FSI-AIBR / INTELLIGENCE
Nigeria Malaria Digital Twin
An experimental disease-intelligence system exploring what long-term climate and health-survey signals can reveal about malaria risk.
From climate signals to health intelligence.
An experimental disease-intelligence system exploring what long-term climate and health-survey signals can reveal about malaria risk — currently deployed as a research platform, with a published preprint and WHO MSI-TAG acknowledgment.
DHS / MIS surveys
＋ CHIRPS / NDVI climate
＋ Geospatial data
→ Feature engineering
→ Random Forest model
→ SHAP explainability
→ Spatial risk intelligence
INTERACTIVE PREVIEW
Hover or tap an LGA cell to preview the interface pattern.
Selected unit—
Relative risk index—
Top climate driver—
ModelRandom Forest + SHAP
StatusPilot
Grid cells are a layout placeholder, not real LGA-level output. The live platform runs on Streamlit today; this interface previews the intended native web experience.