ARIMA-based time-series analysis for forecasting of COVID-19 cases in Egypt. (5th April 2023)

• Record Type: Journal Article
• Authors: Sabry, Ibrahim; Mourad, Abdel-Hamid Ismail; Idrisi, Amir Hussain; ElWakil, Mohamed
• Is Part Of: International journal of simulation and process modelling. Volume 19:Number 1/2(2023)
• Page Start: 86
• Page End: 96
• Publication Date: 2023-04-05
• Subjects: coronavirus -- COVID-19 -- pandemic -- auto-regressive integrated moving average -- ARIMA -- forecast -- Egypt; Management -- Computer simulation -- Periodicals; Mathematical models -- Periodicals; Operations research -- Periodicals; Simulation methods -- Periodicals; 003.05
• Languages: English
• ISSNs: 1740-2123

Abstract

A significant purpose of this study is to examine the distribution of COVID-19 in Egypt to develop an effective forecasting model. It can be used as a decision-making mechanism to administer health interventions and mitigate the transmission of contamination by COVID-19. By this definition, we developed a model and then used it to predict possible COVID-19 cases in Egypt. The analysis suggests a growth trajectory for the events in the days to come. Statistics based on time series analysis and kinetic model analysis indicate that the total case of COVID-19 pneumonia in mainland Egypt can hit 281, 478 after a week (March 1, 2020, through July 31, 2021), and the number of simple regenerations can hit 12. Analysis of ARIMA (2, 1, 2) and (2, 1, 3) sequences shows increasing growth in the number of events.