ABSTRACT
The highly infectious COVID-19 disease continues to spread throughout the world. It has become a need of the hour to work upon the disease. Mathematical models can help in understanding the growth of a disease. They can project how the disease has been progressing. Analysing the disease behaviour at an early stage can help a lot in controlling its spread in society as soon as possible. The standard SIR (Susceptible-Infected-Removed) model, which is generally applied for infectious diseases, was modified here as SEIRD (Susceptible-Exposed-Infected-Recovered-Dead) and SEIR (Susceptible-Exposed-Infected-Recovered) during the second wave starting from March 1, 2021.
In the first section of this chapter, we introduce an SEIRD model and analyse the transmission of COVID-19 in India using a deterministic approach. Our study using the deterministic approach shows that Covid cases for R 0 = 1.6 peaked at nearly 100 days after the start of the second wave, with cases reaching approximately 2*106 and declining up to 300 cases per day upon reaching October 10, 2021.
In a later section, we propose an SEIR model to study the tranmission dynamics of the deadly disease using the stochastic approach.
In conclusion through either of the approaches, we can say that on reduction of value of R 0, the spread of the disease reduces and there are more chances of it becoming extinct. The reduction in value of R 0 can be made possible by following Covid norms as well as people being aware of the disease and government coming up with effective control strategies.
Keywords: COVID-19; SIR Model; Basic Reproduction Number; Deterministic approach; Stochastic approach.
