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Global behavior of a multi-group SEIR epidemic model with spatial diffusion in a heterogeneous environment

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper, we propose a multi-group SEIR epidemic model with spatial diffusion, where the model parameters are spatially heterogeneous. The positivity and ultimate boundedness of the solution, as well as the existence of a global attractor of the associated solution semiflow, are established. The definition of the basic reproduction number is given by utilizing the next generation operator approach, whereby threshold-type results on the global dynamics in terms of this number are established. That is, when the basic reproduction number is less than one, the disease-free steady state is globally asymptotically stable, while if it is greater than one, uniform persistence of this model is proved. Finally, the feasibility of the main theoretical results is shown with the aid of numerical examples for a model with two groups.
Rocznik
Strony
271--283
Opis fizyczny
Bibliogr. 23 poz., wykr.
Twórcy
autor
  • College of Science, Tianjin University of Technology and Education, No. 1310 Dagu South Road, Tianjin 300222, PR China
autor
  • College of Mathematics, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu, Sichuan 610065, PR China
Bibliografia
  • [1] Allen, L.J.S., Bolker, B.M., Lou, Y. and Nevai, A.L. (2008). Asymptotic profiles of the steady states for an SIS epidemic reaction-diffusion model, Discrete and Continuous Dynamical Systems B 21(1): 1–20.
  • [2] Chaturantabut, S. (2020). Stabilized model reduction for nonlinear dynamical systems through a contractivity-preserving framework, International Journal of Applied Mathematics and Computer Science 30(4): 615–628, DOI: 10.34768/amcs-2020-0045.
  • [3] Chen, T., Xu, J. and Wu, B. (2016). Stability of multi-group coupled systems on networks with multi-diffusion based on the graph-theoretic approach, Mathematical Methods in the Applied Sciences 39(18): 5744–5756.
  • [4] Du, Y. (2006). Order Structure and Topological Methods in Nonlinear Partial Differential Equations. Vol. 1: Maximum Principles and Applications, World Scientific, Singapore.
  • [5] El-Douh, A.A.-R., Lu, S.F., Elkouny, A.A. and Amein, A.S. (2022). Hybrid cryptography with a one-time stamp to secure contact tracing for COVID-19 infection, International Journal of Applied Mathematics and Computer Science 32(1): 139–146, DOI: 10.34768/amcs-2022-0011.
  • [6] Grabowski, P. (2021). Comparison of direct and perturbation approaches to analysis of infinite-dimensional feedback control systems, International Journal of Applied Mathematics and Computer Science 31(2): 195–218, DOI: 10.34768/amcs-2021-0014.
  • [7] Guo, Z., Wang, F.-B. and Zou, X. (2012). Threshold dynamics of an infective disease model with a fixed latent period and non-local infections, Journal of Mathematical Biology 65(6–7): 1387–1410.
  • [8] Hale, J.K. (1969). Dynamical systems and stability, Journal of Mathematical Analysis and Applications 26(1): 39–59.
  • [9] Hale, J.K. (1988). Asymptotic Behavior of Dissipative Systems, American Mathematical Society, Providence.
  • [10] Li, H., Peng, R. and Wang, F.-B. (2017). Varying total population enhances disease persistence: Qualitative analysis on a diffusive SIS epidemic model, Journal of Differential Equations 262(2): 885–913.
  • [11] Liu, P. and Li, H.-X. (2020a). Global behavior of a multi-group SEIR epidemic model with age structure and spatial diffusion, Mathematical Biosciences and Engineering 17(6): 7248–7273.
  • [12] Liu, P. and Li, H.-X. (2020b). Global stability of autonomous and nonautonomous hepatitis B virus models in patchy environment, Journal of Applied Analysis and Computation 10(5): 1771–1799.
  • [13] Luo, Y., Tang, S., Teng, Z. and Zhang, L. (2019). Global dynamics in a reaction-diffusion multi-group SIR epidemic model with nonlinear incidence, Nonlinear Analysis: Real World Applications 50: 365–385.
  • [14] Martin, R.H. and Smith, H.L. (1990). Abstract functional differential equations and reaction-diffusion systems, Transactions of the American Mathematical Society 321(1): 1–44.
  • [15] Smith, H.L. (1995). Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, American Mathematical Society, Providence.
  • [16] Song, P., Lou, Y. and Xiao, Y. (2019). A spatial SEIRS reaction-diffusion model in heterogeneous environment, Journal of Differential Equations 267(9): 5084–5114.
  • [17] Wang, W. and Zhao, X.-Q. (2012). Basic reproduction numbers for reaction-diffusion epidemic models, SIAM Journal on Applied Dynamical Systems 11(4): 1652–1673.
  • [18] Wu, J. (1996). Theory and Applications of Partial Functional Differential Equations, Springer, New York.
  • [19] Xing, Y. and Li, H.-X. (2021). Almost periodic solutions for a SVIR epidemic model with relapse, Mathematical Biosciences and Engineering 18(6): 7191–7217.
  • [20] Yang, J. and Wang, X. (2019). Dynamics and asymptotical profiles of an age-structured viral infection model with spatial diffusion, Applied Mathematics and Computation 360(11): 236–254.
  • [21] Yang, Y., Zou, L., Zhang, T. and Xu, Y. (2020). Dynamical analysis of a diffusive SIRS model with general incidence rate, Discrete and Continuous Dynamical Systems B 25(7): 2433–2451.
  • [22] Zhao, L., Wang, Z.-C. and Ruan, S. (2018). Traveling wave solutions in a two-group SIR epidemic model with constant recruitment, Journal of Mathematical Biology 77(6–7, SI): 1871–1915.
  • [23] Zhao, X.-Q. (2003). Dynamical Systems in Population Biology, Springer, New York.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3d5ecb4e-260d-4693-b134-7b92797efac8
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