The global pandemic due to the outbreak of COVID-19 ravages the whole world for more than two years in which all the countries are suffering a lot since December 2019. In order to control this ongoing waves of epidemiological infections, attempts have been made to understand the dynamics of this pandemic in deterministic approach with the help of several mathematical models. In this article characteristics of a multi-wave SIR model have been studied which successfully explains the features of this pandemic waves in India. Stability of this model has been studied by identifying the equilibrium points as well as by finding the eigen values of the corresponding Jacobian matrices. Complex eigen values are found which ultimately give rise to the oscillatory solutions for the three categories of populations, say, susceptible, infected and removed. In this model, a finite probability of the recovered people for becoming susceptible again is introduced which eventually lead to the oscillatory solution in other words. The set of differential equations has been solved numerically in order to obtain the variation for numbers of susceptible, infected and removed people with time. In this phenomenological study, finally an additional modification is made in order to explain the aperiodic oscillation which is found necessary to capture the feature of epidemiological waves particularly in India.
翻译:由于COVID-19的爆发,全球流行病自2019年12月以来使全世界遭受了两年多的破坏,所有国家都在其中遭受了巨大痛苦。为了控制这种持续的流行病感染浪潮,在几个数学模型的帮助下,试图通过确定性方法来理解这一流行病的动态。在本篇文章中,研究了多波SIR模型的特点,成功地解释了印度这一流行病波浪的特征。这一模型的稳定通过确定平衡点和找到相应的Jacobian矩阵的叶根值进行了研究。发现了复杂的艾根值,最终为三类人口(如易感染、感染和迁移)提供了血管变化的解决方案。在这个模型中,复苏者重新变得易感染的可能性有限,最终导致以其他语言得出血管变化的解决方案。一套差异方程式已经用数字方法解决,以便获得易感染、受感染和被驱离的人数的变异数。在这种基因学研究中,最后又进行了进一步的修改,以解释周期性变化,特别是印度的流行病学特征。