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Stability Analysis of SIR Model with Distributed Delay on Complex Networks

机译:复杂网络中具有分布时滞的SIR模型的稳定性分析

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摘要

In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number R0 of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if R01, then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if R0>1, then the system with distributed time delay stabilizes fastest; while R01, the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations.
机译:在本文中,通过充分考虑个体的分布延迟,人口统计学和接触异质性,我们对复杂人群网络上的易感性传染病(SIR)流行模型进行了详细的分析研究。基本复制编号 R 0 的模型由基础网络的拓扑结构决定,个体的属性包括出生率,死亡率,去除率和感染率,并持续分布时间延迟。通过构造合适的Lyapunov泛函并使用Kirchhoff的矩阵树定理,我们研究了无病和地方病平衡点的全局渐近稳定性。具体而言,系统显示阈值行为:if < mi mathvariant =“ script”> R 0 1 ,然后无病平衡是全局渐近稳定的,否则地方病平衡是全局渐近稳定的。此外,获得的结果表明,具有不同类型延迟的SIR模型在传染过程中具有不同的收敛时间:if R 0 > 1 ,则具有分布式时延的系统稳定最快;而 R 0 1 ,具有分布式时延的系统收敛最慢。通过数值仿真证明了这些结果的有效性和有效性。

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