基于分数阶反应扩散方程的传染病模型研究
Research on Epidemic Model Based on Fractional Reaction Diffusion Equation
DOI: 10.12677/PM.2021.117149, PDF,   
作者: 霍俊蓉:沈阳师范大学,数学与系统科学学院,辽宁 沈阳;张荣培:广东工业大学,应用数学学院,广东 广州
关键词: 分数阶反应扩散方程有限差分法传染病模型图灵斑图Fractional Reaction Diffusion Equation Finite Difference Method Integral Factor Method Turing Pattern
摘要: 反应扩散方程在物理学、化学、医学及生物学等多个领域的不同模型中有广泛应用。分数阶反应扩散型方程是整数阶的推广,被广泛应用于研究传染病的传播过程、图像分析以及随机过程。本文采用分数阶反应扩散方程来模拟传染病模型的动态行为。首先,通过求解齐次Neumann边界条件下分数阶反应扩散方程的特征值,对其进行线性稳定性分析,得到图灵不稳定的条件。然后结合Kronecker积用有限差分法以及积分因子法在空间上以及时间上对反应扩散方程组进行离散并求解。最后,给出数值实验验证稳定性分析结果。本文的数值结果有助于预测传染病的流行趋势。
Abstract: Reaction diffusion equation is widely used in different models of physics, chemistry, medicine and biology. Fractional reaction diffusion equation is a generalization of integer order, which is widely used in the study of infectious disease propagation process, image analysis and stochastic process. In this paper, the fractional reaction-diffusion equation is used to simulate the dynamic behavior of the epidemic model. Firstly, by solving the eigenvalues of the fractional reaction-diffusion equation with homogeneous Neumann boundary conditions, the linear stability of the equation is analyzed, and the Turing instability condition is obtained. Then, combined with Kronecker product, the reac-tion-diffusion equations are discretized and solved by finite difference method and integration factor method in space and time. Finally, numerical experiments are given to verify the stability analysis results. The numerical results are helpful to predict the epidemic trend of infectious diseases.
文章引用:霍俊蓉, 张荣培. 基于分数阶反应扩散方程的传染病模型研究[J]. 理论数学, 2021, 11(7): 1326-1334. https://doi.org/10.12677/PM.2021.117149

参考文献

[1] Lin, Y. and Jin, M. (2019) Ergodicity of a Regime-Switching Epidemic Model with Degenerate Diffusion. Physica A: Statistical Mechanics and Its Applications, 526, Article ID: 121134. [Google Scholar] [CrossRef
[2] Cao, B., Shan, M., Zhang, Q., et al. (2017) A Stochastic SIS Epidemic Model with Vaccination. Physica A: Statistical Mechanics and Its Applications, 486, 127-143. [Google Scholar] [CrossRef
[3] Sun, G., Jin, Z., Liu, Q.X., et al. (2007) Pattern Formation in a Spatial S-I Model with Non-Linear Incidence Rates. Journal of Statistical Mechanics: Theory and Experiment, No. 11, 11011. [Google Scholar] [CrossRef
[4] Tong, Y. and Lei, C. (2018) An SIS Epidemic Reac-tion-Diffusion Model with Spontaneous Infection in a Spatially Heterogeneous Environment. Nonlinear Analysis: Real World Applications, 41, 443-460. [Google Scholar] [CrossRef
[5] Sun, G.Q. (2012) Pattern Formation of an Epidemic Model with Diffusion. Nonlinear Dynamics, 69, 1097-1104. [Google Scholar] [CrossRef] [PubMed]
[6] Jia, Y., Cai, Y., Shi, H., et al. (2018) Turing patterns in a Reac-tion-Diffusion Epidemic Model. International Journal of Biomathematics, 11, Article ID: 1850025. [Google Scholar] [CrossRef
[7] 张荣培, 王震, 王语, 韩子健. 反应扩散模型在图灵斑图中的应用及数值模[J]. 物理学报, 2018, 67(5): 51-59.
[8] Liu, C., Li, L., Wang, Z. and Wang, R.W. (2019) Pattern Transitions in a Vegetation System with Cross-Diffusion. Applied Mathematics and Computation, 342, 255-262. [Google Scholar] [CrossRef
[9] Wang, W., Liu, H., Cai, Y. and Li, Z. (2011) Turing Pattern Se-lection in a Reaction-Diffusion Epidemic Model. Chinese Physics B, 20, 290-301. [Google Scholar] [CrossRef
[10] Zhang, R.P., Yu, X.J., Zhu, J. and Loula, A.F.D. (2014) Di-rect Discontinuous Galerkin Method for Nonlinear Reaction-Diffusion Systems in Pattern Formation. Direct Discon-tinuous Galerkin Method for Nonlinear Reaction-Diffusion Systems in Pattern Formation, 38, 1612-1621. [Google Scholar] [CrossRef
[11] Zhang, R.P., Wang, Z., Liu, J. and Liu, L.M. (2018) A Compact Finite Difference Method for Reaction-Diffusion Problems Using Compact Integration Factor Methods in High Spatial Dimensions. Advances in Difference Equations, No. 1, 274. [Google Scholar] [CrossRef
[12] 张荣培, 李明军, 蔚喜军. Chebyshev谱配置方法求解反应扩散方程组[J]. 数值计算与计算机应用, 2017, 38(4): 271-281.
[13] Zhu, Y.T., Zhang, S., Newman, A. and Alber, M. (2009) Application of Discontinuous Galerkin Meth-ods for Reaction-Diffusion Systems in Developmental Biology. Journal of Scientific Computing, 40, 391-418. [Google Scholar] [CrossRef
[14] Huang, J., Tang, Y., Vázquez, L., et al. (2013) Two Finite Dif-ference Schemes for Time Fractional Diffusion-Wave Equation. Numerical Algorithms, 64, 707-720. [Google Scholar] [CrossRef