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Spatial and temporal dynamics of SARS-CoV-2: Modeling, analysis and simulation.
Wu, Peng; Wang, Xiunan; Feng, Zhaosheng.
  • Wu P; Institute of Mathematics & Interdisciplinary Sciences, Zhejiang University of Finance & Economics, Hangzhou 310018, China.
  • Wang X; Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA.
  • Feng Z; Schoolf of Mathematical and Statistical Sciences, University of Texas Rio Grande Valley, Edinburg, TX 78539, USA.
Appl Math Model ; 113: 220-240, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-2031119
ABSTRACT
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 R 0 , 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.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Appl Math Model Year: 2023 Document Type: Article Affiliation country: J.apm.2022.09.006

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Appl Math Model Year: 2023 Document Type: Article Affiliation country: J.apm.2022.09.006