Research & Innovation
AI-driven healthcare research that surfaces population-level insights for policy and clinical care.
Africa generates vast quantities of health data from malaria surveillance to maternal health records and yet much of it sits siloed and underanalysed. TAHTA's Research & Innovation programme brings together epidemiologists, data scientists, and clinicians to change that.
We build machine-learning pipelines on top of de-identified, consented datasets to forecast disease outbreaks, understand treatment efficacy across populations, and identify high-risk cohorts before they reach crisis point.
All research is conducted under IRB-equivalent ethics review from at least one African institution, and all findings are published open-access. We also run an open dataset repository to make anonymised population cohort data available to the global research community.
Our current flagship project, AfriPredict, combines satellite imagery, climate data, and community symptom reports to produce 14-day malaria risk forecasts at sub-district level — a world first.
Key Outcomes
- 14 peer-reviewed publications (2022–2025)
- AfriPredict: malaria forecast model in production
- AI triage tool piloted in 3 countries
- Open dataset repository with 40+ datasets
- 3 university research partnerships active