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A robust study on 2019-nCOV outbreaks through non-singular derivative.
Khan, Muhammad Altaf; Ullah, Saif; Kumar, Sunil.
  • Khan MA; Informetrics Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
  • Ullah S; Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam.
  • Kumar S; Department of Mathematics, University of Peshawar, Peshawar, Pakistan.
Eur Phys J Plus ; 136(2): 168, 2021.
Article in English | MEDLINE | ID: covidwho-1069447
ABSTRACT
The new coronavirus disease is still a major panic for people all over the world. The world is grappling with the second wave of this new pandemic. Different approaches are taken into consideration to tackle this deadly disease. These approaches were suggested in the form of modeling, analysis of the data, controlling the disease spread and clinical perspectives. In all these suggested approaches, the main aim was to eliminate or decrease the infection of the coronavirus from the community. Here, in this paper, we focus on developing a new mathematical model to understand its dynamics and possible control. We formulate the model first in the integer order and then use the Atangana-Baleanu derivative concept with a non-singular kernel for its generalization. We present some of the necessary mathematical aspects of the fractional model. We use a nonlinear fractional Lyapunov function in order to present the global asymptotical stability of the model at the disease-free equilibrium. In order to solve the model numerically in the fractional case, we use an efficient modified Adams-Bashforth scheme. The resulting iterative scheme is then used to demonstrate the detailed simulation results of the ABC mathematical model to examine the importance of the memory index and model parameters on the transmission and control of COVID-19 infection.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Eur Phys J Plus Year: 2021 Document Type: Article Affiliation country: Epjp

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Eur Phys J Plus Year: 2021 Document Type: Article Affiliation country: Epjp