Differential Equations and Applications to COVID-19
Fuente:
arXiv
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866914864358752256 |
|---|---|
| author | Hounkonnou, Mitonsou Tierry Gouba, Laure |
| author_facet | Hounkonnou, Mitonsou Tierry Gouba, Laure |
| contents | This paper focuses on the application of the Verhulst logistic equation to model in retrospective the total COVID-19 cases in Senegal during the period from April 2022 to April 2023. Our predictions for April 2023 are compared with the real COVID-19 data for April 2023 to assess the accuracy of the model. The data analysis is conducted using Python programming language, which allows for efficient data processing and prediction generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_07123 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Differential Equations and Applications to COVID-19 Hounkonnou, Mitonsou Tierry Gouba, Laure Applications Physics and Society This paper focuses on the application of the Verhulst logistic equation to model in retrospective the total COVID-19 cases in Senegal during the period from April 2022 to April 2023. Our predictions for April 2023 are compared with the real COVID-19 data for April 2023 to assess the accuracy of the model. The data analysis is conducted using Python programming language, which allows for efficient data processing and prediction generation. |
| title | Differential Equations and Applications to COVID-19 |
| topic | Applications Physics and Society |
| url | https://arxiv.org/abs/2407.07123 |