Global dynamics of deterministic-stochastic dengue infection model including multi specific receptors via crossover effects

被引:9
|
作者
Rashid, Saima [1 ]
Jarad, Fahd [2 ,3 ,4 ]
El-Marouf, Sobhy A. A. [5 ,6 ]
Elagan, Sayed K. [6 ,7 ]
机构
[1] Govt Coll Univ, Dept Math, Faislabad, Pakistan
[2] Cankaya Univ, Dept Math, Ankara, Turkiye
[3] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung, Taiwan
[4] King Abdulaziz Univ, Dept Math, Jeddah, Saudi Arabia
[5] Taibah Univ, Fac Sci, Dept Math, Medina, Saudi Arabia
[6] Fac Sci Menoufia Univ, Dept Math & Comp Sci, Shibin Al Kawm, Egypt
[7] Taif Univ, Coll Sci, Dept Math & Stat, POB 11099, Taif 21944, Saudi Arabia
来源
AIMS MATHEMATICS | 2023年 / 8卷 / 03期
关键词
dengue viral model; stochastic-deterministic models; numerical solutions; Ito ? derivative; chaotic attractor; EPIDEMIC MODEL; VIRUS; PATHOGENESIS; FEVER;
D O I
10.3934/math.2023327
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Dengue viruses have distinct viral regularities due to the their serotypes. Dengue can be aggravated from a simple fever in an acute infection to a presumably fatal secondary pathogen. This article investigates a deterministic-stochastic secondary dengue viral infection (SDVI) model including logistic growth and a nonlinear incidence rate through the use of piecewise fractional differential equations. This framework accounts for the fact that the dengue virus can penetrate various kinds of specific receptors. Because of the supplementary infection, the system comprises both heterologous and homologous antibody. For the deterministic case, we determine the invariant region and threshold for the aforesaid model. Besides that, we demonstrate that the suggested stochastic SDVI model yields a global and non-negative solution. Taking into consideration effective Lyapunov candidates, the sufficient requirements for the presence of an ergodic stationary distribution of the solution to the stochastic SDVI model are generated. This report basically utilizes a novel idea of piecewise differentiation and integration. This method aids in the acquisition of mechanisms, including crossover impacts. Graphical illustrations of piecewise modeling techniques for chaos challenges are demonstrated. A piecewise numerical scheme is addressed. For various cases, numerical simulations are presented.
引用
收藏
页码:6466 / 6503
页数:38
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