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Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation
A reaction-diffusion viral infection model is formulated to characterize the infection process of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a heterogeneous environment. In the model, the viral production, infection and death rates of compartments are given by the general fu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9472993/ https://www.ncbi.nlm.nih.gov/pubmed/36124095 http://dx.doi.org/10.1016/j.apm.2022.09.006 |
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author | Wu, Peng Wang, Xiunan Feng, Zhaosheng |
author_facet | Wu, Peng Wang, Xiunan Feng, Zhaosheng |
author_sort | Wu, Peng |
collection | PubMed |
description | A reaction-diffusion viral infection model is formulated to characterize the infection process of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a heterogeneous environment. In the model, the viral production, infection and death rates of compartments are given by the general functions. We consider the well-posedness of the solution, derive the basic reproduction number [Formula: see text] , discuss the global stability of uninfected steady state and explore the uniform persistence for the model. We further propose a spatial diffusion SARS-CoV-2 infection model with humoral immunity and spatial independent coefficients, and analyze the global attractivity of uninfected, humoral inactivated and humoral activated equilibria which are determined by two dynamical thresholds. Numerical simulations are performed to illustrate our theoretical results which reveal that diffusion, spatial heterogeneity and incidence types have evident impact on the SARS-CoV-2 infection process which should not be neglected for experiments and clinical treatments. |
format | Online Article Text |
id | pubmed-9472993 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94729932022-09-15 Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation Wu, Peng Wang, Xiunan Feng, Zhaosheng Appl Math Model Article A reaction-diffusion viral infection model is formulated to characterize the infection process of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a heterogeneous environment. In the model, the viral production, infection and death rates of compartments are given by the general functions. We consider the well-posedness of the solution, derive the basic reproduction number [Formula: see text] , discuss the global stability of uninfected steady state and explore the uniform persistence for the model. We further propose a spatial diffusion SARS-CoV-2 infection model with humoral immunity and spatial independent coefficients, and analyze the global attractivity of uninfected, humoral inactivated and humoral activated equilibria which are determined by two dynamical thresholds. Numerical simulations are performed to illustrate our theoretical results which reveal that diffusion, spatial heterogeneity and incidence types have evident impact on the SARS-CoV-2 infection process which should not be neglected for experiments and clinical treatments. Elsevier Inc. 2023-01 2022-09-14 /pmc/articles/PMC9472993/ /pubmed/36124095 http://dx.doi.org/10.1016/j.apm.2022.09.006 Text en © 2022 Elsevier Inc. All rights reserved. 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 Wu, Peng Wang, Xiunan Feng, Zhaosheng Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title | Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title_full | Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title_fullStr | Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title_full_unstemmed | Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title_short | Spatial and temporal dynamics of SARS‐CoV‐2: Modeling, analysis and simulation |
title_sort | spatial and temporal dynamics of sars‐cov‐2: modeling, analysis and simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9472993/ https://www.ncbi.nlm.nih.gov/pubmed/36124095 http://dx.doi.org/10.1016/j.apm.2022.09.006 |
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