Estimating the epidemic threshold on networks by deterministic connections.

Estimating the epidemic threshold on networks by deterministic connections.
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通过确定性连接估计网络上的流行阈值

DOI:
10.1063/1.4901334
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发表时间:
2014-12
期刊:
Chaos (Woodbury, N.Y.)
影响因子:
--
通讯作者:
Zhu G
Zhu G
中科院分区:
其他
文献类型:
--
作者:
Li K;Fu X;Small M;Zhu G

文献摘要

参考文献

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对于许多流行病网络,节点之间的某些连接被视为确定性的,而其余的则是随机的,并且具有不同的连接概率。通过对几个构建的模型进行谱分析,我们发现可以通过只调查确定性连接的信息来估计这些网络的流行阈值。然而,在这些模型中,一般的非均匀随机连接和异构社区结构也被考虑。通过具有上界和下界的不等式实现了流行病阈值的估计,发现与数值模拟非常一致。由于确定性连接比随机性连接更容易检测,本文的工作为真实的传染病网络中传染病阈值的估计提供了一种可行而有效的方法。
For many epidemic networks some connections between nodes are treated as deterministic, while the remainder are random and have different connection probabilities. By applying spectral analysis to several constructed models, we find that one can estimate the epidemic thresholds of these networks by investigating information from only the deterministic connections. Nonetheless, in these models, generic nonuniform stochastic connections and heterogeneous community structure are also considered. The estimation of epidemic thresholds is achieved via inequalities with upper and lower bounds, which are found to be in very good agreement with numerical simulations. Since these deterministic connections are easier to detect than those stochastic connections, this work provides a feasible and effective method to estimate the epidemic thresholds in real epidemic networks.
DOI: 10.1063/1.3673573
发表时间: 2012-03
期刊: Chaos (Woodbury, N.Y.)
影响因子: --
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