An environment aware epidemic spreading model and immune strategy in complex networks

In the standard SIS model, each node has the same probability to be infected by its neighbors regardless of its surrounding environment. In the real world, the probability of a node to be infected is varying with the network environment; the prior model is not suitable for this scenario. In this paper, we consider an actual epidemic spreading model in which the probability of a node to be infected is related with the number of the infected nodes among its neighbors. We develop an analytical model for this epidemic spreading, named environment aware SIS model (EA-SIS) considering the heterogeneous infection rates, and analytically investigate the epidemic spreading in complex networks. We find that the threshold of EA-SIS is smaller than SIS which means the virus is easier to spread out in the EA-SIS model. In addition, we study several existing immune strategies on the EA-SIS model and propose a novel immune strategy which is based on expected infection time, ETB, of the nodes around the infected nodes for EA-SIS. The simulation results show that the EA-SIS model is more efficient that the SIS model, also, the proposed immune strategy, ETB, is more effective than the local information method and is close to the target immune strategy.