Infection-induced Cascading Failures -- Impact and Mitigation

Coupled spreading processes on interdependent networks are studied, where the spreading infection of diseases or malware in one layer can trigger cascading failures in another layer and lead to secondary disasters, e.g., disrupting public services, supply chains, or power distribution. We utilize the dynamic message-passing method to devise efficient algorithms for inferring the system states, which allows one to investigate systematically the nature of such complex intertwined spreading processes and evaluate their impact. Based on the dynamic message-passing framework and optimal control, we further develop an effective optimization algorithm for mitigating network failures.