发表机构
Universidade Federal de Viçosa; Universidade Federal de São Paulo; Universidade de São Paulo（维索萨联邦大学; 圣保罗联邦大学; 圣保罗大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究通过理论分析与随机模拟，发现节点间歇性（非马尔可夫性）比边间歇性更有效抑制流行病传播，短且均匀的间隔时间提高传播阈值，为干预策略提供新视角。
AI 中文摘要
社会互动由可能高度异质性的网络所塑造，其中一些个体可能与许多其他人互动。然而，物理和时间上的限制限制了同时互动的数量，使得社会接触本质上是间歇性的。在此，我们研究间歇性如何影响复杂网络上的流行病传播，考虑两种不同的机制：连接（边）的间歇性和个体本身（节点）的间歇性，其活跃和不活跃周期由具有广泛分布的间隔时间的更新过程控制。结合机制性理论方法与随机模拟，我们表明这两种间歇性形式对流行病传播具有根本不同的影响。边的间歇性在很大程度上保留了维持传播的机制，流行病行为可以主要由接触机会的平均减少来解释。相比之下，节点的间歇性在遏制传播方面更为有效，因为所有接触的同时中断抑制了传播，而恢复过程则独立继续。节点间歇性的非马尔可夫性质起关键作用：更短且异质性更小的间隔时间提高了流行病阈值并增强了流行病遏制。我们的结果强调了个人活动的时间组织，超越平均接触减少，能显著改变流行病传播，并可能有助于利用社会和生物接触网络中间歇性的干预措施。
英文摘要
Social interactions are shaped by networks that can be highly heterogeneous, with some individuals potentially interacting with many others. However, physical and temporal constraints limit the number of simultaneous interactions, making social contacts inherently intermittent. Here, we investigate how intermittency affects epidemic spreading on complex networks considering two distinct mechanisms: intermittency of connections (links) and individuals themselves (nodes), with periods of activity and inactivity governed by renewal processes with broadly distributed inter-event times. Combining mechanistic theoretical approaches with stochastic simulations, we show that these two forms of intermittency have fundamentally different effects on epidemic spreading. Link intermittency largely preserves the mechanisms responsible for sustaining transmission, and epidemic behavior can be largely explained by the average reduction in contact opportunities. Contrastingly, node intermittency is substantially more effective at containing spreading because the simultaneous interruption of all contacts suppresses transmission while recovery continues independently. The non-Markovian nature of node intermittency plays a key role: shorter and less heterogeneous inter-event times increase epidemic thresholds and enhance epidemic containment. Our results highlight how the temporal organization of individual activity, beyond the average reduction in contacts, can substantially alter epidemic spreading and may help inform interventions that exploit intermittency in social and biological contact networks.
Comments9 pages, 4 figures
