The National Institutes of Health is investing about $74.5 million over five years to advance data science, catalyze innovation and spur health discoveries across Africa.
Under its new Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa) program, the NIH is issuing 19 awards to support research and training activities.
DS-I Africa is an NIH Common Fund program that is supported by the Office of the Director and 11 NIH Institutes, Centers and Offices.
Awards will establish a consortium consisting of a data science platform and coordinating center, seven research hubs, seven data science research training programs and four projects focused on studying the ethical, legal and social implications of data science research. Awardees have a robust network of partnerships across the African continent and in the United States, including numerous national health ministries, nongovernmental organizations, corporations, and other academic institutions.
“This initiative has generated tremendous enthusiasm in all sectors of Africa’s biomedical research community,” said NIH Director Francis S. Collins, M.D., Ph.D. “Big data and artificial intelligence have the potential to transform the conduct of research across the continent, while investing in research training will help to support Africa’s future data science leaders and ensure sustainable progress in this promising field.”
The University of Cape Town (UCT) will develop and manage the initiative’s open data science platform and coordinating center, building on previous NIH investments in UCT’s data and informatics capabilities made through the Human Heredity and Health in Africa (H3Africa) program. UCT will provide a flexible, scalable platform for the DS-I Africa researchers, so they can find and access data, select tools and workflows, and run analyses through collaborative workspaces. UCT will also administer and support core resources, as well as coordinate consortium activities.
The research hubs, all of which are led by African institutions, will apply novel approaches to data analysis and AI to address critical health issues.
The research training programs, which leverage partnerships with U.S. institutions, will create multi-tiered curricula to build skills in foundational health data science, with options ranging from master’s and doctoral degree tracks, to postdoctoral training and faculty development. A mix of in-person and remote training will be offered to build skills in multi-disciplinary topics such as applied mathematics, biostatistics, epidemiology, clinical informatics, analytics, computational omics, biomedical imaging, machine intelligence, computational paradigms, computer science and engineering.
