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用流体动力学对传染病流行进行建模。

Modeling epidemic flow with fluid dynamics.

机构信息

School of Mathematics, Hefei University of Technology, Hefei, Anhui 230009, China.

Department of Mathematics, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA.

出版信息

Math Biosci Eng. 2022 Jun 9;19(8):8334-8360. doi: 10.3934/mbe.2022388.

Abstract

In this paper, a new mathematical model based on partial differential equations is proposed to study the spatial spread of infectious diseases. The model incorporates fluid dynamics theory and represents the epidemic spread as a fluid motion generated through the interaction between the susceptible and infected hosts. At the macroscopic level, the spread of the infection is modeled as an inviscid flow described by the Euler equation. Nontrivial numerical methods from computational fluid dynamics (CFD) are applied to investigate the model. In particular, a fifth-order weighted essentially non-oscillatory (WENO) scheme is employed for the spatial discretization. As an application, this mathematical and computational framework is used in a simulation study for the COVID-19 outbreak in Wuhan, China. The simulation results match the reported data for the cumulative cases with high accuracy and generate new insight into the complex spatial dynamics of COVID-19.

摘要

本文提出了一个基于偏微分方程的新数学模型,用于研究传染病的空间传播。该模型结合了流体动力学理论,将传染病的传播表示为通过易感宿主和感染宿主之间的相互作用产生的流体运动。在宏观层面上,感染的传播被建模为由欧拉方程描述的无粘流。计算流体动力学(CFD)的非平凡数值方法被应用于研究该模型。特别是,采用五阶加权本质无振荡(WENO)格式进行空间离散化。作为应用,该数学和计算框架被用于对中国武汉 COVID-19 爆发的模拟研究。模拟结果与累积病例的报告数据高度吻合,为 COVID-19 的复杂空间动态提供了新的见解。

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