Merck Research Laboratories, UG1C-60, PO Box 1000, North Wales, PA 19454-1099, United States.
Math Biosci Eng. 2013 Aug;10(4):1045-65. doi: 10.3934/mbe.2013.10.1045.
Hepatitis C virus (HCV) is a leading cause of chronic liver disease. This paper presents a deterministic model for HCV infection transmission and uses the model to assess the potential impact of antiviral therapy. The model is based on the susceptible-infective-removed-susceptible (SIRS) compartmental structure with chronic primary infection and possibility of reinfection. Important epidemiologic thresholds such as the basic and control reproduction numbers and a measure of treatment impact are derived. We find that if the control reproduction number is greater than unity, there is a locally unstable infection-free equilibrium and a unique, globally asymptotically stable endemic equilibrium. If the control reproduction number is less than unity, the infection-free equilibrium is globally asymptotically stable, and HCV will be eliminated. Numerical simulations suggest that, besides the parameters that determine the basic reproduction number, reinfection plays an important role in HCV transmissions and magnitude of the public health impact of antiviral therapy. Further, treatment regimens with better efficacy holds great promise for lowering the public health burden of HCV disease.
丙型肝炎病毒 (HCV) 是慢性肝病的主要病因。本文提出了一个用于 HCV 感染传播的确定性模型,并使用该模型评估抗病毒治疗的潜在影响。该模型基于易感-感染-清除-易感 (SIRS) compartment 结构,包括慢性原发性感染和再次感染的可能性。得出了基本和控制繁殖数等重要的流行病学阈值,以及治疗效果的衡量标准。我们发现,如果控制繁殖数大于 1,则存在局部不稳定的无感染平衡点和唯一的全局渐近稳定的地方病平衡点。如果控制繁殖数小于 1,则无感染平衡点是全局渐近稳定的,HCV 将被消除。数值模拟表明,除了决定基本繁殖数的参数外,再感染在 HCV 传播中起着重要作用,并且抗病毒治疗对公共卫生的影响程度也很大。此外,疗效更好的治疗方案有望降低 HCV 疾病的公共卫生负担。