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

• Published in: Chaos, solitons and fractals solitons and fractals, 2020-11, Vol.140, p.110154-110154, Article 110154
• Main Authors: Bagal, Dilip Kumar, Rath, Arati, Barua, Abhishek, Patnaik, Dulu
• Format: Article
• Language: English
• Subjects: COVID-19; India; Lockdown; Python; SIR Model
• ISSN: 0960-0779; 1873-2887; 0960-0779
• DOI: 10.1016/j.chaos.2020.110154

•From the pandemic scenario of COVID-19 disease cases in all over the world, the outbreak prediction becomes very complex for the emerging scientifically research.•Several epidemiological mathematical models of spread are increasing day by day to forecast correctly.•Here, the classical SIR modelling approach is carried out to study the different parameters of this model in case of India county.•This type of approach analyzed by considering different governmental lock down measures in India.•The outcome results showed the extreme interventions should be taken to tackle this type of pandemic situation in near future. 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. [Display omitted]