ARIMA-based time-series analysis for forecasting of COVID-19 cases in Egypt

被引：0
|
作者：
Sabry I. [1 ]
Ismail Mourad A.-H. [2 ,3 ,4 ]
Idrisi A.H. [5 ]
ElWakil M. [6 ]
机构：
[1] Department of Mechanical Engineering, Benha University, Benha
[2] Mechanical and Aerospace Engineering Department, College of Engineering, United Arab Emirates University, P.O. Box. 15551, Al-Ain
[3] National Water and Energy Center, United Arab Emirates University, P.O. Box. 15551, Al Ain
[4] Mechanical Design Department, Faculty of Engineering, Helwan University, El Mataria, Cairo
[5] Department of Mechanical Engineering, UAE University, P.O. Box 15551, Al Ain
[6] Department of Production Engineering and Mechanical Design, Tanta University, Tanta
来源：
International Journal of Simulation and Process Modelling | 2022年 / 19卷 / 1-2期
关键词：
ARIMA; auto-regressive integrated moving average; coronavirus; COVID-19; Egypt; forecast; pandemic;
D O I：
10.1504/IJSPM.2022.130292
中图分类号：
学科分类号：
摘要：
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. © 2022 Inderscience Enterprises Ltd.
引用
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页码：86 / 96
页数：10
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