Guinea
AI-Powered Hotspot Prediction for Lassa Fever, Ebola, and Severe Malaria
EPCON has been supporting international organizations in the nation to fight Lassa Fever and severe Malaria.
1. Viral Hemorrhagic Fevers – DECIPHER Project (2024–2026)
Guinea continues to face risks from Lassa Fever and the potential for Ebola outbreaks, with fragile health systems often challenged to respond effectively. Predictive intelligence is key to pandemic preparedness.
Objective
Support pandemic preparedness by identifying high-risk population groups and enabling data-driven intervention planning for viral hemorrhagic fevers (VHF) like Ebola and Lassa fever.
EPCON's Approach
We are developing an AI model that integrates high-resolution contextual, environmental, and case data to estimate disease burden, simulate progression, and identify at-risk groups.
Key Outcomes and Impact
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EPCON’s AI modeling will enhance risk forecasting and strategic deployment of diagnostics, enabling more effective and efficient outbreak response.
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Data-driven deployment of diagnostics and treatment resources.
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Stronger outbreak response capacity and resilience.
Partners
2. Malaria – Severe Malaria Risk in Children (2024–2025)
Malaria is one of the leading causes of childhood mortality in sub-Saharan Africa. In Guinea, children under 18 are particularly vulnerable, but reliable disaggregated risk data is lacking.
Objective
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Generate new evidence on the burden of severe malaria in children.
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Provide high-resolution risk maps to support national malaria programs.
EPCON's Approach
EPCON applies Bayesian inference models and machine learning to combine:
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Climate and environmental indicators.
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Population, health system access, and socio-economic factors.
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Malaria prevalence, resistance patterns, and vector distribution.
Key Outcomes and Impact
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Severe malaria risk rates disaggregated by age groups (2-year intervals).
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High-resolution hotspot maps of pediatric malaria transmission.
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Evidence-based guidance for resource allocation and intervention targeting.
