涉及移民和疫苗接种的COVID-19延迟传播模型的稳定性分析

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS

Communications in Mathematical Biology and Neuroscience Pub Date : 2023-01-01 DOI:10.28919/cmbn/8151

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引用次数: 0

摘要

本文提出并分析了具有移民、疫苗接种和一般发病率函数的COVID-19延迟传播模型的动力学行为。进入所提模型的时间延迟表示潜伏期。首先对模型的适定性进行了研究。此外，我们构造了适当的Lyapunov函数来证明平衡点的全局稳定性。为了支持理论结果，在研究的最后给出了数值模拟。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Stability analysis of a delayed COVID-19 transmission model involving immigration and vaccination

In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.

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来源期刊

Communications in Mathematical Biology and Neuroscience COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

2.10

自引率

15.40%

发文量

期刊介绍： Communications in Mathematical Biology and Neuroscience (CMBN) is a peer-reviewed open access international journal, which is aimed to provide a publication forum for important research in all aspects of mathematical biology and neuroscience. This journal will accept high quality articles containing original research results and survey articles of exceptional merit.