Department of Physics, Ryerson University, Toronto, ON, M5B 2K3, Canada.
BMC Public Health. 2011 Feb 25;11 Suppl 1(Suppl 1):S7. doi: 10.1186/1471-2458-11-S1-S7.
Most mathematical models used to study the dynamics of influenza A have thus far focused on the between-host population level, with the aim to inform public health decisions regarding issues such as drug and social distancing intervention strategies, antiviral stockpiling or vaccine distribution. Here, we investigate mathematical modeling of influenza infection spread at a different scale; namely that occurring within an individual host or a cell culture. We review the models that have been developed in the last decades and discuss their contributions to our understanding of the dynamics of influenza infections. We review kinetic parameters (e.g., viral clearance rate, lifespan of infected cells) and values obtained through fitting mathematical models, and contrast them with values obtained directly from experiments. We explore the symbiotic role of mathematical models and experimental assays in improving our quantitative understanding of influenza infection dynamics. We also discuss the challenges in developing better, more comprehensive models for the course of influenza infections within a host or cell culture. Finally, we explain the contributions of such modeling efforts to important public health issues, and suggest future modeling studies that can help to address additional questions relevant to public health.
迄今为止，用于研究甲型流感动力学的大多数数学模型都集中在宿主间种群水平上，旨在为公共卫生决策提供信息，例如药物和社交距离干预策略、抗病毒药物储备或疫苗分发。在这里，我们研究了在不同规模上发生的流感感染传播的数学建模；即发生在个体宿主或细胞培养物内。我们回顾了过去几十年中开发的模型，并讨论了它们对我们理解流感感染动力学的贡献。我们回顾了通过拟合数学模型获得的动力学参数（例如病毒清除率、感染细胞的寿命）和值，并将其与直接从实验获得的值进行对比。我们探讨了数学模型和实验分析在提高我们对流感感染动力学的定量理解方面的共生作用。我们还讨论了在宿主或细胞培养物内开发更好、更全面的流感感染过程模型所面临的挑战。最后，我们解释了此类建模工作对重要公共卫生问题的贡献，并提出了未来的建模研究，可以帮助解决与公共卫生相关的其他问题。
