Sahani Saroj Kumar, Jakhad Anjali
Faculty of Mathematics and Computer Science, Department of Mathematics, South Asian University Akbar Bhawan, Chankyapuri, New Delhi, Delhi 110021, India.
MethodsX. 2023 Aug 6;11:102317. doi: 10.1016/j.mex.2023.102317. eCollection 2023 Dec.
The last three years have been the most challenging for humanity due to the COVID-19 pandemic. The novel viral infection has eventually been able to infect most of the human population. It is now considered to be in the endemic stage, meaning it will remain in our world throughout our lifetime. There will be an intermittent outbreak of the COVID infection from time to time. Therefore, it is necessary to formulate a robust Mathematical model to study the dynamics of disease to have a control mechanism in place. In this article, we suggest a modified MSEIR model to explain the dynamics of COVID-19 infection. We assume that a susceptible person contracting the coronavirus develops a transient immunity to the illness. Further, infectives comprise asymptomatic, symptomatic, hospitalized and quarantined individuals. We assume that the incidence rate is of standard type, and susceptible can only become infective if they come in contact with either asymptomatic or symptomatic individuals. This basic and simple model effectively models the various waves every country has seen during the Pandemic. The simple analysis shows that the model could suggest various waves in future if we carefully select the incidence rate for the infection. In summary, we have discussed the following major points in this article. •We have analysed for local behavior infection-free equilibrium solution. Further, a thorough numerical exploration with various parameter settings has been performed to obtain the different cases of infection dynamics of the coronavirus epidemic.•We have found some interesting scenarios which explain the emergence of multiple waves observed in many countries.
过去三年因新冠疫情对人类来说是最具挑战性的。这种新型病毒感染最终得以感染了大部分人类。现在它被认为处于地方流行阶段，这意味着在我们的有生之年它将一直存在于我们的世界。新冠感染会时不时地间歇性爆发。因此，有必要建立一个强大的数学模型来研究疾病动态，以便有一个控制机制。在本文中，我们提出一个改进的MSEIR模型来解释新冠病毒感染的动态。我们假设感染冠状病毒的易感者会对该疾病产生短暂免疫力。此外，感染者包括无症状、有症状、住院和被隔离的个体。我们假设发病率是标准类型，并且易感者只有在与无症状或有症状个体接触时才会变成感染者。这个基本且简单的模型有效地模拟了每个国家在疫情期间所经历的各种疫情波。简单分析表明，如果我们仔细选择感染的发病率，该模型可以预测未来的各种疫情波。总之，我们在本文中讨论了以下要点。•我们分析了无感染平衡解的局部行为。此外，还对各种参数设置进行了全面的数值探索，以获得冠状病毒疫情感染动态的不同情况。•我们发现了一些有趣的情形，它们解释了许多国家出现的多波疫情。
