A delay differential equation model on Covid-19 with vaccination strategy                                                      

Gaurang Sharma, Amit Sharma
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Abstract

In this paper, we have extended SEIR model of COVID- 19. The model incorporates two vital aspects in the form of vaccine compartment and constant time delay. The vaccination and time delay provide the information about immune protection and actual existence of the infection among the individuals, respectively. The model is analysed numerically and numerical simulation are executed for three different initial histories and constant time delays which affirm the biological relevance of the system. The analysis includes disease-free equilibrium (DFE), endemic equilibrium, and the basic reproduction number. The stability analysis is performed which reveal the asymptotic stability of the DFE when the basic reproduction number R0 < 1. The study addresses the boundedness and positivity of the solution as the time delay approaches zero. In addition, sensitivity analysis and contour plots for R0 with different parameters offer deeper insights into the model. The impact of vaccination and vaccine inefficacy on the model dynamics is explored.
带疫苗接种策略的 Covid-19 延迟微分方程模型
在本文中,我们扩展了 COVID- 19 的 SEIR 模型。该模型包含两个重要方面,即疫苗分区和恒定时间延迟。疫苗接种和时间延迟分别提供了免疫保护和个体间实际存在感染的信息。我们对该模型进行了数值分析,并对三种不同的初始历史和恒定的时间延迟进行了数值模拟,从而确定了该系统的生物学相关性。分析包括无病平衡(DFE)、地方病平衡和基本繁殖数。稳定性分析揭示了当基本繁殖数 R0 < 1 时 DFE 的渐进稳定性。当时间延迟趋近于零时,研究涉及解的有界性和实在性。此外,对不同参数 R0 的敏感性分析和等值线图提供了对模型更深入的见解。研究还探讨了疫苗接种和疫苗无效对模型动态的影响。
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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