Stationary distribution and probability density function of a stochastic COVID-19 infections model with general incidence

被引:1
作者
Niu, Lijuan [1 ]
Chen, Qiaoling [1 ,2 ]
Teng, Zhidong [3 ]
Rifhat, Ramziya [3 ]
Zhang, Ge [4 ]
机构
[1] Xian Polytech Univ, Sch Sci, Xian 710048, Peoples R China
[2] Shaanxi Normal Univ, Sch Math & Stat, Xian 710062, Peoples R China
[3] Xinjiang Med Univ, Coll Med Engn & Technol, Urumqi 830017, Peoples R China
[4] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830017, Peoples R China
来源
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2024年 / 361卷 / 12期
基金
中国国家自然科学基金;
关键词
SVEIHR model; General incidence; Stationary distribution; Density function; SIMULATION; DYNAMICS;
D O I
10.1016/j.jfranklin.2024.106963
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the sudden outbreak of COVID-19 all over the world, vaccination was one of the most effective treatments. In this paper, a stochastic COVID-19 model with vaccination is developed. We first prove that the stochastic model has a unique global solution by constructing the corresponding Lyapunov function. Then, sufficient condition for ergodic stationary distribution v(& sdot;) is provided under the condition R-o(s) > 1 . Moreover, by applying the six-dimensional Fokker- Planck equation, we obtain the explicit expression of the probability density function near quasi-local equilibrium Q(& lowast;), which has the form of lognormal density function. Finally, numerical simulations are presented to verify the above conclusions.
引用
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页数:25
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