An extended SEIARD model for COVID-19 vaccination in Mexico: analysis and forecast

Autor: Ángel G. C. Pérez, David A. Oluyori
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Mathematics in Applied Sciences and Engineering, Vol 2, Iss 4, Pp 273-289 (2021)
Druh dokumentu: article
ISSN: 2563-1926
DOI: 10.5206/mase/14233
Popis: In this study, we propose and analyse an extended SEIARD model with vaccination. We compute the control reproduction number $\mathcal{R}_c$ of our model and study the stability of equilibria. We show that the set of disease-free equilibria is locally asymptotically stable when $\mathcal{R}_c1$, and we provide a sufficient condition for its global stability. Furthermore, we perform numerical simulations using the reported data of COVID-19 infections and vaccination in Mexico to study the impact of different vaccination, transmission and efficacy rates on the dynamics of the disease.
Databáze: Directory of Open Access Journals