Optimizing Vaccination Strategies within a Population-Pathogen Landscape

建模和计算方法为研究个人和群体层面的疾病动态提供了强有力的工具。最近的分析发展，加上信息和通信技术的进步，为数学免疫学和流行病学开辟了新的前景，提出了新的挑战。数学、统计和计算建模在应对这些挑战方面具有巨大的潜力，它提供了综合框架，使假设变得明确并最好地利用有限的数据，突出决定政策需求的关键因素，提供量化预测，并评估疾病动力学和控制程序中隐含的风险、收益和权衡。数学和计算模型的效用是有据可查的。一个重要的例子是，在2009年流感大流行期间，就疫苗接种战略和抗病毒药物的使用执行了基于模型的建议。

Modelling and computational approaches provide powerful tools in the study of disease dynamics at both the individual and population levels. Recent analytical developments, coupled with advances in information and communications technologies, have opened up novel vistas and presented new challenges in mathematical immunology and epidemiology. Mathematical, statistical, and computational modelling has enormous potential to address these challenges, offering integrated frameworks for making assumptions explicit and for best using limited data, highlighting key factors that determine policy needs, providing quantitative projections, and assessing risks, benefits, and trade-offs that are implicit in disease dynamics and control programs. The utility of mathematical and computational modelling is well-documented. An important example is the implementation of model-based recommendations for vaccination strategies and use of antiviral drugs during the 2009 pandemic influenza.