Vol. 5, Issue 1 (2020)
Coronavirus (COVID-19) forecasting in India: Application of ARIMA and periodic regression models
Author(s): Bharath Prasad Cholanayakanahalli Thyagaraju, Shinduja Rajamani, Dharshan Hebbuluse Veerabhadrappa, Sharanagouda Patil, Parimal Roy, Srikantiah Chandrashekar, Kuralayanapalya Puttahonnappa Suresh, Raghavendra G Amachawadi
Abstract: Coronavirus disease, COVID-19 is the deadliest pandemic, which has affected most of the countries worldwide. Disease outbreak analysis has become a priority for the Government to take healthcare measures in reducing the impact of this pandemic. In this study, we attempt to analyse the disease outbreak data collected from 4th March 2020 to 26th May 2020 in India. Auto Regressive Integrated Moving Average (ARIMA) and Periodic Regression models were employed to predict the epidemiological trend of the incidence and probable number of new cases for the next ninety days for COVID-19 in India. The total number of probable daily new cases would be increased in the future as predicted by both ARIMA and Periodic regression models. Both ARIMA and Periodic regression models are best fitted to the observed data on daily incidence of COVID-19 in India. Incidence of COVID-19 expected to increase in next ninety days allowing to employ the stringent infection control measures such as public awareness and social distancing for effective mitigation and spread of disease in India.