Analysis of a stochastic HIV-1 infection model with degenerate diffusion

被引:53
作者
Feng, Tao [1 ,2 ]
Qiu, Zhipeng [1 ]
Meng, Xinzhu [2 ]
Rong, Libin [3 ]
机构
[1] Nanjing Univ Sci & Technol, Dept Appl Math, Nanjing 210094, Jiangsu, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
[3] Univ Florida, Dept Math, Gainesville, FL 32611 USA
基金
中国国家自然科学基金;
关键词
Stochastic stability; HIV-1 infection model; Ergodicity; Polynomial convergence rate; Cell-to-cell spread; Invariant measure; SEIR EPIDEMIC MODELS; MATHEMATICAL-ANALYSIS; NUMERICAL SIMULATIONS; DYNAMICS; SIR; STABILITY; ERGODICITY; EXTINCTION; RECURRENCE; BEHAVIOR;
D O I
10.1016/j.amc.2018.12.007
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
This paper studies a stochastic HIV-1 infection model with degenerate diffusion. The asymptotic dynamics of the stochastic model are shown to be governed by a threshold parameter. When the parameter is negative, the infection is predicted to go extinct exponentially while the level of healthy cells converges weakly to a unique invariant measure. When the threshold parameter is positive, the solution of the stochastic model converges polynomially to a unique invariant probability measure, indicating that the system admits a unique ergodic stationary distribution. Numerical simulations are conducted to show the analytical results. These results highlight the role of environmental noise in the spread of HIV-1. The method can also be applied to the non-degenerate systems. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:437 / 455
页数:19
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