Computational and stability analysis of Ebola virus epidemic model with piecewise hybrid fractional operator.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 08 10 2023
accepted: 27 01 2024
medline: 16 4 2024
pubmed: 16 4 2024
entrez: 16 4 2024
Statut: epublish

Résumé

In this manuscript, we developed a nonlinear fractional order Ebola virus with a novel piecewise hybrid technique to observe the dynamical transmission having eight compartments. The existence and uniqueness of a solution of piecewise derivative is treated for a system with Arzel'a-Ascoli and Schauder conditions. We investigate the effects of classical and modified fractional calculus operators, specifically the classical Caputo piecewise operator, on the behavior of the model. A model shows that a completely continuous operator is uniformly continuous, and bounded according to the equilibrium points. The reproductive number R0 is derived for the biological feasibility of the model with sensitivity analysis with different parameters impact on the model. Sensitivity analysis is an essential tool for comprehending how various model parameters affect the spread of illness. Through a methodical manipulation of important parameters and an assessment of their impact on Ro, we are able to learn more about the resiliency and susceptibility of the model. Local stability is established with next Matignon method and global stability is conducted with the Lyapunov function for a feasible solution of the proposed model. In the end, a numerical solution is derived with Newton's polynomial technique for a piecewise Caputo operator through simulations of the compartments at various fractional orders by using real data. Our findings highlight the importance of fractional operators in enhancing the accuracy of the model in capturing the intricate dynamics of the disease. This research contributes to a deeper understanding of Ebola virus dynamics and provides valuable insights for improving disease modeling and public health strategies.

Identifiants

pubmed: 38625847
doi: 10.1371/journal.pone.0298620
pii: PONE-D-23-32788
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0298620

Informations de copyright

Copyright: © 2024 Nisar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

No.

Auteurs

Kottakkaran Sooppy Nisar (KS)

Department of Mathematics, College of Arts and Sciences, Prince Sattam bin Abdulaziz University, Wadi Aldawaser, Saudi Arabia.

Muhammad Farman (M)

Faculty of Arts and Sciences, Department of Mathematics, Near East University, Nicosia, Northern Cyprus, Turkey.
Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon.

Khadija Jamil (K)

Institute of Mathematics, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.

Ali Akgul (A)

Faculty of Arts and Science, Department of Mathematics, Siirt University, Siirt, Turkey.

Saba Jamil (S)

Institute of Mathematics, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan.

Classifications MeSH