UZIMA-DS: Turning East Africa health data into early risk alerts
Official title: UZIMA-DS: UtiliZing health Information for Meaningful Impact in East Africa through Data Science
Funded at Aga Khan University (Kenya) · NIH-11511758 · Data updated 2026-11-12
A data science hub in East Africa will build AI-powered tools to spot early risks for mothers, babies, and adolescent mental health so care can happen sooner.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Aga Khan University (Kenya) NIH-funded |
| Lab location | 1 site (Nairobi, Kenya) |
| Project start | March 9, 2026 |
| Project end | June 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $305,000 |
| NIH project number | 3U54TW012089-05S1 |
| Project ID | NIH-11511758 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are pregnant/childbearing individuals, children up to 11 years old, adolescents and young adults in East Africa, and their families who are part of the data platforms or health systems linked to the UZIMA-DS hub.
✕Less likely to help
Patients outside the East Africa context or not connected to the participating data sources may not directly benefit from this project.
What this research studies
This project creates a scalable platform that combines multiple health data sources from East Africa to detect early signs of problems in maternal, newborn, child health and adolescent mental health. It uses data assimilation and AI/ML techniques to develop repeatable methods for predicting risk, with a focus on real-world data from surveillance systems, cohorts, hospitals, and communities. The goal is to provide timely, actionable insights that can guide prevention and early intervention efforts across the translational spectrum. The work is anchored in partnerships with local institutions like Aga Khan University in Nairobi to ensure relevance and sustainability in the African context.
Why it matters
Potential benefit: If successful, the project could enable earlier detection and prevention of pregnancy complications, developmental issues, and adolescent mental health crises, potentially reducing harm and healthcare costs.
How similar studies have gone: Prior data science efforts in similar settings have shown promise in early risk prediction, though applying harmonized multimodal data in East Africa is relatively novel.
Where this research is happening
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Aga Khan University (Kenya)
Nairobi, Kenya Active
Researchers
- Principal investigator: Ali, Amina Abubakar — Aga Khan University (Kenya)
- Study coordinator: Ali, Amina Abubakar
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.