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A new study on two different vaccinated fractional-order COVID-19 models via numerical algorithms.
Zeb, Anwar; Kumar, Pushpendra; Erturk, Vedat Suat; Sitthiwirattham, Thanin.
Afiliação
  • Zeb A; Department of Mathematics, COMSATS University Islamabad, Abbottabad 22060, K.P.K, Pakistan.
  • Kumar P; Department of Mathematics and Statistics, School of Basic and Applied Sciences, Central University of Punjab, Bathinda, Punjab, 151001, India.
  • Erturk VS; Department of Mathematics, Ondokuz Mayis University, Atakum-55200, Samsun, Turkey.
  • Sitthiwirattham T; Mathematics Department, Faculty of Science and Technology, Suan Dusit University, Bangkok 10300, Thailand.
J King Saud Univ Sci ; : 101914, 2022 Feb 17.
Article em En | MEDLINE | ID: mdl-35194351
The 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 allow 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 the vaccine availability plays an important role in the control of COVID-19 infection.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J King Saud Univ Sci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Paquistão País de publicação: Arábia Saudita

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J King Saud Univ Sci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Paquistão País de publicação: Arábia Saudita