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Nonlinear dynamical analysis and control strategies of a network-based SIS epidemic model with time delay

机译:基于网络的SIS流行病模型与时滞的非线性动力学分析与控制策略

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In this paper, we establish a susceptible-infected-susceptible (SIS) epidemic model with nonlinear incidence rate and time delay on complex networks. Firstly, according to the existence of a positive equilibrium point, we work out the threshold values R-0 and lambda(c) of disease propagation. Secondly, we demonstrate the stabilities of the disease-free equilibrium point and the disease-spreading equilibrium point by constructing Lyapunov function and applying delay differential equations theorem. Thirdly, four different control strategies are investigated and compared, including uniform immunization control, acquaintance immunization control, active immunization control and optimal control. Finally, we perform representative numerical simulations to illustrate the theoretical results and further discover that the nonlinear incidence rate can more accurately reflect individual psychological activities when a certain disease outbreaks at a high level. (C) 2019 Elsevier Inc. All rights reserved.
机译:在本文中,我们建立了具有非线性发生率和复杂网络的非线性发生率和时间延迟的敏感感染易感模型。首先,根据正平衡点的存在,我们制定疾病繁殖的阈值R-0和Lambda(C)。其次,我们通过构建Lyapunov函数和应用延迟微分方程定理来证明无疾病平衡点和疾病扩散均衡点的稳定性。第三,研究了四种不同的控制策略,并进行了比较,包括均匀免疫控制,熟人免疫控制,主动免疫控制和最佳控制。最后,我们执行代表性的数值模拟以说明理论结果,进一步发现,当在高水平的某种疾病爆发时,非线性发生率可以更准确地反映个体心理活动。 (c)2019 Elsevier Inc.保留所有权利。

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