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COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia

In this paper, we investigate the stochastic nature of the COVID-19 temporal dynamics by generating a fractional-order dynamic model and a fractional-order-stochastic model. Initially, we considered the first and second vaccination doses as multiple vaccinations were initiated worldwide. The concern...

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Autores principales: Omar, Othman A.M., Alnafisah, Yousef, Elbarkouky, Reda A., Ahmed, Hamdy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327613/
https://www.ncbi.nlm.nih.gov/pubmed/34367890
http://dx.doi.org/10.1016/j.rinp.2021.104629
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author Omar, Othman A.M.
Alnafisah, Yousef
Elbarkouky, Reda A.
Ahmed, Hamdy M.
author_facet Omar, Othman A.M.
Alnafisah, Yousef
Elbarkouky, Reda A.
Ahmed, Hamdy M.
author_sort Omar, Othman A.M.
collection PubMed
description In this paper, we investigate the stochastic nature of the COVID-19 temporal dynamics by generating a fractional-order dynamic model and a fractional-order-stochastic model. Initially, we considered the first and second vaccination doses as multiple vaccinations were initiated worldwide. The concerned models are then tested for the Saudi Arabia second virus wave, which is assumed to start on 1st March 2021. Four daily vaccination scenarios for the first and second dose are assumed for 100 days from the wave beginning. One of these scenarios is based on function optimization using the invasive weed optimization algorithm (IWO). After that, we numerically solve the established models using the fractional Euler method and the Euler-Murayama method. Finally, the obtained virus dynamics using the assumed scenarios and the real one started by the government are compared. The optimized scenario using the IWO effectively minimizes the predicted cumulative wave infections with a 4.4 % lower number of used vaccination doses.
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spelling pubmed-83276132021-08-02 COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia Omar, Othman A.M. Alnafisah, Yousef Elbarkouky, Reda A. Ahmed, Hamdy M. Results Phys Article In this paper, we investigate the stochastic nature of the COVID-19 temporal dynamics by generating a fractional-order dynamic model and a fractional-order-stochastic model. Initially, we considered the first and second vaccination doses as multiple vaccinations were initiated worldwide. The concerned models are then tested for the Saudi Arabia second virus wave, which is assumed to start on 1st March 2021. Four daily vaccination scenarios for the first and second dose are assumed for 100 days from the wave beginning. One of these scenarios is based on function optimization using the invasive weed optimization algorithm (IWO). After that, we numerically solve the established models using the fractional Euler method and the Euler-Murayama method. Finally, the obtained virus dynamics using the assumed scenarios and the real one started by the government are compared. The optimized scenario using the IWO effectively minimizes the predicted cumulative wave infections with a 4.4 % lower number of used vaccination doses. The Author(s). Published by Elsevier B.V. 2021-09 2021-08-02 /pmc/articles/PMC8327613/ /pubmed/34367890 http://dx.doi.org/10.1016/j.rinp.2021.104629 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Omar, Othman A.M.
Alnafisah, Yousef
Elbarkouky, Reda A.
Ahmed, Hamdy M.
COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title_full COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title_fullStr COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title_full_unstemmed COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title_short COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia
title_sort covid-19 deterministic and stochastic modelling with optimized daily vaccinations in saudi arabia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327613/
https://www.ncbi.nlm.nih.gov/pubmed/34367890
http://dx.doi.org/10.1016/j.rinp.2021.104629
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