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10.1103/PhysRevE.102.010401 http://scihub22266oqcxt.onion/10.1103/PhysRevE.102.010401 32794949!ä!32794949 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Phys+Rev+E 2020 ; 102 (1-1): 010401 Nephropedia Template TP {{tp|p=32794949|t=2020. Self-isolation or borders closing: What prevents the spread of the epidemic better?|pdf=|usr=}}{{32794949}} gab.com Text Self-isolation or borders closing: What prevents the spread of the epidemic better JO: Phys Rev E http://www.kidney.de/pget.php?&tw=1&pmid=32794949 #FOAvip 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) approximately k;eta, with a small critical exponent -2<eta<-1. We argue that the scale-free behavior emerges as a result of the randomness in the initial degree distributions. Twit Text FOAVip Self-isolation or borders closing: What prevents the spread of the epidemic better ????Phys Rev E http://www.kidney.de/pget.php?&tw=1&pmid=32794949 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32794949 #FOAvip English Wikipedia <ref>{{Cite pmid|32794949}}</ref> Self-isolation or borders closing: What prevents the spread of the epidemic better? #MMPMID32794949 Valba O; Avetisov V; Gorsky A; Nechaev S Phys Rev E 2020[Jul]; 102 (1-1): 010401 PMID32794949show ga 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) approximately k;eta, with a small critical exponent -2 äSelf-isolation or borders closing: What prevents the spread of the epi(epmc).pdf DeepDyve Pubget Overpricing