Fractal–fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics
| dc.contributor.author | Addai, Emmanuel | |
| dc.contributor.author | Zhang, Lingling | |
| dc.contributor.author | Asamoah, Joshua Kiddy K. | |
| dc.contributor.author | Preko, Ama Kyerewaa | |
| dc.contributor.author | Arthur, Yarhands Dissou | |
| dc.contributor.orcid | 0000-0002-7066-246X | |
| dc.date.accessioned | 2024-11-20T12:32:06Z | |
| dc.date.available | 2024-11-20T12:32:06Z | |
| dc.date.issued | 2022-09 | |
| dc.description | This article is published by Elsevier 2022 and is also available at https://doi.org/10.1016/j.padiff.2022.100455 | |
| dc.description.abstract | This paper proposes a new fractal–fractional age-structure model for the omicron SARS-CoV-2 variant under the Caputo–Fabrizio fractional order derivative. Caputo–Fabrizio fractal–fractional order is particularly successful in modelling real-world phenomena due to its repeated memory effect and ability to capture the exponentially decreasing impact of disease transmission dynamics. We consider two age groups, the first of which has a population under 50 and the second of a population beyond 50. Our results show that at a population dynamics level, there is a high infection and recovery of omicron SARS-CoV-2 variant infection among the population under 50 (Group-1), while a high infection rate and low recovery of omicron SARS-CoV-2 variant infection among the population beyond 50 (Group-2) when the fractal–fractional order is varied. | |
| dc.description.sponsorship | KNUST | |
| dc.identifier.citation | Partial Differential Equations in Applied Mathematics 6 (2022) 100455 | |
| dc.identifier.uri | https://doi.org/10.1016/j.padiff.2022.100455 | |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/15963 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.title | Fractal–fractional age-structure study of omicron SARS-CoV-2 variant transmission dynamics | |
| dc.type | Article |