The impact of high-order multi-source information verification mechanisms on propagation dynamics in multilayer high-order networks

In epidemic dynamics, the coupling between information diffusion and disease transmission is profoundly influenced by higher-order interactions. To capture this effect, we propose a higher-order multi-source information confirmation mechanism, which accounts for individuals’ reliance on multiple, mutually reinforcing sources of information when adopting protective behaviors. By employing a Markov chain framework, we derive an analytical description of the coupled dynamics, and validate our theoretical predictions through numerical simulations. Our results reveal that when perceptive nodes strongly attenuate higher-order transmission in the physical layer, the density of perceptive nodes exhibits a nonlinear response to the disease transmission rate—first increasing and then decreasing. Furthermore, higher-order information in the physical layer (layer B) exerts a stronger regulatory effect on disease spreading than that in the information layer (layer A). This cross-layer confirmation of neighbors’ perception and infection states, mediated by higher-order interactions, leads to a lower steady-state infection density in the physical layer and a higher perception density in the information layer compared with a scenario without such multi-source confirmation.