Diffusion of resources and their impact on epidemic spreading in multilayer networks with simplicial complexes

TLDR: In this article , the authors proposed a multilayer network model, where the upper layer network represents a resource network composed of random simplicial complexes to transmit resources, while the lower-layer network represents the network of physical contacts where the disease can spread.

Abstract: Recent studies have shown that personal resources have a significant impact on the dynamics of epidemic spreading. In previous studies, the main way for individuals to be able to obtain resources was through pairwise interactions. However, the human relationship network is often characterized also by group interactions, not just by pairwise interactions. To study the impact of resource diffusion on disease propagation in such higher-order networks, we therefore propose a multilayer network model, where the upper-layer network represents a resource network composed of random simplicial complexes to transmit resources, while the lower-layer network represents the network of physical contacts where the disease can spread. We derive the outbreak threshold expression for the epidemic by means of the micro Markov chain method, which reveals that the diffusion of resources may substantially change the epidemic threshold. We also show that the final fractions of infected individuals obtained via the micro Markov chain method and the classical Monte Carlo method are very similar, thus confirming that the model can predict well the epidemic spreading within the networked population. Finally, through extensive simulations, we show also that increasing the spread of resources on 2-simplexes can suppress the epidemic spreading and outbreaks, thus outlining possibilities for novel containment strategies.