The overarching goal of the Data Science for Social Determinants (DSDD) at New York University, Moi University and Brown University 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 social determinants of health. DSSD’s design will rapidly expand the local base of expertise via curriculum development, resulting in 2 PhD (4-year training) and 6 total postdoctoral (2-year) and faculty trainees (12-14 month) will train at NYU, while 8 Masters and 2 PhD trainees will commence or complete training (2-year and 4-year training, respectively) through newly developed data science tracks at Moi University. Connecting with local data science industries and organizations (IBM, Deep Learning Indaba, DataKind, AI.Kenya and Aga Khan University Nairobi and Karachi) will bring in and create intellectual meeting spaces for a wide pool and variety of talented trainees from both data science and health backgrounds, to propel and sustainably advance data science capacity in Kenyan institutions as well as the DSI-consortium.
Elevating both capacity in data science and concepts captured in data, this training program will develop future leaders in data science who are equipped to develop and analyze data to better leverage rich survey and digital data sources to capture information on the social determinants of health. Training includes future faculty at Moi University, graduate data science programs at Moi, as well as a Social Determinant Data Community of Practice for data scientists in the region.
Relevant Papers
Chunara, R., Gjonaj, J., Immaculate, E., Wanna, I., Alaro, J., Scott-Sheldon, L. A. J., Mangeni, J., Mwangi, A., Vedanthan, R., & Hogan, J., 2024. Social determinants of health: the need for data science methods and capacity. The lancet . Digital health , 6(4), e235-e237.
Hoodbhoy, Z., Chunara, R., Wale, A., AbuBakr, A., & Samad, Z., 2023. Is there a need for graduate-level programs in health data science? A perspective from Pakistan. The lancet . Global health, 11(1), e23-e25.
Mirin, N., Mattie, H., Jackson, L., Samad, Z., & Chunara, R., 2022. Data Science in Public Health: Building Next Generation Capacity. Harvard Data Science Review, 4(4).
Kuhlman, C., Jackson, L. and Chunara, R., 2020, August. No Computation without Representation: Avoiding Data and Algorithm Biases through Diversity. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 3593-3593).
Funders
