互联网络上的传染病传播

异构网络上传染病与级联相互作用的动力学行为

Dynamic Behavior of Interacting between Epidemics and Cascades on Heterogeneous Networks

传染病传播和连锁失效是复杂网络上两个重要的动力学过程。历史上，它们一直被单独研究。但在现实世界中，这两种动力有时会相互作用。本文将SIR传染病传播模型与局部负荷分担连锁故障模型相结合，提出了一种基于局部负荷分担的连锁故障模型。在该模型中，存在一个容忍参数的临界值，即具有高感染概率的流行病是否能够传播并感染网络的一部分。当容忍度参数小于临界值时，连锁失效切断了大量的路径，阻断了疫情的局部传播。当容忍度参数大于临界值时，传染病扩散并感染网络的一部分。提出了一种估算临界值的方法。在仿真中，我们在Barabási-Albert（BA）网络中验证了该方法的有效性。

Self-isolation or borders closing: what prevents epidemic spreading better?

Pandemic distribution of COVID-19 in the world has motivated us to discuss combined effects of network clustering and adaptivity on epidemic spreading. We address the question concerning the choice of optimal mechanism for most effective prohibiting disease propagation in a connected network: adaptive clustering, which mimics self-isolation (SI) in local communities, or sharp instant clustering, which looks like frontiers closing (FC) between cities and countries. SI-networks are "adaptively grown" under condition of maximization of small cliques in the entire network, while FC-networks are "i…

多层网络中的传染病传播和键渗流

Epidemic spreading and bond percolation in multilayer networks

研究了多层网络中任意链路数的SIR模型。通过映射到键渗流，我们给出了任意层数的传染病阈值和感染率的解析表达式。这些结果提供了一个精确的预测的传染病阈值的无限局部树状多层网络，和更一般的多层网络的传染病阈值的下界。由两个互连的网络形成的多层网络的情况下，具体研究作为一个功能的层内和跨层的度分布。我们发现，流行阈值强烈依赖于多层结构的度相关性。最后，我们将我们的结果与退火近似的易感-感染-易感（SIS）模型的结果。

聚类和网格排序在传染病传播中的作用

The role of clustering and gridlike ordering in epidemic spreading

流行病的传播是由构成人口基础的联结模式决定的。虽然已经注意到，病毒在全球距离较近的网络上更容易传播，但要找到办法来揭示地方相互联系的确切作用，仍然是一个巨大的挑战。这样的拓扑性质非常自然地进入我们的两时间步描述的框架，也提供了一种新的方法来跟踪概率系统。该方法阐述了SIS型的流行过程，导致循环的作用，长度为4的流行病的发病定量解释。

基于传染病传播的相互依赖网络的渗流理论

Percolation Theory on Interdependent Networks Based on Epidemic Spreading

我们考虑相互依赖的局部树状网络上的渗流，最近由Buldyrev等人介绍，Nature 464，1025（2010），并证明，可以通过删除所有对故障级联的引用来简化概念上的问题。这样的级联确实存在，但它们的明确处理只是使理论复杂化-这是一个简单的扩展，在一个单一的网络上通常的传染病传播理论。我们的方法还有一个额外的好处，即它是直接根据序参量来制定的，并且它的模块化结构可以很容易地扩展到其他问题，例如，扩展到任何数量的相互依赖的网络，或具有依赖链接的网络。

Spreading processes in "post-epidemic" environments

We analyze infection spreading processes in a system where only a fraction $p$ of individuals can be affected by disease, while remaining $1-p$ individuals are immune. Such a picture can emerge as a natural consequence of previously terminated epidemic process or arise in formerly vaccinated population. To this end, we apply the synchronous cellular automata algorithm studying stationary states and spatial patterning in SI, SIS and SIR models on a square lattice with the fraction $p$ of active sites. A concept of "safety patterns" of susceptible agents surrounded by immune individuals naturall…

加权网络中的传染病传播

Epidemic spread in weighted networks

我们研究了无标度网络中传染病传播的详细过程，该网络的权值表示两个人或计算机之间的熟悉程度。结果表明，网络传播速度先达到峰值后衰减，呈现幂律时间行为;与非加权网络相比，虽然网络强度较大的节点更容易被感染，但没有发现精确的层次动力学。

Spreading processes in "post-epidemic" environments. II. Safety patterns on scale-free networks

This paper continues our previous study on spreading processes in inhomogeneous populations consisting of susceptible and immune individuals [V. Blavatska, Yu. Holovatch, Physica A 573, 125980 (2021)]. A special role in such populations is played by "safety patterns" of susceptible nodes surrounded by the immune ones. Here, we analyze spreading on scale-free networks, where the distribution of node connectivity $k$ obeys a power-law decay $\sim k^{-λ}$. We assume, that only a fraction $p$ of individual nodes can be affected by spreading process, while remaining $1-p$ are immune. We apply the s…

随机环境中的远距离传染病传播

Long-range epidemic spreading in a random environment

考虑了随机环境中的远程传染病传播问题，考虑了一个猝灭的无序$d$ -维接触过程，其传染率随距离的增加而衰减为$1/r^{d+σ}$。我们研究了模型的动力学行为，并低于流行阈值的强无序重整化群方法的一个变种，并通过蒙特卡罗模拟在一个和两个空间维度。从一个单一的感染网站，平均生存概率被发现衰减为$P(t) \sim t^{-d/z}$乘法对数校正。在流行阈值以下，出现Griffiths阶段，其中动力学指数$z$随控制参数连续变化，并且随着阈值的接近而趋向于$z_c=d+σ$。在阈值，感染的集群（在存活的试验）的空间扩展被发现与$R(t) \sim t^{1/z_c}$增长与乘法对数校正，并发现在存活的试验中感染的网站的平均数增加与$N_s(t) \sim (\ln t)^χ$与$χ=2$在一个维度。

Dropping mortality by increasing connectivity in plant epidemics

Pathogen introduction in plant communities can cause serious impact and biodiversity losses that may take long time to manage and restore. Effective control of epidemic spreading in the wild is a problem of paramount importance, because of its implications in conservation and potential economic losses. Understanding the mechanisms that hinder pathogen's propagation is, therefore, crucial. Usual modelization approaches in epidemic spreading are based in compartmentalized models, without keeping track of pathogen's concentrations during spreading. In this contribution we present and fully analyz…