School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, PR China.
School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, PR China.
J Virol Methods. 2019 Apr;266:103-113. doi: 10.1016/j.jviromet.2019.01.014. Epub 2019 Feb 1.
Understanding the infection and pathogenesis mechanism of hepatitis B virus (HBV) is very important for the prevention and treatment of hepatitis B. Mathematical models contribute to illuminate the dynamic process of HBV replication in vivo. Therefore, in this paper we review the viral dynamics in HBV infection, which may help us further understand the dynamic mechanism of HBV infection and efficacy of antiviral treatment. Firstly, we introduce a family of deterministic models by considering different biological mechanisms, such as, antiviral therapy, CTL immune response, multi-types of infected hepatocytes, time delay and spatial diffusion. Particularly, we briefly describe the stochastic models of HBV infection. Secondly, we introduce the commonly used parameter estimation methods for HBV viral dynamic models and briefly discuss how to use these methods to estimate unknown parameters (such as drug efficacy) through two specific examples. We also discuss the idea and method of model identification and use a specific example to illustrate its application. Finally, we propose three new research programs, namely, considering HBV drug-resistant strain, coupling within-host and between-host dynamics in HBV infection and linking population dynamics with evolutionary dynamics of HBV diversity.
了解乙型肝炎病毒（HBV）的感染和发病机制对于乙型肝炎的预防和治疗非常重要。数学模型有助于阐明HBV 在体内的复制动态过程。因此，本文综述了 HBV 感染中的病毒动力学，这可能有助于我们进一步了解 HBV 感染的动态机制和抗病毒治疗的效果。首先，我们通过考虑不同的生物学机制，如抗病毒治疗、CTL 免疫反应、多种感染的肝细胞、时滞和空间扩散，引入了一系列确定性模型。特别地，我们简要描述了 HBV 感染的随机模型。其次，我们介绍了 HBV 病毒动力学模型常用的参数估计方法，并通过两个具体的例子简要讨论了如何通过这些方法来估计未知参数（如药物疗效）。我们还讨论了模型识别的思路和方法，并通过一个具体的例子来说明其应用。最后，我们提出了三个新的研究计划，即考虑 HBV 耐药株、HBV 感染中宿主内和宿主间动力学的耦合以及将种群动力学与 HBV 多样性的进化动力学联系起来。
