A linear, decoupled and positivity-preserving numerical scheme for an epidemic model with advection and diffusion

Embargo End Date
2022-09-08

Type
Article

Authors
Kou, Jisheng
Chen, Huangxin
Wang, Xiuhua
Sun, Shuyu

KAUST Department
Computational Transport Phenomena Lab
Earth Science and Engineering Program
Physical Science and Engineering (PSE) Division

Online Publication Date
2021-06-09

Print Publication Date
2023-01-01

Date
2021-06-09

Abstract
In this paper, we propose an efficient numerical method for a comprehensive infection model that is formulated by a system of nonlinear coupling advection-diffusion-reaction equations. Using some subtle mixed explicit-implicit treatments, we construct a linearized and decoupled discrete scheme. Moreover, the proposed scheme is capable of preserving the positivity of variables, which is an essential requirement of the model under consideration. The proposed scheme uses the cell-centered finite difference method for the spatial discretization, and thus, it is easy to implement. The diffusion terms are treated implicitly to improve the robustness of the scheme. A semi-implicit upwind approach is proposed to discretize the advection terms, and a distinctive feature of the resulting scheme is to preserve the positivity of variables without any restriction on the spatial mesh size and time step size. We rigorously prove the unique existence of discrete solutions and positivity-preserving property of the proposed scheme without requirements for the mesh size and time step size. It is worthwhile to note that these properties are proved using the discrete variational principles rather than the conventional approaches of matrix analysis. Numerical results are also provided to assess the performance of the proposed scheme.

Citation
Kou, J., Chen, H., Wang, X., & Sun, S. (2021). A linear, decoupled and positivity-preserving numerical scheme for an epidemic model with advection and diffusion. Communications on Pure & Applied Analysis, 0(0), 0. doi:10.3934/cpaa.2021094

Publisher
American Institute of Mathematical Sciences (AIMS)

Journal
Communications on Pure & Applied Analysis

DOI
10.3934/cpaa.2021094

Additional Links
https://www.aimsciences.org/article/doi/10.3934/cpaa.2021094

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