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表征新冠疫情的阶段:基于振幅方程的非线性物理学视角

Characterizing stages of COVID-19 epidemics: a nonlinear physics perspective based on amplitude equations.

作者信息

Frank T D, Smucker J

机构信息

Department of Psychological Sciences, University of Connecticut, Storrs, USA.

Department of Physics, University of Connecticut, Storrs, USA.

出版信息

Eur Phys J Spec Top. 2022;231(18-20):3403-3418. doi: 10.1140/epjs/s11734-022-00530-9. Epub 2022 Mar 16.

Abstract

The relevant dynamics underlying COVID-19 waves is described from an amplitude space perspective. To this end, the amplitude dynamics of infected populations is considered in different stages of epidemic waves. Eigenvectors and their corresponding amplitudes are derived analytically for low-dimensional models and by means of computational methods for high-dimensional models. It is shown that the amplitudes of all eigenvectors as functions of time can be tracked through the diverse stages of COVID-19 waves featuring jumps at the stage boundaries. In particular, it is shown that under certain circumstances the initial, outbreak stage and the final, subsiding stage of an epidemic wave are primarily determined by the unstable eigenvector of the initial stage and its corresponding remnant vector of the final stage. The corresponding amplitude captures most of the dynamics of the emerging and subsiding epidemics such that the problem at hand effectively becomes one dimensional leading to a dramatic reduction of the complexity of the problem at hand. Explicitly demonstrated for the first-wave COVID-19 epidemics of the year 2020 in the state of New York and Pakistan are given.

摘要

从振幅空间的角度描述了新冠疫情浪潮背后的相关动态。为此,在疫情浪潮的不同阶段考虑了感染人群的振幅动态。对于低维模型,通过解析方法推导特征向量及其相应的振幅;对于高维模型,则借助计算方法进行推导。结果表明,所有特征向量的振幅作为时间的函数,可以在新冠疫情浪潮的不同阶段进行追踪,这些阶段在阶段边界处存在跳跃。特别地,研究表明在某些情况下,疫情浪潮的初始爆发阶段和最终消退阶段主要由初始阶段的不稳定特征向量及其在最终阶段的相应残余向量决定。相应的振幅捕捉了新兴和消退疫情的大部分动态,使得手头的问题有效地变为一维问题,从而大幅降低了问题的复杂性。文中明确展示了2020年纽约州和巴基斯坦第一波新冠疫情的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1545/8925301/58b85a90b65a/11734_2022_530_Fig1_HTML.jpg

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