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一种基于变阶分数阶导数的新型冠状病毒数学模型。

A mathematical model for SARS-CoV-2 in variable-order fractional derivative.

作者信息

DarAssi Mahmoud H, Safi Mohammad A, Khan Muhammad Altaf, Beigi Alireza, Aly Ayman A, Alshahrani Mohammad Y

机构信息

Department of Basic Sciences, Princess Sumaya University for Technology, Amman, 11941 Jordan.

Department of Mathematics Faculty of science, The Hashemite University, P. O. Box 330127, Zarqa, 13133 Jordan.

出版信息

Eur Phys J Spec Top. 2022;231(10):1905-1914. doi: 10.1140/epjs/s11734-022-00458-0. Epub 2022 Feb 3.

Abstract

A new coronavirus mathematical with hospitalization is considered with the consideration of the real cases from March 06, 2021 till the end of April 30, 2021. The essential mathematical results for the model are presented. We show the model stability when in the absence of infection. We show that the system is stable locally asymptotically when at infection free state. We also show that the system is globally asymptotically stable in the disease absence when . Data have been used to fit accurately to the model and found the estimated basic reproduction number to be . Some graphical results for the effective parameters are drawn for the disease elimination. In addition, a variable-order model is introduced, and so as to handle the outbreak effectively and efficiently, a genetic algorithm is used to produce high-quality control. Numerical simulations clearly show that decision-makers may develop helpful and practical strategies to manage future waves by implementing optimum policies.

摘要

考虑到2021年3月6日至2021年4月30日的实际病例,构建了一个包含住院情况的新型冠状病毒数学模型。给出了该模型的基本数学结果。我们展示了在无感染情况下模型的稳定性。我们表明,在无感染状态下系统是局部渐近稳定的。我们还表明,在无疾病情况下,当 时系统是全局渐近稳定的。已使用数据对模型进行精确拟合,发现估计的基本再生数为 。绘制了一些有效参数的图形结果以实现疾病消除。此外,引入了一个变阶模型,为了有效且高效地应对疫情,使用遗传算法来产生高质量的控制。数值模拟清楚地表明,决策者可以通过实施最优政策制定出有助于管理未来疫情波的实用策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0547/8820367/6ed04add886e/11734_2022_458_Fig1_HTML.jpg

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