Public Health Intelligence
Harnessing AI and swarm algorithms to model pathogen spread, power disease surveillance, and deliver predictive tools that protect communities and save lives.
Public Health Intelligence
Our epidemiological modeling platform uses swarm algorithms to track pathogen spread in real-time. By simulating agent-based interactions at massive scales, we provide health authorities with predictive tools that are 40% more accurate than traditional statistical models. We collaborate with the Ghana Health Service and WHO Africa to deploy these tools at the community level, bridging the gap between cutting-edge AI research and ground-level public health interventions.
Key Research Topics
Epidemic Forecasting
Agent-based simulation of outbreak trajectories with 14-day predictive horizons across district-level geographies.
Geospatial Surveillance
Real-time mapping of disease clusters using satellite imagery, mobile health data, and IoT sensor networks.
Privacy-Preserving Analytics
Federated learning pipelines that extract population-level health insights without centralising individual patient records.
Healthcare Delivery Optimisation
Resource allocation models that route vaccines, personnel, and equipment during surge events using reinforcement learning.
Current Projects
FedHealth: Federated Health Intelligence Network
Federated learning across district hospitals — enabling AI-driven health intelligence without centralising patient data.
VaxRoute: Vaccine Cold-Chain Optimisation
Optimising vaccine cold-chain logistics with AI routing to ensure life-saving doses reach remote communities on time.
SwarmEpi: Decentralised Epidemic Tracker
Decentralised epidemic surveillance using swarm intelligence to track infectious disease outbreaks in real time across Ghana.
Related Publications
Interested in Collaborating?
We welcome partnerships with institutions, NGOs, and researchers working at the frontier of AI and this domain.