Optimal information dissemination in epidemic networks

One of the popular dynamics on complex networks is the SIS epidemic spreading. The SIS epidemic model describes how infections spread throughout a network. The SIS model was extended to Susceptible-Alert-Infected-Susceptible (SAIS) model [1] to incorporate reaction of agents to the spread of the infection. Built upon the SAIS model, we investigate how information dissemination can help boosting the resilience of the agents population against the spreading. The information dissemination is realized through an additional network among agents, which has the same nodes (agents) but different links with respect to the contact network. Each link in the information dissemination network is a directed link which provides the health status of the source agent to the end agent. We introduce an information dissemination metric which is a quadratic form of the adjacency matrix of the information dissemination network and the dominant eigenvector of the adjacency matrix of the contact graph. By tools of perturbation theory, we analytically show that the effect of the information dissemination is explicitly related to the information dissemination metric. It is proven that the spectral centrality of the nodes and edges determines the optimal information dissemination network. Our results suggest that monitoring the health status of a small subgroup of the agents and circulating the information can greatly enhance the resilience of the network, with multiple potential areas of applications, from infectious diseases mitigations to malware impact reduction.