Mathematical analysis of a delayed SEIRDS epidemics models: deterministic and stochastic approach
The primary goal of this research is to investigate the impact of delay on the dynamics of the Susceptible-Exposed-Infected-Recovered-Death and Susceptible (SEIRDS) model, to which we add a stochastic term to account for uncertainty in COVID-19 parameter estimations. We run two models, one deterministic and one stochastic, and show that their solutions exist and are unique. We also numerically investigate the impact of immunity loss on the emerging time of a new wave, as well as the necessary condition for the extinction and persistence of the disease.
Authors
- Mohamed Ben Alaya (ORCID: https://orcid.org/0009-0004-8086-8703)
- Walid Ben Aribi
- Slimane Ben Miled (ORCID: https://orcid.org/0000-0002-2390-4892)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Laboratoire de Mathématiques Raphaël Salem (FR)
- École Supérieure Privée d'Ingénierie et de Technologies (TN)
- Institut Pasteur de Tunis (TN)
- Esprit (Slovakia) (SK)
- Université de Rouen Normandie (FR)
- Tunis El Manar University (TN)
Publication Details
- Journal
- Stochastics
- Published
- 2026-05-22
- DOI
- https://doi.org/10.1080/17442508.2026.2662251
- Citations
- 1
- Primary Topic
- COVID-19 epidemiological studies
- Type
- preprint
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministère de l'Europe et des Affaires Étrangères