Rajasekar S P, Pitchaimani M, Zhu Quanxin
Ramanujan Institute for Advanced Study in Mathematics, University of Madras, Chennai, Tamil Nadu, 600 005 India.
Department of Mathematics, Government Arts College for Women, Nilakottai, Tamil Nadu, 624 202 India.
Acta Math Sci. 2022;42(5):2087-2112. doi: 10.1007/s10473-022-0521-1. Epub 2022 Jul 25.
The hepatitis C virus is hitherto a tremendous threat to human beings, but many researchers have analyzed mathematical models for hepatitis C virus transmission dynamics only in the deterministic case. Stochasticity plays an immense role in pathology and epidemiology. Hence, the main theme of this article is to investigate a stochastic epidemic hepatitis C virus model with five states of epidemiological classification: susceptible, acutely infected, chronically infected, recovered or removed and chronically infected, and treated. The stochastic hepatitis C virus model in epidemiology is established based on the environmental influence on individuals, is manifested by stochastic perturbations, and is proportional to each state. We assert that the stochastic HCV model has a unique global positive solution and attains sufficient conditions for the extinction of the hepatotropic RNA virus. Furthermore, by constructing a suitable Lyapunov function, we obtain sufficient conditions for the existence of an ergodic stationary distribution of the solutions to the stochastic HCV model. Moreover, this article confirms that using numerical simulations, the six parameters of the stochastic HCV model can have a high impact over the disease transmission dynamics, specifically the disease transmission rate, the rate of chronically infected population, the rate of progression to chronic infection, the treatment failure rate of chronically infected population, the recovery rate from chronic infection and the treatment rate of the chronically infected population. Eventually, numerical simulations validate the effectiveness of our theoretical conclusions.
丙型肝炎病毒迄今为止对人类构成巨大威胁,但许多研究人员仅在确定性情况下分析了丙型肝炎病毒传播动力学的数学模型。随机性在病理学和流行病学中起着巨大作用。因此,本文的主题是研究一个具有五种流行病学分类状态的随机丙型肝炎病毒流行模型:易感、急性感染、慢性感染、康复或清除以及慢性感染且接受治疗。流行病学中的随机丙型肝炎病毒模型是基于环境对个体的影响建立的,表现为随机扰动,且与每种状态成比例。我们断言,随机丙型肝炎病毒模型有唯一的全局正解,并获得了嗜肝RNA病毒灭绝的充分条件。此外,通过构造一个合适的李雅普诺夫函数,我们得到了随机丙型肝炎病毒模型解的遍历平稳分布存在的充分条件。而且,本文证实,通过数值模拟,随机丙型肝炎病毒模型的六个参数对疾病传播动力学有很大影响,特别是疾病传播率、慢性感染人群的比例、进展为慢性感染的速率、慢性感染人群的治疗失败率、慢性感染的康复率以及慢性感染人群的治疗率。最终,数值模拟验证了我们理论结论的有效性。