Effects of positive and negative social reinforcement on coupling of information and epidemic in multilayer networks

The spread of epidemics is often accompanied by the spread of epidemic-related information, and the two processes are interdependent and interactive. A social reinforcement effect frequently emerges during the transmission of both the epidemic and information. While prior studies have primarily examined the role of positive social reinforcement in this process, the influence of negative social reinforcement has largely been neglected. In this paper, we incorporate both positive and negative social reinforcement effects and establish a two-layer dynamical model to investigate the interactive coupling mechanism of information and epidemic transmission. The Heaviside step function is utilized to describe the influence mechanism of positive and negative social reinforcements in the actual transmission process. A microscopic Markov chain approach is used to describe the dynamic evolution process, and the epidemic outbreak threshold is derived. Extensive Monte Carlo numerical simulations demonstrate that while positive social reinforcement alters the outbreak threshold of both information and epidemic and promotes their spread, negative social reinforcement does not change the outbreak threshold but significantly impedes the transmission of both. In addition, publishing more accurate information through official channels, intensifying quarantine measures, promoting vaccines and treatments for outbreaks, and enhancing physical immunity can also help contain epidemics.