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Mathematical Analysis of Viral Replication Dynamics and Antiviral Treatment Strategies: From Basic Models to Age-Based Multi-Scale Modeling

机译:病毒复制动力学和抗病毒治疗策略的数学分析:从基本模型到基于年龄的多尺度建模

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摘要

Viral infectious diseases are a global health concern, as is evident by recent outbreaks of the middle east respiratory syndrome, Ebola virus disease, and re-emerging zika, dengue, and chikungunya fevers. Viral epidemics are a socio-economic burden that causes short- and long-term costs for disease diagnosis and treatment as well as a loss in productivity by absenteeism. These outbreaks and their socio-economic costs underline the necessity for a precise analysis of virus-host interactions, which would help to understand disease mechanisms and to develop therapeutic interventions. The combination of quantitative measurements and dynamic mathematical modeling has increased our understanding of the within-host infection dynamics and has led to important insights into viral pathogenesis, transmission, and disease progression. Furthermore, virus-host models helped to identify drug targets, to predict the treatment duration to achieve cure, and to reduce treatment costs. In this article, we review important achievements made by mathematical modeling of viral kinetics on the extracellular, intracellular, and multi-scale level for Human Immunodeficiency Virus, Hepatitis C Virus, Influenza A Virus, Ebola Virus, Dengue Virus, and Zika Virus. Herein, we focus on basic mathematical models on the population scale (so-called target cell-limited models), detailed models regarding the most important steps in the viral life cycle, and the combination of both. For this purpose, we review how mathematical modeling of viral dynamics helped to understand the virus-host interactions and disease progression or clearance. Additionally, we review different types and effects of therapeutic strategies and how mathematical modeling has been used to predict new treatment regimens.
机译:病毒感染性疾病是全球性的健康问题,最近爆发的中东呼吸综合征,埃博拉病毒病以及寨卡,登革热和基孔肯雅热再度爆发就证明了这一点。病毒流行是一种社会经济负担,会导致疾病诊断和治疗的短期和长期成本,以及旷工造成的生产力损失。这些暴发及其社会经济成本突显了对病毒-宿主相互作用进行精确分析的必要性,这将有助于了解疾病机理并制定治疗性干预措施。定量测量和动态数学模型的结合增加了我们对宿主内部感染动力学的理解,并导致了对病毒发病机理,传播和疾病进展的重要见解。此外,病毒宿主模型有助于确定药物靶标,预测实现治愈的治疗时间并降低治疗成本。在本文中,我们将对人免疫缺陷病毒,丙型肝炎病毒,甲型流感病毒,埃博拉病毒,登革热病毒和寨卡病毒在细胞外,细胞内和多尺度水平上的病毒动力学数学建模取得的重要成就进行回顾。在这里,我们集中于人口规模的基本数学模型(所谓的目标细胞有限模型),有关病毒生命周期中最重要步骤的详细模型以及两者的结合。为此,我们回顾了病毒动力学的数学模型如何帮助理解病毒与宿主的相互作用以及疾病的进展或清除。此外,我们回顾了治疗策略的不同类型和效果,以及如何使用数学模型来预测新的治疗方案。

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