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The impact of vaccination strategy on the spatiotemporal pattern dynamics of a COVID-19 epidemic model

Sekerci, Yadigar; Khoshnaw, Sarbaz H.A.

Authors

Yadigar Sekerci

Sarbaz H.A. Khoshnaw



Abstract

In the last 3 years, mathematical modelling and computational simulations have been used to discuss and estimate key transmission parameters of the spreading COVID-19 pandemics. There are several major factors that have played a crucial role in controlling this disease. These factors include contact tracing, rapid testing, and vaccination programs. In this study, we use a developed model to understand the impact of vaccination strategy on the spatiotemporal pattern dynamics of the COVID-19. We consider a system of diffusion equations of the spreading COVID-19 with vaccinated individuals. Accordingly, we apply the local sensitivity techniques to identify the model critical parameters. Computational results show spatial distribution of individuals for different initial states and parameters to show association between vaccination and COVID-19. It can be noticed that the spatio-temporal distribution of the recovered individuals appears to be reduced by the increased vaccination rate, as evident in three different normalization results of local sensitivity. Interestingly, the vaccination and contact tracing rate can effectively reduce the reproduction number of the virus in the population rather than the other parameters. Numerical results provide a wide range of possible solutions to control the spreading of this disease.

Citation

Sekerci, Y., & Khoshnaw, S. H. (2024). The impact of vaccination strategy on the spatiotemporal pattern dynamics of a COVID-19 epidemic model. European Physical Journal Plus, 139(2), Article 174. https://doi.org/10.1140/epjp/s13360-024-04944-3

Journal Article Type Article
Acceptance Date Jan 27, 2024
Online Publication Date Feb 19, 2024
Publication Date Feb 1, 2024
Deposit Date Jun 24, 2024
Publicly Available Date Feb 2, 2025
Journal European Physical Journal Plus
Electronic ISSN 2190-5444
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 139
Issue 2
Article Number 174
DOI https://doi.org/10.1140/epjp/s13360-024-04944-3
Keywords COVID-19; Diffusion; Pattern formation; Sensitivity analysis
Public URL https://hull-repository.worktribe.com/output/4718466

Files

This file is under embargo until Feb 2, 2025 due to copyright reasons.

Contact Y.Sekerci-Firat@hull.ac.uk to request a copy for personal use.




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