Jiayi Song , Wenjie Li , Yunzhu Xiao , Ling Chen , Chun Yang , Li Qi , Wei Wang
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引用次数: 0
Abstract
When an epidemic spreads through a population, related information also spreads concurrently, prompting individuals to adopt protective behaviours (e.g., washing hands). Collective behaviour has been shown to play a critical role in shaping the dynamics of epidemic spreading, and higher-order networks offer a natural framework to describe such group interactions in social contact networks. Yet, the interplay between epidemic and information dynamics on higher-order structures is not fully understood, further limiting our understanding of the optimal information spreading strategy for containing epidemic spreading.In this study, we first construct a higher-order multiplex network framework based on simplicial complexes. Then, a coevolutionary spreading model is proposed, integrating epidemic spreading and information spreading on simplicial complexes. The epidemic spreads through both lower-order (pairwise) and higher-order (group) interactions, while information spreads through lower-order interactions in a degree-preferential manner. Using an extended Microscopic Markov Chain Approach, we analytically derive the dynamical equations of the system and compute the basic reproduction number using the next-generation matrix method. Finally, we conduct extensive numerical simulations of the spreading process across various parameter regimes. Our results demonstrate the role of higher-order infections in promoting epidemics. Although information spreading generally suppresses the spread of most epidemics, it can paradoxically enhance the spread of certain epidemics with a very low spreading capacity. Increases in the recovery probabilities of both the disease and the information can weaken the promoting effect of higher-order infection and enhance the suppressive effect of the information. For certain epidemics with weak spreading capabilities but strong recovery capabilities, the spread of information can completely suppress the outbreak of the disease, while the enhancement of higher-order infections can promote the outbreak of these diseases. By analysing the effects of different information spreading strategies on epidemic spreading, we find that the optimal strategy for containing the epidemic is to allow information to spread without degree preference.
期刊介绍:
Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results.
In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.