Last Updated: 18/12/2025
Project Foresight: AI-Powered malaria prediction and response in Nigeria
Objectives
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Develop and validate predictive models for malaria incidence and commodity needs
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Integrate forecasts into supply chain planning to enable proactive response
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Pilot the model in selected states (e.g., Sokoto, Kebbi, Zamfara)
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Assess the impact of predictive forecasting on reducing stockouts and improving malaria outcomes.
Project Foresight is an innovative initiative designed to transform malaria control in Nigeria by transitioning from reactive reporting to predictive action. The project leverages routine health facility data (DHIS2), climatic variables (rainfall, temperature, vegetation indices), and supply chain information to build machine learning models that can:
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Forecast malaria case surges 2–4 weeks in advance at LGA and facility levels
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Anticipate commodity needs (ACTs, RDTs) to prevent stockouts
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Identify hidden hotspots where disease spikes and stockouts overlap
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Support more efficient allocation of resources and reduce severe malaria cases
The successful implementation of Project Foresight will represent a paradigm shift in malaria commodity management, providing an early warning system, reducing inefficiencies, saving lives, and offering a scalable framework adaptable to other diseases.
Jan 2026 — Dec 2027
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