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

作     者：Valba, O. Avetisov, V. Gorsky, A. Nechaev, Sergei 

作者机构：Department of Applied Mathematics National Research University Higher School of Economics Moscow101000 Russia Federal Research Center of Chemical Physics RAS Moscow119991 Russia Institute of Information Transmission Problems RAS Moscow127051 Russia Moscow Institute of Physics and Technology Dolgoprudny141700 Russia Interdisciplinary Scientific Center Poncelet CNRS UMI 2615 Moscow119002 Russia P.N. Lebedev Physical Institute RAS Moscow119991 Russia 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2020年

核心收录：

主　　题：Epidemiology 

摘      要：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 areadaptively grown under condition of maximization of small cliques in the entire network, while FC-networks areinstantly created. Running the standard SIR model on clustered SI- and FC-networks, we demonstrate that the adaptive network clustering prohibits the epidemic spreading better than the instant clustering in the network with similar parameters. We found that SI model has scale-free property for degree distribution P(k) ∼ kη with small critical exponent −2 Copyright © 2020, The Authors. All rights reserved.