Ebola epidemic model with dynamic population and memory
| dc.contributor.author | Ndaïrou Faïçal | |
| dc.contributor.author | Khalighi Moein | |
| dc.contributor.author | Lahti Leo | |
| dc.contributor.organization | fi=data-analytiikka|en=Data-analytiikka| | |
| dc.contributor.organization-code | 1.2.246.10.2458963.20.68940835793 | |
| dc.converis.publication-id | 179183435 | |
| dc.converis.url | https://research.utu.fi/converis/portal/Publication/179183435 | |
| dc.date.accessioned | 2025-08-27T21:49:45Z | |
| dc.date.available | 2025-08-27T21:49:45Z | |
| dc.description.abstract | <p>The recent outbreaks of Ebola encourage researchers to develop mathematical models for simulating the dynamics of Ebola transmission. We continue the study of the models focusing on those with a variable population. Hence, this paper presents a compartmental model consisting of 8-dimensional nonlinear differential equations with a dynamic population and investigates its basic reproduction number. Moreover, a dimensionless model is introduced for numerical analysis, thus proving the disease-free equilibrium is locally asymptotically stable whenever the threshold condition, known as a basic reproduction number, is less than one. Finally, we use a fractional differential form of the model to sufficiently fit long time-series data of Guinea, Liberia, and Sierra Leone retrieved from the World Health Organization, and the numerical results demonstrate the performance of the model.</p> | |
| dc.identifier.eissn | 1873-2887 | |
| dc.identifier.jour-issn | 0960-0779 | |
| dc.identifier.olddbid | 201222 | |
| dc.identifier.oldhandle | 10024/184249 | |
| dc.identifier.uri | https://www.utupub.fi/handle/11111/47803 | |
| dc.identifier.url | https://doi.org/10.1016/j.chaos.2023.113361 | |
| dc.identifier.urn | URN:NBN:fi-fe2023041336265 | |
| dc.language.iso | en | |
| dc.okm.affiliatedauthor | Khalighi, Moein | |
| dc.okm.affiliatedauthor | Lahti, Leo | |
| dc.okm.discipline | 113 Computer and information sciences | en_GB |
| dc.okm.discipline | 113 Tietojenkäsittely ja informaatiotieteet | fi_FI |
| dc.okm.internationalcopublication | international co-publication | |
| dc.okm.internationality | International publication | |
| dc.okm.type | A1 ScientificArticle | |
| dc.publisher | Elsevier Ltd | |
| dc.publisher.country | United Kingdom | en_GB |
| dc.publisher.country | Britannia | fi_FI |
| dc.publisher.country-code | GB | |
| dc.relation.articlenumber | 113361 | |
| dc.relation.doi | 10.1016/j.chaos.2023.113361 | |
| dc.relation.ispartofjournal | Chaos, Solitons and Fractals | |
| dc.relation.volume | 170 | |
| dc.source.identifier | https://www.utupub.fi/handle/10024/184249 | |
| dc.title | Ebola epidemic model with dynamic population and memory | |
| dc.year.issued | 2023 |
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