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Master equation analysis of mesoscopic localization in contagion dynamics on higher-order networks
Physical Review E ( IF 2.4 ) Pub Date : 2021-03-01 , DOI: 10.1103/physreve.103.032301
Guillaume St-Onge , Vincent Thibeault , Antoine Allard , Louis J. Dubé , Laurent Hébert-Dufresne

Simple models of infectious diseases tend to assume random mixing of individuals, but real interactions are not random pairwise encounters: they occur within various types of gatherings such as workplaces, households, schools, and concerts, best described by a higher-order network structure. We model contagions on higher-order networks using group-based approximate master equations, in which we track all states and interactions within a group of nodes and assume a mean-field coupling between them. Using the susceptible-infected-susceptible dynamics, our approach reveals the existence of a mesoscopic localization regime, where a disease can concentrate and self-sustain only around large groups in the network overall organization. In this regime, the phase transition is smeared, characterized by an inhomogeneous activation of the groups. At the mesoscopic level, we observe that the distribution of infected nodes within groups of the same size can be very dispersed, even bimodal. When considering heterogeneous networks, both at the level of nodes and at the level of groups, we characterize analytically the region associated with mesoscopic localization in the structural parameter space. We put in perspective this phenomenon with eigenvector localization and discuss how a focus on higher-order structures is needed to discern the more subtle localization at the mesoscopic level. Finally, we discuss how mesoscopic localization affects the response to structural interventions and how this framework could provide important insights for a broad range of dynamics.

中文翻译:

高阶网络传染动力学中介观局部化的主方程分析

传染病的简单模型倾向于假定个人是随机混合的,但真正的互动并不是成对的随机接触:它们发生在各种类型的聚会中,例如工作场所,家庭,学校和音乐会,最好用高阶网络结构来描述。我们使用基于组的近似主方程对高阶网络上的传染进行建模,在该方程中,我们跟踪一组节点内的所有状态和相互作用,并假设它们之间的均值场耦合。利用易感感染的动态,我们的方法揭示了介观定位机制的存在,在这种机制下,疾病只能在网络整体组织中的大群体周围集中和自我维持。在这种情况下,相变被涂抹,其特征在于基团的活化不均匀。在介观水平上,我们观察到相同大小的组中受感染节点的分布可能非常分散,甚至是双峰的。当考虑异构网络时,无论是在节点级别还是在组级别,我们都通过分析来表征与结构参数空间中的介观局部化相关的区域。我们从特征向量定位角度对这一现象进行了透视,并讨论了如何需要关注高阶结构才能在介观水平上辨别更细微的定位。最后,我们讨论了介观局部化如何影响对结构性干预的反应,以及该框架如何为广泛的动力学提供重要的见解。甚至双峰。当考虑异构网络时,无论是在节点级别还是在组级别,我们都通过分析来表征与结构参数空间中的介观局部化相关的区域。我们从特征向量定位角度对这一现象进行了透视,并讨论了如何需要关注高阶结构才能在介观水平上辨别更细微的定位。最后,我们讨论了介观局部化如何影响对结构性干预的反应,以及该框架如何为广泛的动力学提供重要见解。甚至双峰。当考虑异构网络时,无论是在节点级别还是在组级别,我们都通过分析表征与结构参数空间中的介观局部化相关的区域。我们从特征向量定位角度对这一现象进行了透视,并讨论了如何需要关注高阶结构才能在介观水平上辨别更细微的定位。最后,我们讨论了介观局部化如何影响对结构性干预的反应,以及该框架如何为广泛的动力学提供重要的见解。我们从特征向量定位角度对这一现象进行了透视,并讨论了如何需要关注高阶结构才能在介观水平上辨别更细微的定位。最后,我们讨论了介观局部化如何影响对结构性干预的反应,以及该框架如何为广泛的动力学提供重要的见解。我们从特征向量定位角度对这一现象进行了透视,并讨论了如何需要关注高阶结构才能在介观水平上辨别更细微的定位。最后,我们讨论了介观局部化如何影响对结构性干预的反应,以及该框架如何为广泛的动力学提供重要的见解。
更新日期:2021-03-01
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