Comparative Performance Analysis of ARIMA, Prophet and Holt-Winters Forecasting Methods on European COVID-19 Data

Abstract

COVID-19 is the most common infectious disease of the last few years and has caused an outbreak all around the world. The mortality rate, which was earlier in the hundreds, increased to thousands and then to millions. Since January 2020, several scientists attempted to understand and predict the spread of COVID-19 so that governments may make sufficient arrangements in hospitals and reduce the mortality rate. This research article presents a comparative performance analysis of ARIMA, Prophet and Holt-Winters Exponential Smoothing forecasting methods to make predictions for the COVID-19 disease epidemiology in Europe. The dataset has been collected from the World Health Organization (WHO) and includes the COVID-19 case data of European countries, which is categorized by WHO between the years of 2020 and 2022. The results indicate that Holt-Winters Exponential Smoothing method (RMSE: 0.2080, MAE: 0.1747) outperforms ARIMA and Prophet forecasting methods.