Using health data and AI to improve maternal, newborn, and child well-being in East Africa
Official title: UZIMA-DS: UtiliZing health Information for Meaningful Impact in East Africa through Data Science
Funded at Aga Khan University (Kenya) · NIH-11160679 · Data updated 2026-11-12
This project combines health records and new AI tools to spot early warning signs and guide care for pregnant people, newborns, children, and adolescents in East Africa.
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 | September 15, 2021 |
| Project end | June 30, 2026 |
| Funding year | 2025 |
| Award (this year) | $1,641,317 |
| NIH project number | 5U54TW012089-05 |
| Project ID | NIH-11160679 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are pregnant people, newborns, children, and adolescents receiving care at participating hospitals or community sites in East Africa or families willing to share linked health information.
✕Less likely to help
People living outside participating East African sites, those not receiving care at partner facilities, or those without accessible or linkable health data may not benefit directly from this work.
What this research studies
You'll be part of work that brings together clinic records, birth data, community information, and mental health measures and uses AI to find patterns that matter over time. The project will build a platform to harmonize data across hospitals and communities in East Africa and train machine-learning tools to act as early warnings for risks in mothers, newborns, children, and adolescents. Teams plan to work with local clinicians and community partners to create methods that can be scaled and sustained so findings can change care where you live.
Why it matters
Potential benefit: If successful, this could help catch health problems earlier and guide better care for mothers, babies, and children across East Africa.
How similar studies have gone: AI and data-science approaches have shown promise in predicting maternal and child health risks in some settings, but applying harmonized, temporal models across diverse East African data is relatively new and still being tested.
Where this research is happening
-
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.