文章基本信息

标题：A new study on two different vaccinated fractional-order COVID-19 models via numerical algorithms
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作者：Anwar Zeb ; Pushpendra Kumar ; Vedat Suat Erturk 等
期刊名称：Journal of King Saud University - Science
印刷版ISSN：1018-3647
出版年度：2022
卷号：34
期号：4
页码：1-13
DOI：10.1016/j.jksus.2022.101914
语种：English
出版社：Elsevier
摘要：AbstractThe main purpose of this paper is to provide new vaccinated models of COVID-19 in the sense of Caputo-Fabrizio and new generalized Caputo-type fractional derivatives. The formulation of the given models is presented including an exhaustive study of the model dynamics such as positivity, boundedness of the solutions, and local stability analysis. Furthermore, the unique solution existence for the proposed fractional-order models is discussed via fixed point theory. Numerical solutions are also derived by using two-steps Adams-Bashforth algorithm for Caputo-Fabrizio operator, and modified Predictor-Corrector method for generalised Caputo fractional derivative. Our analysis allows to show that the given fractional-order models exemplify the dynamics of COVID-19 much better than the classical ones. Also, the analysis on the convergence and stability for the proposed methods are performed. By this study, we see that how vaccine availability plays an important role in the control of COVID-19 infection.
关键词：KeywordsFractional mathematical modelNumerical methodsCaputo-Fabrizio and new generalized Caputo fractional-derivatives