Yadigar Sekerci
The impact of vaccination strategy on the spatiotemporal pattern dynamics of a COVID-19 epidemic model
Sekerci, Yadigar; Khoshnaw, Sarbaz H.A.
Authors
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 |
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Copyright Statement
Copyright © 2024, The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature. This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1140/epjp/s13360-024-04944-3
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