Washington University joins major NIH effort to advance health data science in Africa
School of Medicine faculty will lead initiative to train data scientists in Rwanda
Getty ImagesWashington University in St. Louis is joining a major international effort to advance data science, catalyze innovation and spur health discoveries across Africa. Researchers at the School of Medicine are receiving one of 19 grant awards that will support data science research and training activities in Africa. The researchers will focus their efforts on developing new training programs in health data science in Rwanda.
Washington University in St. Louis is joining a major international effort to advance data science, catalyze innovation and spur health discoveries across Africa. The program is supported by the National Institutes of Health’s (NIH) Common Fund, which will invest nearly $75 million over five years to fund the Harnessing Data Science for Health Discovery and Innovation in Africa (DS-I Africa) program.
Researchers at the School of Medicine are receiving one of 19 grant awards that will support data science research and training activities in Africa. The researchers will focus their efforts on developing new training programs in health data science in Rwanda. Faculty from the Brown School and the McKelvey School of Engineering also are involved in the initiative.
Led by co-principal investigators Victor Davila-Roman, MD, director of the Global Health Center at Washington University’s Institute for Public Health; and Philip R.O. Payne, PhD, director of Washington University’s Institute for Informatics, the investigators will collaborate with colleagues at the University of Rwanda and the African Institute for Mathematical Sciences, both in Kigali, Rwanda.
The project aims to develop a program that nurtures the development of trainees in research careers with a focus on urgent health-care issues in Rwanda, including the burden of infectious diseases, such as HIV, malaria and COVID-19, as well as chronic health conditions, including high blood pressure, diabetes and heart disease. Applying the techniques of big data science to these issues will enable researchers to identify patterns in diseases and their prevalence in large populations and, based on these, help scientists develop new hypotheses to test with the goal of improving public health.
“Data science holds great potential for understanding the burden of disease across Africa,” said Davila-Roman, also a professor of medicine, of anesthesiology and of radiology. “But to make strides in tackling these diseases, we need highly trained data scientists in Africa, to gather and analyze large sets of health data across populations. Such analyses can then be used to guide interventions. We look forward to working with our colleagues in Rwanda and other sites within the DS-I Africa initiative to develop and implement exceptional training programs for students in Rwanda so they can learn these skills and gain valuable experience.”
The Global Health Center is joining with Washington University’s Institute for Informatics to develop the training programs and curricula that will go into the project.
“The major public health problems that we’re trying to tackle are global in nature — the COVID-19 pandemic alone demonstrates that these issues don’t care about geographic boundaries,” said Payne, also the Janet and Bernard Becker Professor, associate dean for health information and data science, and chief data scientist for the School of Medicine. “In order to tackle these huge problems, we have to be able to collect and analyze immense amounts of data. The NIH is making a substantial investment in creating a network of academic institutions and other groups in Africa and the U.S. that will launch important research and training programs so we can better organize and understand the health data that’s being generated. In addition, the program will help develop a workforce in Rwanda and across many other African countries that can carry this work forward.”
The training programs in Rwanda will build skills in health data science, and trainees in Rwanda will be able to choose among master’s and doctoral degree programs as well as postdoctoral training and faculty development. In-person and remote training options will include opportunities to build skills in applied mathematics, biostatistics, epidemiology, clinical informatics, analytics, computational biology, biomedical imaging, machine intelligence, computer science and engineering.
Mentoring and internship opportunities will help trainees harness their skills to tackle real world problems. They could, for example, apply data science concepts to medical and public health areas such as social determinants of health, climate change, food systems, infectious diseases, noncommunicable diseases, health surveillance, injuries, pediatrics and parasitology.
The NIH program in Africa has four components: a coordinating center at the University of Cape Town in South Africa; seven training centers, including the one led by Washington University; seven research hubs; and four centers focused on understanding the ethical, legal and social implications of data science research.
“This initiative has generated tremendous enthusiasm in all sectors of Africa’s biomedical research community,” said NIH Director Francis S. Collins, MD, PhD, in the NIH announcement. “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.”
In addition to the Common Fund (CF), the awards are being supported by the Fogarty International Center (FIC), the National Cancer Institute (NCI), the National Human Genome Research Institute, the National Institute of Allergy and Infectious Diseases, the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Dental and Craniofacial Research, the National Institute of Environmental Health Sciences, the National Institute of Mental Health (NIMH), the National Library of Medicine (NLM) and the NIH Office of Data Science Strategy. The initiative is being led by the CF, FIC, NIBIB, NIMH and NLM.
