Disease spreading model considering the activity of individuals on complex networks

Abstract

In this paper, we propose a multiplex networks model to understand the spreading dynamics between disease and information with different activity characteristics for individuals at different rates. The paper establishes a multiplex networks model of information and disease transmission at the same time. The top layer is the information layer of virtual contacts and the lower layer is the disease layer of physical contacts. In the top layer of virtual contacts, individuals have their own characteristics, either positive or negative. The positive individuals spread disease prevention information with a high probability, but the individuals in the negative state spread disease prevention information with a low probability. At the same time, positive and negative individuals can change their behavior habits with a certain probability. In the disease layer of physical contacts, individuals are either active or inactive. The active individuals are easily infected by a neighboring individual, but the individuals in an inactive state can only be affected by active neighbors. And the active and inactive individuals can change their behavior habits with a certain probability. According to the mean-field theory, we have analyzed the dynamic evolution of the system and derived the disease thresholds. Finally, we have validated the theoretical analysis by numerical simulations on scale-free networks and discussed the changes in disease spreading under different individual activities. Our results indicate the individual activity of the information layer and disease layer has a certain impact on the disease spreading.