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A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources
The coronavirus disease 2019 (COVID-19) pandemic has caused the world to operate uncharacteristically for almost the last two years. Governments across the globe have taken different control measures to eradicate it. The Oxford COVID-19 Government Response Tracker (OxCGRT) provides open access data...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748003/ https://www.ncbi.nlm.nih.gov/pubmed/35028196 http://dx.doi.org/10.7759/cureus.20279 |
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author | Ahmad, Naim Qahmash, Ayman |
author_facet | Ahmad, Naim Qahmash, Ayman |
author_sort | Ahmad, Naim |
collection | PubMed |
description | The coronavirus disease 2019 (COVID-19) pandemic has caused the world to operate uncharacteristically for almost the last two years. Governments across the globe have taken different control measures to eradicate it. The Oxford COVID-19 Government Response Tracker (OxCGRT) provides open access data for different countries on 20 control measures, including numerous aggregated indices. This paper employs the modified Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiology model to study the COVID-19 pandemic in Saudi Arabia. The modification has been achieved by including control measures and the infectiousness of exposed compartment. A hybrid approach has been used to estimate and incorporate control measures. Initially, a composite control measure has been derived from OxCGRT data to make an attempt to fit the COVID-19 pattern in Saudi Arabia. The derived model has proven to be satisfactory through statistical tests. Nonetheless, the model patterns do not resemble the reported patterns more closely. Hence, a second heuristic approach has been utilized to devise effective control measures from the reported pattern of COVID-19 from the Saudi government agency. A satisfactory model was derived utilizing this approach with successful validation through statistical tests. Also, the model patterns more closely resemble the reported patterns of COVID-19 cases. This hybrid approach proves more robust and ensures the validity of model parameters better. The R naught (R(0)) value with the current control measures has varied from 0.515 to 1.892, with a mean value of 1.119, and is presently less than 1. The threshold herd immunity, in the absence of any control measure, is estimated to be 47.12% with an R(0 )value of 1.89 and would end up infecting 76.32% of the population. The scenario analysis with gradual partial and complete relaxations up to December 31, 2021, shows that the peaks are likely to occur in 2022; therefore, Saudi Arabia must continue to inoculate its population to eradicate COVID-19. |
format | Online Article Text |
id | pubmed-8748003 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-87480032022-01-12 A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources Ahmad, Naim Qahmash, Ayman Cureus Medical Simulation The coronavirus disease 2019 (COVID-19) pandemic has caused the world to operate uncharacteristically for almost the last two years. Governments across the globe have taken different control measures to eradicate it. The Oxford COVID-19 Government Response Tracker (OxCGRT) provides open access data for different countries on 20 control measures, including numerous aggregated indices. This paper employs the modified Susceptible-Exposed-Infectious-Recovered (SEIR) epidemiology model to study the COVID-19 pandemic in Saudi Arabia. The modification has been achieved by including control measures and the infectiousness of exposed compartment. A hybrid approach has been used to estimate and incorporate control measures. Initially, a composite control measure has been derived from OxCGRT data to make an attempt to fit the COVID-19 pattern in Saudi Arabia. The derived model has proven to be satisfactory through statistical tests. Nonetheless, the model patterns do not resemble the reported patterns more closely. Hence, a second heuristic approach has been utilized to devise effective control measures from the reported pattern of COVID-19 from the Saudi government agency. A satisfactory model was derived utilizing this approach with successful validation through statistical tests. Also, the model patterns more closely resemble the reported patterns of COVID-19 cases. This hybrid approach proves more robust and ensures the validity of model parameters better. The R naught (R(0)) value with the current control measures has varied from 0.515 to 1.892, with a mean value of 1.119, and is presently less than 1. The threshold herd immunity, in the absence of any control measure, is estimated to be 47.12% with an R(0 )value of 1.89 and would end up infecting 76.32% of the population. The scenario analysis with gradual partial and complete relaxations up to December 31, 2021, shows that the peaks are likely to occur in 2022; therefore, Saudi Arabia must continue to inoculate its population to eradicate COVID-19. Cureus 2021-12-08 /pmc/articles/PMC8748003/ /pubmed/35028196 http://dx.doi.org/10.7759/cureus.20279 Text en Copyright © 2021, Ahmad et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Medical Simulation Ahmad, Naim Qahmash, Ayman A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title | A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title_full | A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title_fullStr | A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title_full_unstemmed | A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title_short | A Hybrid Approach Toward COVID-19 Pandemic Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered Model and Open Data Sources |
title_sort | hybrid approach toward covid-19 pandemic modeling in saudi arabia using the modified susceptible-exposed-infectious-recovered model and open data sources |
topic | Medical Simulation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748003/ https://www.ncbi.nlm.nih.gov/pubmed/35028196 http://dx.doi.org/10.7759/cureus.20279 |
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