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用有限数量的免疫单位控制疫情。

Suppressing epidemics with a limited amount of immunization units.

作者信息

Schneider Christian M, Mihaljev Tamara, Havlin Shlomo, Herrmann Hans J

机构信息

Computational Physics, IfB, ETH Zurich, Schafmattstrasse 6, CH-8093 Zurich, Switzerland.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 1):061911. doi: 10.1103/PhysRevE.84.061911. Epub 2011 Dec 15.

Abstract

The way diseases spread through schools, epidemics through countries, and viruses through the internet is crucial in determining their risk. Although each of these threats has its own characteristics, its underlying network determines the spreading. To restrain the spreading, a widely used approach is the fragmentation of these networks through immunization, so that epidemics cannot spread. Here we develop an immunization approach based on optimizing the susceptible size, which outperforms the best known strategy based on immunizing the highest-betweenness links or nodes. We find that the network's vulnerability can be significantly reduced, demonstrating this on three different real networks: the global flight network, a school friendship network, and the internet. In all cases, we find that not only is the average infection probability significantly suppressed, but also for the most relevant case of a small and limited number of immunization units the infection probability can be reduced by up to 55%.

摘要

疾病在学校中的传播方式、流行病在国家间的传播方式以及病毒在互联网上的传播方式,对于确定它们的风险至关重要。尽管这些威胁各自具有其自身特点,但其潜在网络决定了传播情况。为抑制传播,一种广泛使用的方法是通过免疫使这些网络碎片化,从而使流行病无法传播。在此,我们开发了一种基于优化易感规模的免疫方法,该方法优于基于免疫具有最高介数的边或节点的最知名策略。我们发现,网络的脆弱性可显著降低,我们在三个不同的真实网络上证明了这一点:全球航班网络、学校友谊网络和互联网。在所有情况下,我们发现不仅平均感染概率被显著抑制,而且对于免疫单位数量少且有限的最相关情况,感染概率可降低多达55%。

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