Prediction and forecasting of COVID-19 outbreak using regression and ARIMA models

Abstract

In recent times, the coronavirus (COVID-19) epidemic is becoming a prevalent danger for humankind all over the world. This disastrous virus is propagating very fast through direct contact and respiratory droplets due to its contagious nature, and infecting millions of people globally. In the current scenario, spreading awareness regarding detection, forecasting, and prevention of this pandemic can save numerous lives in the whole community. In the present work, an outburst of this ailment has been investigated from 25/01/2020 to 05/06/2020 and predictions are made for the pattern of this outbreak in the weeks to come. ARIMA and Regression models are employed for forecasting, data being taken from John Hopkin University source for the timeline of 5-month in the year 2020. The error estimation of the proposed models has been carried out with the help of RMSLE and found to be 1.82 and 2.13 for Regression and S-ARIMA models respectively. It is anticipated that there may be a sharp rise in active cases around the world and governmental forms are required to take some stringent steps to stop the spread of this virus. The present study will be highly beneficial for the Governing bodies and health organizations in formulating concrete plans for the near future and long-term span.

Subject Classification:

• 62J05 (Linear Regression)
• 97R40 (Artificial Intelligence)
• 97R50 (Data bases, information systems)

Keywords:

• Novel corona virus
• COVID-19
• ARIMA
• Regression method and forecasting