A multicompartment mathematical model to study the dynamic behaviour of COVID-19 using vaccination as control parameter

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 ([Formula: see text] ), vaccinated ([Formula: see text] ), exposed ([Formula: see text] ), asymptomatic infected ([Formula: see text] ), symptomatic infected ([Formula: see text] ), isolated ([Formula: see text] ), hospitalised ([Formula: see text] ), recovered ([Formula: see text] ). 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, [Formula: see text] , the disease-free equilibrium is locally asymptotically stable; but, if, [Formula: see text] 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.