Coupled Spreading Dynamics of Competitive Information and Epidemics on Weighted Multilayer Networks with Higher-Order Interactions

The spread of epidemics in real social systems is often coupled with competitive information diffusion, higher-order group interactions, and dynamic contact behaviors. To capture these mechanisms, we develop a bilayer competitive information–epidemic coupled spreading framework. The upper layer is a weighted higher-order network incorporating both pairwise spreading and 2-simplex-driven group spreading, while the lower layer is a weighted activity-driven network describing time-varying physical contacts regulated by a policy relaxation parameter. Based on the microscopic Markov chain framework, we establish node-level evolution equations and derive a spectral condition for the local invasion threshold, which is evaluated numerically. Monte Carlo simulations show good agreement with the predicted steady-state densities. These findings indicate that enhancing the diffusion of the more protective information reduces steady-state epidemic prevalence and raises the epidemic threshold, whereas preference for the less protective information weakens the overall protective effect. Higher-order interactions exert asymmetric effects on competing information, while social tie weights and activity-driven contacts also significantly influence epidemic spreading. Moreover, the epidemic threshold is jointly affected by recovery probability, activity heterogeneity, information-layer topology, and policy regulation. These findings reveal the cross-layer coupling between higher-order information diffusion and temporal physical contacts.