NIH awards $75M to boost data science in Africa
September/October 2021 Volume 20 Number 5
Photo courtesy of UCT
The University of Cape Town (UCT) will develop and manage the open data science
platform and coordinating center of the NIH’s new Data Science in Africa program.
The NIH 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 (ELSI) of data science research.
Awardees have a robust network of partnerships across
the African continent and in the U.S., 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 Dr. Francis S. Collins. “Big data and Artificial
Intelligence (AI) 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. Scientists in Kenya will
leverage large, existing data sets to develop and validate
AI models to identify women at risk for poor pregnancy
outcomes; and to identify adolescents and young healthcare
workers at risk of depression and suicide ideation. A hub
in Nigeria will study SARS-CoV-2 and HIV with the goal of
using data to improve pandemic preparedness. In Uganda,
researchers will advance data science for medical imaging
with efforts to improve diagnoses of eye disease and cervical
cancer. Scientists in Nigeria will also study anti-microbial
resistance and the dynamics of disease transmission,
develop a portable screening tool for bacterial infections
and test a potential anti-microbial compound. A project
based in Cameroon will investigate ways to decrease the
burden of injuries and surgical diseases, as well as improve
access to quality surgical care across the continent. From
a hub in South Africa, researchers will study multi-disease
morbidity by analyzing clinical and genomic data with
the goal of providing actionable insights to reduce disease
burden and improve overall health. Finally, another project
in South Africa will develop innovative solutions to mitigate
the health impacts of climate change throughout the region,
with initial studies of clinical outcomes of heat exposure.
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 topics such as applied mathematics, biostatistics, epidemiology, clinical informatics, analytics,
computational omics, biomedical imaging, machine
intelligence, computer science and engineering. Trainees
will receive intensive mentoring and participate in
internships to learn how to apply data science concepts
to medical and public health areas including the social
determinants of health, climate change, infectious
diseases, noncommunicable diseases and health
surveillance.
Recognizing that data science research may uncover
potential ethical, legal and social implications (ELSI),
the consortium will include dedicated ELSI research teams that will be embedded in the research hubs
to address these topics. This will include efforts to
develop evidence-based, context specific guidance for
the conduct and governance of data science initiatives.
Researchers will evaluate current legal instruments and
guidelines to develop new and innovative governance
frameworks for data science health research in Africa.
They will explore legal differences across regions of
the continent, as well as investigate public attitudes
regarding data science approaches for healthcare.
A second phase of the program is being planned to
encourage more researchers to join the consortium,
foster the formation of new partnerships and address
additional capacity building needs. A concept under
development would support discrete research projects
led by African investigators who propose innovative
health data science research and solutions with a new
non-academic partner. To enhance the career pipeline
and retention of health data scientists in Africa, at least
half of the awards would go to new and early-stage
investigators. A second concept would enhance the
existing research training programs.
In addition to the Common Fund, the DS-I Africa awards
are being supported by Fogarty, the National Cancer
Institute, the National Human Genome Research
Institute, the National Institute of Allergy and Infectious
Diseases, the National Institute of Biomedical Imaging
and Bioengineering, 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, the National
Library of Medicine and the NIH Office of Data Science
Strategy.
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