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Robustness and fragility of the susceptible-infected-susceptible epidemic models on complex networks

机译:复杂网络上敏感感染易感疫情模型的鲁棒性和脆弱性

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We analyze two alterations of the standard susceptible-infected-susceptible (SIS) dynamics that preserve the central properties of spontaneous healing and infection capacity of a vertex increasing unlimitedly with its degree. All models have the same epidemic thresholds in mean-field theories but depending on the network properties, simulations yield a dual scenario, in which the epidemic thresholds of the modified SIS models can be either dramatically altered or remain unchanged in comparison with the standard dynamics. For uncorrelated synthetic networks having a power-law degree distribution with exponentγ < 5/2, the SIS dynamics are robust exhibiting essentially the same outcomes for all investigated models. A threshold in better agreement with the heterogeneous rather than quenched mean-field theory is observed in the modified dynamics for exponentγ > 5/2. Differences are more remarkable for γ > 3, where a finite threshold is found in the modified models in contrast with the vanishing threshold of the original one. This duality is elucidated in terms of epidemic lifespan on star graphs. We verify that the activation of the modified SIS models is triggered in the innermost component of the network given by a k-core decomposition for γ < 3 while it happens only for γ < 5/2 in the standard model. For γ > 3, the activation in the modified dynamics is collective involving essentially the whole network while it is triggered by hubs in the standard SIS. The duality also appears in the finite-size scaling of the critical quantities where mean-field behaviors are observed for the modified but not for the original dynamics. Our results feed the discussions about the most proper conceptions of epidemic models to describe real systems and the choices of the most suitable theoretical approaches to deal with these models.
机译:我们分析了标准敏感感染易感(SIS)动态的两种改变,可保持顶点的自发愈合和感染能力无限地增加的核心性质。所有型号在平均视场理论中具有相同的疫情阈值,而是根据网络属性,模拟产生了一种双场景,其中修改的SIS模型的疫情阈值可以与标准动态相比显着变化或保持不变。对于具有具有exconentγ<5/2的电力法度分布的不相关的合成网络,SIS动态非常强大地展示所有调查模型的相同结果。在exconentγ> 5/2的修改动态中观察到与异构γ> 5/2的改进动态更好地与异质而不是淬火平均场理论更好的阈值。对于γ> 3,差异更为显着,其中在修改模型中,与原始的消失阈值相反,在修改模型中找到有限阈值。这种二元性在星形图中阐明了疫情。我们验证了修改的SIS模型的激活在通过γ<3的k核分解给出的网络的最内部分量中触发,而标准模型中仅适用于γ<5/2的γ<3。对于γ> 3,修改动态中的激活是集体涉及整个网络,同时由标准SIS中的集线器触发。二元性也出现在临界量的有限量缩放中,其中对于修改但不适用于原始动态的平均值。我们的结果涉及关于疫情模型最适当的概念的讨论,以描述真实的系统和最适合处理这些模型的理论方法的选择。

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