A statistical study of COVID-19 pandemic in Egypt

The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19, 2021). In this paper, we propose a statistical...

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Autor principal: Radwan Taha
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Publicado: De Gruyter 2021
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Acceso en línea:https://doaj.org/article/a4af4b7551fa4801b6e437eed4bcd3df
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spelling oai:doaj.org-article:a4af4b7551fa4801b6e437eed4bcd3df2021-12-05T14:10:45ZA statistical study of COVID-19 pandemic in Egypt2391-466110.1515/dema-2021-0028https://doaj.org/article/a4af4b7551fa4801b6e437eed4bcd3df2021-07-01T00:00:00Zhttps://doi.org/10.1515/dema-2021-0028https://doaj.org/toc/2391-4661The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19, 2021). In this paper, we propose a statistical study of COVID-19 pandemic in Egypt. This study will help us to understand and study the evolution of this pandemic. Moreover, documenting of accurate data and taken policies in Egypt can help other countries to deal with this epidemic, and it will also be useful in the event that other similar viruses emerge in the future. We will apply a widely used model in order to predict the number of COVID-19 cases in the coming period, which is the autoregressive integrated moving average (ARIMA) model. This model depicts the present behaviour of variables through linear relationship with their past values. The expected results will enable us to provide appropriate advice to decision-makers in Egypt on how to deal with this epidemic.Radwan TahaDe Gruyterarticlestatistical modelpandemiccovid-19coronavirustime series analysis37m1062m1062p1065c20MathematicsQA1-939ENDemonstratio Mathematica, Vol 54, Iss 1, Pp 233-244 (2021)
institution DOAJ
collection DOAJ
language EN
topic statistical model
pandemic
covid-19
coronavirus
time series analysis
37m10
62m10
62p10
65c20
Mathematics
QA1-939
spellingShingle statistical model
pandemic
covid-19
coronavirus
time series analysis
37m10
62m10
62p10
65c20
Mathematics
QA1-939
Radwan Taha
A statistical study of COVID-19 pandemic in Egypt
description The spread of the COVID-19 started in Wuhan on December 31, 2019, and a powerful outbreak of the disease occurred there. According to the latest data, more than 165 million cases of COVID-19 infection have been detected in the world (last update May 19, 2021). In this paper, we propose a statistical study of COVID-19 pandemic in Egypt. This study will help us to understand and study the evolution of this pandemic. Moreover, documenting of accurate data and taken policies in Egypt can help other countries to deal with this epidemic, and it will also be useful in the event that other similar viruses emerge in the future. We will apply a widely used model in order to predict the number of COVID-19 cases in the coming period, which is the autoregressive integrated moving average (ARIMA) model. This model depicts the present behaviour of variables through linear relationship with their past values. The expected results will enable us to provide appropriate advice to decision-makers in Egypt on how to deal with this epidemic.
format article
author Radwan Taha
author_facet Radwan Taha
author_sort Radwan Taha
title A statistical study of COVID-19 pandemic in Egypt
title_short A statistical study of COVID-19 pandemic in Egypt
title_full A statistical study of COVID-19 pandemic in Egypt
title_fullStr A statistical study of COVID-19 pandemic in Egypt
title_full_unstemmed A statistical study of COVID-19 pandemic in Egypt
title_sort statistical study of covid-19 pandemic in egypt
publisher De Gruyter
publishDate 2021
url https://doaj.org/article/a4af4b7551fa4801b6e437eed4bcd3df
work_keys_str_mv AT radwantaha astatisticalstudyofcovid19pandemicinegypt
AT radwantaha statisticalstudyofcovid19pandemicinegypt
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