Kurmi Sonu, Chouhan Usha
Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh India.
Nonlinear Dyn. 2022;109(3):2185-2201. doi: 10.1007/s11071-022-07591-4. Epub 2022 Jun 13.
To analyse novel coronavirus disease (COVID-19) transmission in India, this article provides an extended SEIR multicompartment model using vaccination as a control parameter. The model considers eight classes of infection: susceptible ( ), vaccinated ( ), exposed ( ), asymptomatic infected ( ), symptomatic infected ( ), isolated ( ), hospitalised ( ), recovered ( ). To begin, a mathematical study is performed to demonstrate the suggested model's uniform boundedness, epidemic equilibrium, and basic reproduction number. The findings indicate that if, , the disease-free equilibrium is locally asymptotically stable; but, if, the equilibrium is unstable. Secondly, we examine the effect on those who have received vaccinations with what are deemed optimal values. The suggested model is numerically simulated using MATLAB 14.0, and the results confirm the capacity of the proposed model to provide an accurate forecast of the progress of the epidemic in India. Finally, we examine the impact of immunisation on COVID-19 dissemination.
为分析新型冠状病毒病(COVID-19)在印度的传播情况,本文提供了一个扩展的SEIR多隔室模型,将疫苗接种作为控制参数。该模型考虑了八类感染状态:易感者( )、已接种者( )、暴露者( )、无症状感染者( )、有症状感染者( )、隔离者( )、住院者( )、康复者( )。首先,进行数学研究以证明所提出模型的一致有界性、流行平衡点和基本再生数。研究结果表明,如果 ,无病平衡点是局部渐近稳定的;但是,如果 ,平衡点是不稳定的。其次,我们用最优值来研究对已接种疫苗者的影响。使用MATLAB 14.0对所提出的模型进行数值模拟,结果证实了该模型能够准确预测印度疫情的发展。最后,我们研究了免疫接种对COVID-19传播的影响。