Oscillatory dynamics driven induced by higher-order interactions and self-awareness in multiplex information–epidemic systems

In studies of information-epidemic coevolution on higher-order networks, a key question is how information diffusion in information models with higher-order interactions influences epidemic dynamics. However, existing research has largely overlooked the role of self-awareness, resulting in incomplete analysis of phenomena. Here, we investigate how oscillatory behavior arising in information models with higher-order interactions affects epidemic dynamics. We show that self-awareness acts as an external input that prevents the information layer from falling into an absorbing state, thereby enabling oscillations to appear in simulations. Increasing self-awareness drives the system’s order parameters from periodic to damped oscillations, and within the periodic regime, self-awareness exerts a double-edged effect on the average epidemic prevalence. Dynamical correlations further suppress oscillations in static information networks relative to annealed ones. Most importantly, in the study of information-epidemic dynamics on higher-order networks, our results emphasize that self-awareness can alter the phase-transition type of the information-layer order parameter. Moreover, its coupling with higher-order interactions generates additional novel dynamical behaviors. Our research may readily be extended to a broader field, rather than the network epidemiology in this paper.