Title: Real-time modelling and forecasting of confirmed and death cases for immediate action and their prevention against COVID-19 in India
Authors: Nishtha Phutela; Sunil Gupta; Goldie Gabrani
Addresses: Department of Computer Science and Engineering, BML Munjal University, Gurgaon – 122413, India ' Department of Cybernetics, School of Computer Science and Engineering, University of Petroleum and Energy Studies, Dehradun – 248007, India ' Department of Computer Science and Engineering, BML Munjal University, Gurgaon – 122413, India
Abstract: COVID-19 is an extremely contagious disease caused due to SARS-CoV-2 that appeared from Wuhan and has now spread all over the world. Its spread is worrisome not only because of its high transmissibility rate but also the fatality rate as reported by various studies. Hence, it becomes very important to estimate its spread in order to take appropriate preventive measures. In this paper, authors use different mathematical models to predict the count of COVID-19 confirmed cases in India till the end of lockdown 2.0 and the number of deaths using the data of patients in India. The comparison of the analytical results and the available results shows that the proposed methods are accurate within a specific range and will be useful for healthcare leaders and decision makers in near future. The forecasted results suggest the strong need of preventive measures to be taken rapidly in order to fight with COVID-19.
Keywords: COVID-19; mathematical modelling; linear regression; ridge regression; ARIIMA; forecasting.
International Journal of System of Systems Engineering, 2021 Vol.11 No.2, pp.159 - 169
Received: 08 Oct 2020
Accepted: 30 Oct 2020
Published online: 06 Jul 2021 *