Individual interactions play a crucial role in the co-evolution process of awareness and epidemics; these interactions involve pairwise and higher-order types. Previous research usually assumed that individual interactions are all valid and static, overlooking the fact that some interactions may be invalid and time-varying. Notably, diffusion phenomena cannot occur if interactions lose their validity. To address this gap, a novel coupled model is proposed to study the effect of time-varying interaction validity on the co-evolution of awareness and epidemics in a multiplex high-order network. Individual activity and life-cycle theory are employed to model the time-varying validity of interactions, which is further characterized using threshold functions. Simulation experiments reveal that increasing individual activity will increase the validity of interactions, which then leads to the prevalence of epidemics. In addition, maximizing epidemic control can be achieved by increasing activity in the virtual layer while reducing activity in the physical layer. Moreover, the results in more densely interacted communities suggest that more stringent control measures are required to bring the epidemic to extinction.

中文翻译：

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个体交互的时变效度对多元高阶网络中意识和流行病协同进化的影响


个体互动在意识和流行病的共同进化过程中起着至关重要的作用;这些交互涉及成对和高阶类型。以前的研究通常假设个体交互都是有效和静态的，而忽略了某些交互可能是无效且随时间变化的事实。值得注意的是，如果相互作用失去了有效性，扩散现象就不会发生。为了解决这一差距，提出了一种新的耦合模型来研究时变交互有效性对多路高阶网络中意识和流行病协同进化的影响。采用个体活动和生命周期理论来模拟交互作用的时变有效性，并使用阈值函数进一步表征。模拟实验表明，增加个体活动会增加交互的有效性，从而导致流行病的流行。此外，可以通过增加虚拟层的活动同时减少物理层的活动来实现疫情控制。此外，在互动更密集的社区中，结果表明需要采取更严格的控制措施来消除这种流行病。