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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
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A collaborative approach to advancing research and training in Public Health Data Science-challenges, opportunities,
Elisha Abade1, Wondwossen Mulugeta2, Idah Orowe3
1Department of Computing & Informatics, University of Nairobi, Nairobi, Kenya.
Frontiers in Public Health
|December 26, 2024
Summary
This project established Public Health Data Science (PHDS) training programs in Ethiopia and Kenya. It addresses the need for skilled data scientists to tackle public health challenges in low-income countries.
Area of Science:
- Public Health
- Data Science
- International Collaboration
Background:
- Low and middle income countries (LMIC), particularly in sub-Saharan Africa, face significant public health challenges.
- There is a critical shortage of trained data scientists and context-specific educational programs in these regions.
- Existing educational programs and infrastructure are insufficient to leverage modern technology for public health data analysis.
Purpose of the Study:
- To establish sustainable research training programs for a new generation of data scientists.
- To foster rigorous, ethically conscious Public Health Data Science practice in Ethiopia and Kenya.
- To address the human capacity and resource gap in public health data analysis within Eastern Africa.
Main Methods:
- A collaborative project, Advancing Public Health Research in Eastern Africa through Data Science Training (APHREA-DST), was initiated.
- Partnerships were formed between Columbia University (USA), Addis Ababa University (Ethiopia), and the University of Nairobi (Kenya).
- Qualitative and quantitative approaches, including online surveys and focus group discussions, informed curriculum development for a Master of Science in Public Health Data Science (PHDS) program.
Main Results:
- A Master's degree program in Public Health Data Science (PHDS) was successfully launched in Ethiopia and Kenya.
- An experience-sharing program was conducted at Columbia University.
- Memoranda of Understanding (MoUs) were established for data sharing and internships, fostering collaboration.
Conclusions:
- The project successfully initiated collaborative teaching and research programs to build capacity in Public Health Data Science.
- Key successes include program launch, international exchange, and partnership agreements.
- The initiative highlights the importance of collaboration and investment to overcome challenges in public health data science training in LMICs.
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