africa initiative and recommend multi-level interventions including improving ethics infrastructure, developing resource-appropriate regulations, establishing multinational oversight mechanisms, reducing digital inequity, and eliminating algorithmic bias through diverse representation in data science development.