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

Autor: David A. Oluyori, Ángel G. C. Pérez
Rok vydání: 2021
Předmět:
Zdroj: Mathematics in Applied Sciences and Engineering. 2:273-289
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 ℛcof our model and study the stability of equilibria. We show that the set of disease-free equilibria is locally asymptotically stable when ℛc< 1 and unstable when ℛc> 1, 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: OpenAIRE