Disease suppressing on correlated multiplex networks

Abstract

Social support is indispensable in controlling the spreading of infectious diseases. How to use effectively the limited resources in suppressing disease spreading is a subject of great challenge. In this paper, a novel model of resource allocation in suppressing is proposed that is comprised of the local information of both network structure and spreading state in physical contact subnetwork. Besides a resource based disease spreading model is also proposed. Through extensive simulations on both uncorrelated two-layer multiplex networks and networks with inter-layer degree correlations we find that when only consider the impact of local network structure on uncorrelated multiplex network, there is a worst value, at which the threshold reaches lowest and infected density reaches maximum. When only consider the impact of local information of spreading state we observed that there is also a worst value. In addition, when the inter-layer degree correlation is positive, we observe that when the bias parameter is smaller than zero, resources in layer social layer should be allocated preferentially to nodes with relatively larger LSD. However, when the bias is larger than zero, there is a worst value of the bias parameter, at which resources in layer social layer should be allocated preferentially to nodes with larger LSD. At last, when the inter-layer correlation is negative, we observe that resources in layer social should be allocated preferentially to the nodes with larger value of LSD.