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关于利用熵问题评估和控制某些流行病模型中的瞬态过程

On the Use of Entropy Issues to Evaluate and Control the Transients in Some Epidemic Models.

作者信息

De la Sen Manuel, Nistal Raul, Ibeas Asier, Garrido Aitor J

机构信息

Institute of Research and Development of Processes IIDP, University of the Basque Country, Campus of Leioa, PO Box 48940 Leioa (Bizkaia), Spain.

Department of Telecommunications and Systems Engineering, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.

出版信息

Entropy (Basel). 2020 May 9;22(5):534. doi: 10.3390/e22050534.

Abstract

This paper studies the representation of a general epidemic model by means of a first-order differential equation with a time-varying log-normal type coefficient. Then the generalization of the first-order differential system to epidemic models with more subpopulations is focused on by introducing the inter-subpopulations dynamics couplings and the control interventions information through the mentioned time-varying coefficient which drives the basic differential equation model. It is considered a relevant tool the control intervention of the infection along its transient to fight more efficiently against a potential initial exploding transmission. The study is based on the fact that the disease-free and endemic equilibrium points and their stability properties depend on the concrete parameterization while they admit a certain design monitoring by the choice of the control and treatment gains and the use of feedback information in the corresponding control interventions. Therefore, special attention is paid to the evolution transients of the infection curve, rather than to the equilibrium points, in terms of the time instants of its first relative maximum towards its previous inflection time instant. Such relevant time instants are evaluated via the calculation of an "ad hoc" Shannon's entropy. Analytical and numerical examples are included in the study in order to evaluate the study and its conclusions.

摘要

本文研究了通过具有时变对数正态型系数的一阶微分方程来表示一般流行病模型。然后,通过引入子群体间动态耦合以及通过驱动基本微分方程模型的上述时变系数来引入控制干预信息,重点关注一阶微分系统对具有更多子群体的流行病模型的推广。在感染的瞬态过程中进行控制干预被认为是一种相关工具,以便更有效地对抗潜在的初始爆发性传播。该研究基于这样一个事实,即无病平衡点和地方病平衡点及其稳定性性质取决于具体的参数化,同时通过选择控制和治疗增益以及在相应控制干预中使用反馈信息,它们允许进行一定的设计监测。因此,就感染曲线从其第一个相对最大值到其先前拐点时刻的时间瞬间而言,特别关注感染曲线的演化瞬态,而不是平衡点。通过计算一个“特设”的香农熵来评估这些相关的时间瞬间。研究中包含了分析和数值示例,以便评估该研究及其结论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7bd5/7517029/a0cfcdb5757c/entropy-22-00534-g001.jpg

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