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
SwarmEpi: Decentralised Epidemic Tracker
A real-time epidemic tracking platform using swarm-optimised agent-based models, piloted across 5 regions of Ghana with the Ghana Health Service. Generates 14-day disease spread forecasts 40% more acc…
Active · 2024–2026FedHealth: Federated Health Intelligence Network
Connects 12 district hospitals in a federated learning network, enabling joint training of disease prediction models on EHR data without raw patient data leaving each hospital.…
Active · 2025–2027VaxRoute: Vaccine Cold-Chain Optimisation
Reinforcement learning agents that dynamically re-route vaccine distribution during supply disruptions, reducing cold-chain wastage by an estimated 23% in Ghana's Northern Region.…
Pilot · 2025Related Publications
Privacy-Preserving Federated Learning for Healthcare Networks
Justice Kwame Appati, Sarah Jenkins, et al.
International Conference on Machine Learning (ICML)
Predictive Spatio-Temporal Modeling for Viral Outbreak Containment
Sarah Jenkins, Justice Kwame Appati
Nature Communications: Health AI
Interested in Collaborating?
We welcome partnerships with institutions, NGOs, and researchers working at the frontier of AI and this domain.