The dynamics of COVID-19 in the UAE based on fractional derivative modeling using Riesz wavelets simulation.

IF 4.1 3区 数学 Q1 Mathematics Advances in Difference Equations Pub Date : 2021-01-01 Epub Date: 2021-02-19 DOI:10.1186/s13662-021-03262-7
Mutaz Mohammad, Alexander Trounev, Carlo Cattani
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引用次数: 23

Abstract

The well-known novel virus (COVID-19) is a new strain of coronavirus family, declared by the World Health Organization (WHO) as a dangerous epidemic. More than 3.5 million positive cases and 250 thousand deaths (up to May 5, 2020) caused by COVID-19 and has affected more than 280 countries over the world. Therefore studying the prediction of this virus spreading in further attracts a major public attention. In the Arab Emirates (UAE), up to the same date, there are 14,730 positive cases and 137 deaths according to national authorities. In this work, we study a dynamical model based on the fractional derivatives of nonlinear equations that describe the outbreak of COVID-19 according to the available infection data announced and approved by the national committee in the press. We simulate the available total cases reported based on Riesz wavelets generated by some refinable functions, namely the smoothed pseudosplines of types I and II with high vanishing moments. Based on these data, we also consider the formulation of the pandemic model using the Caputo fractional derivative. Then we numerically solve the nonlinear system that describes the dynamics of COVID-19 with given resources based on the collocation Riesz wavelet system constructed. We present graphical illustrations of the numerical solutions with parameters of the model handled under different situations. We anticipate that these results will contribute to the ongoing research to reduce the spreading of the virus and infection cases.

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基于Riesz小波模拟分数阶导数模型的阿联酋COVID-19动态
众所周知的新型病毒(COVID-19)是冠状病毒家族的一种新毒株,被世界卫生组织(WHO)宣布为危险的流行病。截至2020年5月5日,COVID-19造成350多万例阳性病例和25万人死亡,并影响了全球280多个国家。因此,进一步研究该病毒在中国的传播预测引起了公众的广泛关注。在阿拉伯酋长国(阿联酋),根据国家当局的数据,截至同一日期,有14,730例阳性病例和137例死亡。在这项工作中,我们研究了一个基于非线性方程分数阶导数的动力学模型,该模型根据国家委员会在报刊上公布和批准的现有感染数据来描述COVID-19的爆发。我们基于Riesz小波,即具有高消失矩的I型和II型光滑伪样条产生的一些可细化函数,模拟了可用的报告总数。基于这些数据,我们还考虑了使用卡普托分数导数的大流行模型的公式。然后,基于所构造的配置Riesz小波系统,对具有给定资源的描述COVID-19动态的非线性系统进行数值求解。我们给出了在不同情况下处理模型参数的数值解的图形说明。我们预计这些结果将有助于正在进行的减少病毒传播和感染病例的研究。
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期刊介绍: The theory of difference equations, the methods used, and their wide applications have advanced beyond their adolescent stage to occupy a central position in applicable analysis. In fact, in the last 15 years, the proliferation of the subject has been witnessed by hundreds of research articles, several monographs, many international conferences, and numerous special sessions. The theory of differential and difference equations forms two extreme representations of real world problems. For example, a simple population model when represented as a differential equation shows the good behavior of solutions whereas the corresponding discrete analogue shows the chaotic behavior. The actual behavior of the population is somewhere in between. The aim of Advances in Difference Equations is to report mainly the new developments in the field of difference equations, and their applications in all fields. We will also consider research articles emphasizing the qualitative behavior of solutions of ordinary, partial, delay, fractional, abstract, stochastic, fuzzy, and set-valued differential equations. Advances in Difference Equations will accept high-quality articles containing original research results and survey articles of exceptional merit.
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