Predicting COVID-19 Cases in India using Global Data

Shubhnesh Kumar Goyal

Abstract: This study presents a novel method of using SIR-based epidemiological modeling of COVID-19 spread to predict the number of cases in India during January 2020 ? April 2020 by identifying and leveraging the information from other countries that evolved through the same phase. Firstly, countries with similar characteristics were identified using R2 scores, and then their parabolic parameters were used to predict the number of cases in India 15-30 days in advance. Results show excellent accuracy for mentioned period, and thus this method put forward a promising way to mitigate upcoming damage by proper planning.

Keywords: Mathematical modeling, Epidemiology, SIR models, Statistical prediction, Optimisation

How to Cite?: Shubhnesh Kumar Goyal, "Predicting COVID-19 Cases in India using Global Data", Volume 10 Issue 7, July 2021, International Journal of Science and Research (IJSR), Pages: 1387-1394, https://www.ijsr.net/getabstract.php?paperid=SR21720164321, DOI: https://dx.doi.org/10.21275/SR21720164321