Coevolution of epidemic and infodemic on higher-order networks

Gathering events, e.g., going to gyms and meetings, are ubiquitous and crucial in the spreading phenomena, which induce higher-order interactions, and thus can be described as higher-order networks. Previous studies on the coevolution of epidemic-infodemic dynamics ignored the higher-order interactions in the social system, which affects our understanding of the reality spreading. We propose a mathematical framework for the coevolution of epidemic and infodemic on higher-order networks described by simplicial complex, and introduce the Microscopic Markov Chain Approach (MMCA) and mean-field approach to establish the dynamic process. We study the coevolution mathematical model on both artificial simplicial complex and real-world higher-order networks and find that the higher-order interactions show a ’double-edged sword’ role in shaping epidemic size, which is dependent on the breakout of infodemic. Furthermore, the higher-order networks enrich the phase diagram, inducing the emergence of discontinuous phase transition, hysteresis loop region, double transition and inter-epidemic region.