Project Summary
The Data Science Center for the Study of Surgery, Injury, and Equity in Africa (D-SINE-Africa) is an NIH U54-
funded research hub located at the University of Buea (Buea) in Cameroon through the current Data Science
in Africa (DS-I Africa) initiative (U54TW012087). D-SINE Africa is a strategic partnership between the Buea,
the University of California (Los Angeles (UCLA) and Berkeley), the Cameroonian Ministry of Public Health, the
African Institute for Mathematical Sciences in Cameroon, and the University of Cape Town (UCT) in South
Africa. This coalition is built upon a long-standing collaboration between Buea and UCLA focused on decreasing
the burden of surgical diseases in Cameroon and other sub-Saharan African (SSA) countries. Injuries and other
surgically treated diseases comprise a significant burden of disease in SSA, but opportunities for research and
funding are lacking. Our work on injury and other surgical emergencies has identified deep inequities that are
particularly unmasked in acute care settings. The intersection between injury and equity is our priority area of
study, as the inequities revealed by trauma are often symptomatic of larger, systemic, cross-cutting issues. Our
mission is to leverage data science to decrease the impact of trauma, surgical disease, and disparities on the
population of Cameroon and SSA by promoting collaborative research, networking, and capacity building. We
are accomplishing this through three Center Cores (Administrative, Capacity Building, and Data Management
and Analysis Cores) and two Research Projects, one on using data science methods to develop Socioeconomic
Status Surveillance tools and another on using machine learning to enhance trauma patient follow-up after
discharge from the hospital. At the heart of D-SINE Africa’s two Research Projects is the Cameroon Trauma
Registry (CTR), a 10-hospital, ongoing, centralized trauma data bank that collects data on demographics,
context, clinical care, and outcomes for injured patients. To date, the CTR has collected data on over 5000
Cameroonian trauma patients and, at approximately 450 patients per month, is projected to house information
on over additional 16,000 patients over the next 3 years. While these data are essential for the completion of
our two projects, they also have significant potential for other secondary analyses by scientists outside of D-
SINE to tackle the critical, yet vitally understudied, area of injury in Africa, where trauma causes the most death
and disability in the world. The goal of this supplement is to facilitate more secure, private, and streamlined
data-sharing by using ML techniques and differential privacy to generate private synthetic datasets that retain
the statistical properties of the original CTR data, while preventing the disclosure of sensitive information; thus,
safeguarding patient privacy while still allowing broad access to the data for research purposes. This will aid
our objective of reducing the burden of injury, achieving equity in access to surgery, and training the next
generation of data scientists in SSA.