Department of Mathematics, Deshbandhu College, University of Delhi, New Delhi, 110019, India.
DBC i4 Centre, Deshbandhu College, University of Delhi, New Delhi, 110019, India.
Sci Rep. 2021 Oct 11;11(1):20124. doi: 10.1038/s41598-021-99088-0.
The Novel Coronavirus which emerged in India on January/30/2020 has become a catastrophe to the country on the basis of health and economy. Due to rapid variations in the transmission of COVID-19, an accurate prediction to determine the long term effects is infeasible. This paper has introduced a nonlinear mathematical model to interpret the transmission dynamics of COVID-19 infection along with providing vaccination in the precedence. To minimize the level of infection and treatment burden, the optimal control strategies are carried out by using the Pontryagin's Maximum Principle. The data validation has been done by correlating the estimated number of infectives with the real data of India for the month of March/2021. Corresponding to the model, the basic reproduction number [Formula: see text] is introduced to understand the transmission dynamics of COVID-19. To justify the significance of parameters we determined the sensitivity analysis of [Formula: see text] using the parameters value. In the numerical simulations, we concluded that reducing [Formula: see text] below unity is not sufficient enough to eradicate the COVID-19 disease and thus, it is required to increase the vaccination rate and its efficacy by motivating individuals to take precautionary measures.
2020 年 1 月 30 日在印度出现的新型冠状病毒在健康和经济基础上已经成为了该国的一场灾难。由于 COVID-19 的传播迅速变化，对其长期影响进行准确预测是不可行的。本文引入了一个非线性数学模型来解释 COVID-19 感染的传播动态，并在之前的基础上提供疫苗接种。为了将感染和治疗负担的水平最小化，利用庞特里亚金极大值原理来执行最优控制策略。通过将估计的感染者数量与 2021 年 3 月印度的实际数据进行关联，对数据进行了验证。针对该模型，引入基本再生数 [Formula: see text]来理解 COVID-19 的传播动态。为了证明参数的重要性，我们使用参数值对 [Formula: see text]进行了敏感性分析。在数值模拟中，我们得出结论，将 [Formula: see text]降低到 1 以下不足以消除 COVID-19 疾病，因此需要通过激励个人采取预防措施来提高疫苗接种率及其效果。
