AN EXTENDED SEIARD MODEL FOR COVID-19 VACCINATION IN MEXICO: ANALYSIS AND FORECAST

被引：4
作者：
Perez, Angel G. C. [1 ]
Oluyori, David A. [2 ]
机构：
[1] Univ Autonoma Yucatan, Fac Matemat, Merida, Yucatan, Mexico
[2] Ahmadu Bello Univ, Sch Phys Sci, Dept Math, Zaria, Kaduna, Nigeria
来源：
MATHEMATICS IN APPLIED SCIENCES AND ENGINEERING | 2021年 / 2卷 / 04期
关键词：
Coronavirus; vaccine efficacy; asymptomatic infection; stability;
D O I：
10.5206/mase/14233
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this study, we propose and analyse an extended SEIARD model with vaccination. We compute the control reproduction number 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 R-c < 1 and unstable when R-c > 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.
引用
收藏
页码：273 / 289
页数：17
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