Mathematical Analysis of SEIR Model to Prevent COVID-19 Pandemic

This paper is to analyze Susceptible-Exposed-Infectious-Recovered (SEIR) COVID-19 pandemic model. In this article, a modified SEIR model is constructed, and is also discussed various aspects of it with mathematical analysis to study the dynamic behavior of this model. The spread of this disease through immigration can be represented by the SEIR model. COVID-19 is a highly infectious disease that spreads through talking, sneezing, coughing, and touching. In this model, there is an incubation period during the spread of the disease. During the gestation period, a patient is attacked by SARS-CoV-2 coronavirus and shows symptoms of COVID-19, but cannot spread the disease. The horizontal transmission of COVID-19 worldwide can be represented and explained by SEIR model. Maximal control of the pandemic disease COVID-19 can be possible by the optimum vaccination policies. The study also investigates the equilibrium of the disease. In the study, a Lyapunov function is created to analyze the global stability of the disease-free equilibrium. The generation matrix method is analyzed to obtain the basic reproduction number and has discussed the global stability of COVID-19 spreading.