NYU-Moi Data Science for Health Determinants Training Program

Moi University College Of Health Sciences, Eldoret

Investigators

Linked publications & trials

Abstract

Modified Project Summary/Abstract Section The overarching goal of the Data Science for Health Determinants (DSHD) pre- and post-doctoral training program is to develop future leaders in data science who are equipped to develop and analyze data to better leverage deep and rich survey as well as internet and other digitized data sources that can help us capture information on the determinants of health. Such data can provide unique illumination into factors on where we live, work, and play which can be used to better understand and address health across noncommunicable disease, infectious disease and injuries in the Kenyan context. However, the data are often unstructured and can have complex relationships with health outcomes, making the use of modern data science approaches critical. DSHD leverages strong investment across biomedical, public health, data science and artificial intelligence investment at both partners (NYU School of Medicine is 11th in the nation for NIH funding, NYU is home of the AI-now institute and Moi University has a strong NIH funding record) as well as a broader network of academic, industrial and non-governmental organizations, opening a wide pool of potential, strong trainees from both data science and health backgrounds. To develop capacity, priority will be given to Moi affiliates, Kenyan citizens and then others from Africa. A complementary team of 23 mentors at Moi and NYU committed to training and career development will offer resources across health determinants, biomedical sciences, statistics, epidemiology, data management, analytics and ethics. Over the past four years, the program has focused on long-term development of a cohort of PhD, postdoctoral and Faculty fellow trainees who have benefited from interdisciplinary training that carefully layers a core set of competencies in data science across data management and wrangling, prediction and analytics and data communication and ethics, with didactic and experiential training in health determinants as well as best practices in responsible conduct of research, reproducibility and community-engaged, ethical data science at NYU. Second, the program has leveraged international standard biostatistics and informatics faculty and programming at Moi with trainees equipped in advanced data science coursework at NYU, to expand the base of local expertise and capacity in data science by developing MSc and PhD data science tracks at the Institute for Biomedical Informatics and Biostatistics programs at Moi University within 5 years. Finally, continuing education opportunities and networking will occur through workshops bringing together experts in health and data science in Kenya and surrounding areas. Programs will be evaluated annually by our Internal Advisory Board and Training Advisory Committee. As health determinants can be cross-cutting rather than disease-specific, classroom and research opportunities across determinants of health and their applicability to wide range of health application domains will be available at both project sites and curricula will be relevant to research and training efforts across the entire DSI-Africa consortium.