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Harnessing Data Science to Promote Equity in Injury and Surgery for Africa

利用数据科学促进非洲伤害和手术的公平

基本信息

批准号：
10842514
负责人：
Alain Mefire Chichom
金额：
$ 28.53万
依托单位：
UNIVERSITY OF BUEA
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-15 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10842514
关键词：
Address Administrative Supplement Africa Africa South of the Sahara African Area Award California Cameroon Caring Cessation of life Clinical Collaborations Communities Complex Country Data Data Analyses Data Science Data Scientist Data Set Databases Decision Trees Development Disclosure Disease Disparity Emergency Situation Ensure Equity FAIR principles Family Foundations Fringe Benefit Funding Generations Goals Grant Health Health Personnel Health Sciences Health Services Accessibility Heart Hospitals Individual Inequity Injury Institution Instruction Joints Legal Los Angeles Machine Learning Mathematics Measures Methods Mission Modeling Modernization Operative Surgical Procedures Outcome Patients Population Privacy Privacy Act Privatization Property Public Health Readiness Registries Research Research Personnel Research Project Grants Resources Risk Scientist Secure Socioeconomic Status South Africa Techniques Time Training Trauma Trauma patient Trust United States National Institutes of Health Universities Violence Work acute care autoencoder burden of illness clinical care data anonymization data management data registry data repository data sharing demographics design disability experience follow-up generative adversarial network high risk improved injured injury burden innovation insight mathematical sciences multimodal data multimodality next generation novel open data patient privacy prevent recurrent neural network repository secondary analysis shared repository support vector machine tool user-friendly

项目摘要

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.

项目总结