The impact of information dissemination strategies to epidemic spreading on complex networks

Epidemic spreading is one of the popular dynamics on complex networks. The classic SIR (susceptible–infected–recovered) model describes the spreading process of infections. The information dissemination is also considered in many works because people’s reactions to the outbreak of epidemic influence the spreading. In this work, we analyze how the operations on information dissemination affect the infected individuals as well as the spreading conditions of epidemics. We propose an SIR-A (susceptible–infected–recovered–active)model to map the infection and information dissemination to a double-layer network based on the assumption that the community size and individual’s awareness may have an impact on the infection rate (β) between two individuals. We improve the widely used index infected ratio (i(t)) and propose the spreading risk (RSP(t)) to evaluate the epidemic spreading process. Then with the inspiration of immunization strategies, we propose three information dissemination strategies, which are random, targeted and path-based ones. They are used to speed up the information dissemination to control the epidemic spreading. By considering two measures namely speak value (Pv) and peak time (Pt) of RSP(t), we compare the efficiency of these three strategies. The experimental results show that any one of these strategies can reduce Pv and delay the coming of Pt effectively, especially the path-based strategy in the situation of scale-free networks with low μ.