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Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia
This article attempts to establish a mathematical epidemic model for the outbreak of the new COVID-19 coronavirus. A new consideration for evaluating and controlling the COVID-19 outbreak will be constructed based on the SEIQR Pandemic Model. In this paper, the real data of COVID-19 spread in Saudi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053363/ https://www.ncbi.nlm.nih.gov/pubmed/33898884 http://dx.doi.org/10.1016/j.idm.2021.04.005 |
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author | Youssef, Hamdy Alghamdi, Najat Ezzat, Magdy A. El-Bary, Alaa A. Shawky, Ahmed M. |
author_facet | Youssef, Hamdy Alghamdi, Najat Ezzat, Magdy A. El-Bary, Alaa A. Shawky, Ahmed M. |
author_sort | Youssef, Hamdy |
collection | PubMed |
description | This article attempts to establish a mathematical epidemic model for the outbreak of the new COVID-19 coronavirus. A new consideration for evaluating and controlling the COVID-19 outbreak will be constructed based on the SEIQR Pandemic Model. In this paper, the real data of COVID-19 spread in Saudi Arabia has been used for the mathematical model and dynamic analyses. Including the new reproductive number and detailed stability analysis, the dynamics of the proposed SEIQR model have been applied. The local sensitivity of the reproduction number has been analyzed. The domain of solution and equilibrium based on the SEIQR model have been proved using a Jacobian linearization process. The state of equilibrium and its significance have been proved, and a study of the integrity of the disease-free equilibrium has been carried out. The Lyapunov stability theorem demonstrated the global stability of the current model equilibrium. The SEIQR model has been numerically validated and projected by contrasting the results from the SEIQR model with the actual COVID-19 spread data in Saudi Arabia. The result of this paper shows that the SEIQR model is a model that is effective in analyzing epidemic spread, such as COVID-19. At the end of the study, we have implemented the protocol which helped the Saudi population to stop the spread of COVID-19 rapidly. |
format | Online Article Text |
id | pubmed-8053363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-80533632021-04-19 Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia Youssef, Hamdy Alghamdi, Najat Ezzat, Magdy A. El-Bary, Alaa A. Shawky, Ahmed M. Infect Dis Model Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu This article attempts to establish a mathematical epidemic model for the outbreak of the new COVID-19 coronavirus. A new consideration for evaluating and controlling the COVID-19 outbreak will be constructed based on the SEIQR Pandemic Model. In this paper, the real data of COVID-19 spread in Saudi Arabia has been used for the mathematical model and dynamic analyses. Including the new reproductive number and detailed stability analysis, the dynamics of the proposed SEIQR model have been applied. The local sensitivity of the reproduction number has been analyzed. The domain of solution and equilibrium based on the SEIQR model have been proved using a Jacobian linearization process. The state of equilibrium and its significance have been proved, and a study of the integrity of the disease-free equilibrium has been carried out. The Lyapunov stability theorem demonstrated the global stability of the current model equilibrium. The SEIQR model has been numerically validated and projected by contrasting the results from the SEIQR model with the actual COVID-19 spread data in Saudi Arabia. The result of this paper shows that the SEIQR model is a model that is effective in analyzing epidemic spread, such as COVID-19. At the end of the study, we have implemented the protocol which helped the Saudi population to stop the spread of COVID-19 rapidly. KeAi Publishing 2021-04-18 /pmc/articles/PMC8053363/ /pubmed/33898884 http://dx.doi.org/10.1016/j.idm.2021.04.005 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu Youssef, Hamdy Alghamdi, Najat Ezzat, Magdy A. El-Bary, Alaa A. Shawky, Ahmed M. Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title | Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title_full | Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title_fullStr | Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title_full_unstemmed | Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title_short | Study on the SEIQR model and applying the epidemiological rates of COVID-19 epidemic spread in Saudi Arabia |
title_sort | study on the seiqr model and applying the epidemiological rates of covid-19 epidemic spread in saudi arabia |
topic | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053363/ https://www.ncbi.nlm.nih.gov/pubmed/33898884 http://dx.doi.org/10.1016/j.idm.2021.04.005 |
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