Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods

Dilip Kumar Bagal; Arati Rath; Abhishek Barua; Dulu Patnaik

doi:10.1016/j.chaos.2020.110154

Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods

Chaos Solitons Fractals. 2020 Nov:140:110154. doi: 10.1016/j.chaos.2020.110154. Epub 2020 Jul 29.

Authors

Dilip Kumar Bagal¹, Arati Rath², Abhishek Barua³, Dulu Patnaik⁴

Affiliations

¹ Department of Mechanical Engineering, Government College of Engineering, Kalahandi, Bhawanipatna, Odisha, India.
² Department of Computer Applications, National Institute of Technology Jamshedpur, Jamshedpur, Jharkhand, India.
³ Department of Mechanical Engineering, Centre for Advanced Post Graduate Studies, BPUT, Rourkela, Odisha, India.
⁴ Department of Electrical Engineering, Government College of Engineering, Kalahandi, Bhawanipatna, Odisha, India.

Abstract

Owing to the pandemic scenario of COVID-19 disease cases all over the world, the outbreak prediction has become extremely complex for the emerging scientific research. Several epidemiological mathematical models of spread are increasing daily to forecast the predictions appropriately. In this study, the classical susceptible-infected-recovered (SIR) modeling approach was employed to study the different parameters of this model for India. This approach was analyzed by considering different governmental lockdown measures in India. Some assumptions were considered to fit the model in the Python simulation for each lockdown scenario. The predicted parameters of the SIR model exhibited some improvement in each case of lockdown in India. In addition, the outcome results indicated that extreme interventions should be performed to tackle this type of pandemic situation in the near future.

Keywords: COVID-19; India; Lockdown; Python; SIR Model.