Study on the influence of the information diffusion and vaccination behavior on disease transmission in multiplex networks

Abstract

To investigate the influence of information diffusion and vaccination behavior on disease transmission. In this paper, a coupling model is proposed to describe the co-evolution process of information diffusion, vaccination behavior and disease transmission in multiplex network. In the information layer, two types of information are diffused, including the positive information and the negative information, respectively. During the process of information diffusion, the influence of mass media on information diffusion is considered, due to the herd effect, which type of information is believed to depend on the information state of the surrounding neighbors based on the Heaviside step function. In the behavioral layer, the individuals with different types of information will choose different immune behavioral responses, which in turn will influence the disease transmission. The coupling model was analyzed by using the Micro Markov Chain Approach (MMCA) to obtain state transition equations and the prevalence thresholds for disease. By simulating the simulation experiments, it demonstrates that the information diffusion has no direct effect on disease prevalence thresholds, but affects the proportion of infected; vaccination behavior has a significant effect on disease prevalence thresholds and also affects the proportion of infected. The results of the study suggest that when the disease transmission is within the controllable range, the stronger the diffusion of positive information, the higher the vaccination rate, which has a more positive influence on inhibiting disease transmission; once out of control, the official will lose trust, which is not conducive to disease control.