Numerical Forecasting of Covid-19 Epidemic in Odisha Using S.I.R Model: A Case Study

Abstract

In this paper, we study the effectiveness of SIR model (Susceptible- Infected-Removed) in predicting the future development of infectious disease caused by SARS-CoV-2 virus for the Indian state of Odisha. This model helps in checking the effectiveness of controlling measures like lockdown policies and helps in framing new strategies to control the spread of the disease. We formulate a set of differential equations to find the rate of change of susceptible, infected and removed population with respect to time and solve it using Euler’s method. Using the cumulative data of confirmed cases, we try to find the answers to the question of COVID-19 surge. Also, through this we predict the trend in the spread of covid-19 in the state for the next few months. The analysis includes data from March 1 (which is marked as the start of second wave of COVID) to June 28, 2021. We propose predictions on various parameters and factors related to the spread of COVID-19 and on the number of susceptible, infected and removed population until June 2021. By comparing the daily recorded data with the data from our modeling approaches, we conclude that the spread of COVID-19 can be under control in all communities, if proper lockdown restrictions and strong policies are implemented to control the infection rates.