Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning.

The article focuses on developing a privacy-preserving framework for individual-level COVID-19 infection prediction using federated learning and graph neural networks. Topics include proposing a novel method, Falcon, that utilizes a hypergraph structure for contagion process representation, incorporating differential privacy mechanisms and region-level models to protect user privacy while improving prediction accuracy.