COVID-19传播模型的动态分析及其在疫苗接种和社会距离下的模拟

Ummu Habibah
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引用次数: 0

摘要

本文介绍了该模型的创建和动态分析,并对疫苗接种和社会隔离对COVID-19传播的影响进行了分析。易感个体亚群(S)、暴露个体亚群(E)、感染个体亚群(I)和恢复个体亚群(R)是构成该模型中人类种群的四个亚群。这一概念是基于这样一种观念,即从疾病中康复的人仍然容易再次感染。所进行的动力学分析包括平衡点的确定、基本再现数(R_0)和平衡点局部稳定性的评价。动力学分析结果表明,模型中存在两个平衡点:地方病平衡点和无病平衡点。数学R_0>1表示存在地方性平衡点,而无病平衡点总是存在。如果满足Routh-Hurwitz条件,地方病平衡点是局部渐近稳定的,而当R_0<1时,无病平衡点是局部渐近稳定的。数值模拟结果与分析结果一致。
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Dynamical Analysis of the Spread of COVID-19 model and its Simulation with Vaccination and Social Distancing
The model's creation and dynamical analysis were covered in this paper, SEIRS on the effects of vaccination and social isolation on the transmission of COVID-19. The susceptible individual subpopulation (S), the exposed individual subpopulation (E), the infected individual subpopulation (I), and the recovered individual subpopulation (R) are the four subpopulations that make up the human population in this model. This concept is founded on the notion that someone who has recovered from the illness is nonetheless vulnerable to reinfection. The carried out dynamical analysis includes the determination of the equilibrium point, the fundamental reproduction number (R_0), and evaluation of the local stability of the equilibrium point. The outcomes of the dynamical analysis show that there are two equilibrium points in the model: the endemic equilibrium point and the disease-free equilibrium point. Mathematical R_0>1 indicates the presence of an endemic equilibrium point, whereas a disease-free equilibrium point is always present. If the Routh-Hurwitz conditions are met, the endemic equilibrium point is locally asymptotically stable, but the disease-free equilibrium point is locally asymptotically stable if R_0<1. The numerical simulation results are consistent with the analyses' findings.
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审稿时长
24 weeks
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