Self-isolation or borders closing: What prevents the spread of the epidemic better?,Physical Review E

当前位置： X-MOL 学术 › Phys. Rev. E › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Self-isolation or borders closing: What prevents the spread of the epidemic better?
Physical Review E ( IF 2.2 ) Pub Date : 2020-07-09 , DOI: 10.1103/physreve.102.010401
O Valba _{1,

2} , V Avetisov ₂ , A Gorsky _{3,

4} , S Nechaev _{5,

6}

Affiliation

Pandemic propagation of COVID-19 motivated us to discuss the impact of the human network clustering on epidemic spreading. Today, there are two clustering mechanisms which prevent of uncontrolled disease propagation in a connected network: an “internal” clustering, which mimics self-isolation (SI) in local naturally arranged communities, and an “external” clustering, which looks like a sharp frontiers closing (FC) between cities and countries, and which does not care about the natural connections of network agents. SI networks are “evolutionarily grown” under the condition of maximization of small cliques in the entire network, while FC networks are instantly created. Running the standard SIR model on clustered SI and FC networks, we demonstrate that the evolutionary grown clustered network prevents the spread of an epidemic better than the instantly clustered network with similar parameters. We find that SI networks have the scale-free property for the degree distribution

P (k) \sim k^{η}

, with a small critical exponent

- 2 < η < - 1

. We argue that the scale-free behavior emerges as a result of the randomness in the initial degree distributions.

中文翻译：

自我隔离或边界封闭：什么因素可以更好地阻止流行病的传播？

COVID-19的大流行传播促使我们讨论了人类网络集群对流行扩散的影响。如今，有两种聚类机制可以防止疾病在连接的网络中传播，即“内部”聚类，它模仿本地自然排列的社区中的自我隔离（SI），以及“外部”聚类，看起来很尖锐。城市和国家/地区之间的边境关闭（FC），并且不关心网络代理的自然连接。SI网络是在整个网络中最大化小型集团的条件下“进化发展”的，而FC网络则是立即创建的。在群集的SI和FC网络上运行标准SIR模型，我们证明，进化增长的聚类网络比具有相似参数的即时聚类网络更好地防止了流行病的传播。我们发现SI网络具有度分布的无标度特性