Issue |
Math. Model. Nat. Phenom.
Volume 16, 2021
Fractional Dynamics in Natural Phenomena
|
|
---|---|---|
Article Number | 50 | |
Number of page(s) | 14 | |
DOI | https://doi.org/10.1051/mmnp/2021044 | |
Published online | 17 September 2021 |
Investigation of COVID-19 mathematical model under fractional order derivative
1
Department of Mathematics, University of Malakand, Dir(L),
Khyber Pakhtunkhwa, Pakistan.
2
Department of Mathematics, College of Science & Arts, King Abdulaziz University,
P.O. Box 344,
Rabigh
21911, Saudi Arabia.
3
Department of Mathematics, Cankaya University,
Ankara, Turkey.
4
Institute of Space Sciences, Bucharest, Romania, Department of Medical Research, China Medical University Hospital, China Medical University,
Taichung, Taiwan.
* Corresponding author: kamalshah408@gmail.com
Received:
13
June
2020
Accepted:
17
August
2021
The given article is devoted to presentation of some results regarding existence and uniqueness of solution to a fractional order model that addressing the effect of immigration on the transmission dynamics of a population model. Further, in view of this investigation the effect of immigration have been checked on transmission of recent pandemic known as Corona virus COVID-19. The concerned results have been established by using fixed point theory approach. After investigation qualitative analysis of the considered model, by applying Laplace transform along with decomposition method, we have calculated some series type results for the concerned model. The unknown quantities of each equation have been decomposed into small quantities to calculate each small quantity very easily for the series solution by adding first few terms of the said quantities. Approximate results of some testing data with different cases are given to illustrate the results.
Mathematics Subject Classification: 26A33 / 37A25 / 37M01
Key words: Existence and uniqueness / Laplace transform / approximate results
© The authors. Published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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