University of Washington joins international effort to support data science research and training in Africa
The University of Washington at St. Louis is joining a major international effort to advance data science, catalyze innovation and spur health discovery across Africa. Researchers at the School of Medicine are awarded one of 19 scholarships that will support data science research and training activities in Africa. Researchers will focus their efforts on developing new health data science training programs in Rwanda.
The University of Washington at St. Louis is joining a major international effort to advance data science, catalyze innovation and spur health discovery across Africa. The program is supported by the National Institutes of Health (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).
Researchers at the School of Medicine are awarded one of 19 scholarships that will support data science research and training activities in Africa. Researchers will focus their efforts on developing new health data science training programs in Rwanda. Professors from the Brown School and the McKelvey School of Engineering are also involved in the initiative.
Led by Co-Principal Investigators Victor Davila-Roman, MD, Director of the Global Health Center at the Institute for Public Health at the University of Washington; and Philip RO Payne, PhD, director of the Institute of Computer Science at the University of Washington, the researchers will collaborate with colleagues from the University of Rwanda and the African Institute of Mathematical Sciences, both in Kigali, Rwanda.
The project aims to develop a program that promotes the development of interns in research careers with a focus on pressing health 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 big data science techniques to these problems will allow researchers to identify disease patterns and their prevalence in large populations and, based on them, help scientists develop new hypotheses. to be tested in order to improve public health.
Data science offers great potential for understanding the burden of disease in Africa. But to make progress in the fight against these diseases, we need highly trained data scientists in Africa, to collect and analyze large sets of health data across populations. Such analyzes can then be used to guide interventions. We look forward to working with our colleagues in Rwanda and other locations within the DS-I Africa initiative to develop and implement outstanding training programs for students in Rwanda so that they can acquire these skills. and gain valuable experience. “
Davila-Roman, professor of medicine, anesthesiology and radiology
The Global Health Center is joining forces with the Institute for Informatics at the University of Washington to develop the training programs and curricula that will go into the project.
“The main public health issues we are trying to address are global in nature – the COVID-19 pandemic alone demonstrates that these issues do not care about geographic boundaries,” said Payne, also Professor Janet and Bernard Becker, associate dean. for Health Information and Data Science, and Chief Data Scientist for the Faculty of Medicine. “In order to deal with these huge problems, we must be able to collect and analyze immense amounts of data. NIH is making a substantial investment in building a network of academic institutions and other groups in Africa and the United States which will initiate important research and training programs so that we can better organize and understand the health data that is generated.In addition, the program will help develop a workforce in Rwanda and in many other African countries that can advance this work. “
Training programs in Rwanda will develop skills in health data science, and interns in Rwanda will be able to choose from masters and doctoral programs as well as postgraduate training and faculty development. In-person and distance learning options will include opportunities to acquire skills in applied mathematics, biostatistics, epidemiology, clinical informatics, analytics, computational biology, biomedical imaging, artificial intelligence, computer science and engineering.
Mentorship and internship opportunities will help interns harness their skills to tackle real-world issues. They could, for example, apply data science concepts to medical and public health fields such as social determinants of health, climate change, food systems, infectious diseases, noncommunicable diseases, surveillance health, trauma, pediatrics and parasitology.
The NIH program in Africa has four components: a coordination center at the University of Cape Town in South Africa; seven training centers, including one run by the University of Washington; seven research centers; and four centers focused on understanding the ethical, legal and social implications of data science research.
“This initiative has generated tremendous enthusiasm across all sectors of the biomedical research community in Africa,” 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 support future African leaders in data science and ensure progress sustainable in this promising area. “
In addition to the Common Fund (CF), the awards are 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 National Institute of Child Health and Human Development Eunice Kennedy Shriver, 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 led by the CF, FIC, NIBIB, NIMH and NLM.