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针对巴西案例研究的、具有多个延迟因素的数学模型的最优控制方法,该模型用于研究在应对新冠疫情传播时延迟采取预防措施的负面影响以及成本效益。

Optimal control approach of a mathematical modeling with multiple delays of the negative impact of delays in applying preventive precautions against the spread of the COVID-19 pandemic with a case study of Brazil and cost-effectiveness.

作者信息

Kouidere Abdelfatah, Kada Driss, Balatif Omar, Rachik Mostafa, Naim Mouhcine

机构信息

LAMS, Department of Mathematics and Computer Science, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, Morocco.

Laboratory of Information Technology and Modeling, Department of Mathematics and Computer Science, Faculty of Sciences Ben M'Sik, Hassan II University, Casablanca, Morocco.

出版信息

Chaos Solitons Fractals. 2021 Jan;142:110438. doi: 10.1016/j.chaos.2020.110438. Epub 2020 Nov 4.

Abstract

As of June 02, 2020. The number of people infected with COVID-19 virus in Brazil was about 529,405, the number of death is 30046, the number of recovered is 211080, and the number is subject to increase. This is due to the delay by a number of countries in general, and Brazil in particular, in taking preventive and proactive measures to limit the spread of the COVID-19 pandemic. So, we propose to study an optimal control approach with delay in state and control variables in our mathematical model proposed by kouidere et al. which describes the dynamics of the transmission of the COVID-19. That the time with delay represent the delay to applying preventive precautions measures. Pontryagin's maximum principle is used to characterize the optimal controls and the optimality system is solved by an iterative method. Finally, some numerical simulations are performed to verify the theoretical analysis using MATLAB.

摘要

截至2020年6月2日,巴西感染新冠病毒的人数约为529,405人,死亡人数为30046人,康复人数为211080人,且该数字仍有可能增加。总体而言,这是由于许多国家,尤其是巴西,在采取预防和积极措施以限制新冠疫情传播方面有所延迟。因此,我们建议在Kouidere等人提出的数学模型中研究一种状态和控制变量存在延迟的最优控制方法,该模型描述了新冠病毒传播的动态过程。其中延迟时间代表采取预防措施的延迟。利用庞特里亚金极大值原理来刻画最优控制,并通过迭代方法求解最优性系统。最后,使用MATLAB进行了一些数值模拟以验证理论分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a68/7830200/beeb46ed3b11/gr1_lrg.jpg

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