Dynamical modelling and analysis of COVID-19 in India

TL;DR

This paper models the spread of COVID-19 in India using an SEIR dynamical model, estimating transmission rates, calibrating parameters with official data, and evaluating potential scenarios to inform containment strategies.

Contribution

It introduces a calibrated SEIR model specific to India and analyzes various scenarios, emphasizing the role of government and individual efforts in controlling the pandemic.

Findings

Estimated transmission rates during early outbreak

Calibrated model aligns with official infection data

Highlighted importance of containment efforts

Abstract

We consider the pandemic spreading of COVID-19 in India after the outbreak of the coronavirus in Wuhan city, China. We estimate the transmission rate of the initial infecting individuals of COVID-19 in India by using the officially reported data at the early stage of the epidemic with the help of Susceptible (S), Exposed (E), Infected (I), and Removed (R) population model, the so-called SEIR dynamical model. Numerical analysis and model verification are performed to calibrate the system parameters with official public information about the number of people infected, and then to evaluate several COVID -19 scenarios potentially applicable to India. Our findings provide an estimation of disease occurrence in the near future and also demonstrate the importance of governmental and individual efforts to control the effects and time of the pandemic-related critical situations. We also give special emphasis to individual reactions in the containment process.