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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doaj-7534020487d448948152591113e74f5d2021-08-28T04:44:05ZengElsevierResults in Physics2211-37972021-09-0128104629COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi ArabiaOthman A.M. Omar0Yousef Alnafisah1Reda A. Elbarkouky2Hamdy M. Ahmed3Physics and Engineering Mathematics Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; Corresponding author.Mathematics Department, College of Science, Qassim University, P.O.Box 6644, Buraydah 51452, Saudi ArabiaEgyptian Chinese University, Cairo 11725, EgyptHigher Institute of Engineering, El-Shorouk Academy, P.O. 3 El-Shorouk City, Cairo, EgyptIn 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.http://www.sciencedirect.com/science/article/pii/S221137972100721XCOVID-19Epidemiological modellingFractional stochastic dynamic modellingEuler-Murayama methodNumerical optimization algorithms |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Othman A.M. Omar Yousef Alnafisah Reda A. Elbarkouky Hamdy M. Ahmed |
spellingShingle |
Othman A.M. Omar Yousef Alnafisah Reda A. Elbarkouky Hamdy M. Ahmed COVID-19 deterministic and stochastic modelling with optimized daily vaccinations in Saudi Arabia Results in Physics COVID-19 Epidemiological modelling Fractional stochastic dynamic modelling Euler-Murayama method Numerical optimization algorithms |
author_facet |
Othman A.M. Omar Yousef Alnafisah Reda A. Elbarkouky Hamdy M. Ahmed |
author_sort |
Othman A.M. Omar |
title |
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_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_sort |
covid-19 deterministic and stochastic modelling with optimized daily vaccinations in saudi arabia |
publisher |
Elsevier |
series |
Results in Physics |
issn |
2211-3797 |
publishDate |
2021-09-01 |
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. |
topic |
COVID-19 Epidemiological modelling Fractional stochastic dynamic modelling Euler-Murayama method Numerical optimization algorithms |
url |
http://www.sciencedirect.com/science/article/pii/S221137972100721X |
work_keys_str_mv |
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