Fractional order epidemiological model of SARS-CoV-2 dynamism involving Alzheimer’s disease
| dc.contributor.author | Addai, Emmanuel | |
| dc.contributor.author | Zhang, Lingling | |
| dc.contributor.author | Preko, Ama Kyerewaa | |
| dc.contributor.author | Asamoah, Joshua Kiddy K. | |
| dc.contributor.orcid | 0000-0002-7066-246X | |
| dc.date.accessioned | 2024-11-20T10:38:15Z | |
| dc.date.available | 2024-11-20T10:38:15Z | |
| dc.date.issued | 2022-09 | |
| dc.description | This article is published by Elsevier 2022 and is also available at www.elsevier.com/locate/health | |
| dc.description.abstract | In this paper, we study a Caputo–Fabrizio fractional order epidemiological model for the transmission dynamism of the severe acute respiratory syndrome coronavirus 2 pandemic and its relationship with Alzheimer’s disease. Alzheimer’s disease is incorporated into the model by evaluating its relevance to the quarantine strategy. We use functional techniques to demonstrate the proposed model stability under the Ulam–Hyres condition. The Adams–Bashforth method is used to determine the numerical solution for our proposed model. According to our numerical results, we notice that an increase in the quarantine parameter has minimal effect on the Alzheimer’s disease compartment. | |
| dc.description.sponsorship | KNUST | |
| dc.identifier.citation | Healthcare Analytics 2 (2022) 100114 | |
| dc.identifier.uri | www.elsevier.com/locate/health | |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/15947 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.title | Fractional order epidemiological model of SARS-CoV-2 dynamism involving Alzheimer’s disease | |
| dc.type | Article |