419645

Prediction of Covid-19 Cases in Egypt Using ARIMA Models

Article

Last updated: 29 Mar 2025

Subjects

-

Tags

إحصائية

Abstract

COVID-19 is one of the massive challenges that has faced the world since the end of World War II. Egypt was one of the countries that were seriously affected by COVID-19. As a result, the Egyptian authorities, and government had to take many precautionary and preventive procedures to protect Egyptian citizens.
This research aims to model confirmed cases of Covid-19 infections in Egypt from (March 4th, 2020) to (June 29th, 2021) as an estimation period of the model, while the data from (June 30th (2021) to (July 14th, 2021) was used as a prediction period. It has been proved that The ARIMA (4,1,5) model is the appropriate and efficient one for representing the time series data, with the least mean squares of MSE errors after comparing several ARIMA models at the first differences.
  It was, also, concluded that the number of infected people is going to increase. So, it is necessary for the Egyptian authorities to take urgent precautionary measures to limit this pandemic increase.

DOI

10.21608/sjcp.2023.419645

Keywords

COVID-19, time series, ARIMA Models, Forecasting, Box-jenkins method

Authors

First Name

عبد الوهاب السيد

Last Name

حجاج

MiddleName

-

Affiliation

كلية التجارة - جامعة الأزهر

Email

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City

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Orcid

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First Name

محمد عبد السلام

Last Name

عجمي

MiddleName

-

Affiliation

كلية التجارة - جامعة الأزهر

Email

-

City

-

Orcid

-

Volume

37

Article Issue

1

Related Issue

54763

Issue Date

2023-03-01

Receive Date

2025-03-28

Publish Date

2023-03-01

Page Start

155

Page End

176

Print ISSN

1110-8452

Link

https://sjcp.journals.ekb.eg/article_419645.html

Detail API

http://journals.ekb.eg?_action=service&article_code=419645

Order

419,645

Publication Type

Journal

Publication Title

مجلة البحوث التجارية المعاصرة

Publication Link

https://sjcp.journals.ekb.eg/

MainTitle

Prediction of Covid-19 Cases in Egypt Using ARIMA Models

Details

Type

Article

Created At

29 Mar 2025