New SARIMA Approach Model to Forecast COVID-19 Propagation: Case of Morocco

Abstract

The aim of this paper is to avoid any future health crises by analysing COVID-19 data of Morocco using Time Series to get more information about how the pandemic is spreading. For this reason, we used a statistical model called Seasonal Autoregressive Integrated Moving Average (SARIMA) to forecast the new confirmed cases, new deaths, cumulative cases and deaths. Besides predicting the spreading of COVID-19, this study will also help decision makers to better take the right decisions at the right time. Finally, we evaluated the performance of our model by measuring metrics such as Mean Squared Error (MSE). We have applied our SARIMA model for a forward forecasting in a period of 50 days, the MSE reported was 62196.46 for cumulative cases forecasting, and 621.14 for cumulative deaths forecasting.