When model populations are stratified, contacts among their respective sub-populations must be described. Using a simple meta-population model, we showed that mixing among sub-populations, as well as heterogeneity in characteristics affecting their reproduction numbers, must be considered when evaluating interventions to prevent or control infectious disease outbreaks. We discuss how meta-population models with multi-level mixing could be employed to evaluate epidemic mitigation measures. We discuss also that in meta-population models, the gradient of the effective reproduction number can be used as a new tool for devising optimal vaccination strategies, as presented in Feng et al. (J Theor Biol 2015; 386:177-87). Using an SEIR model of pandemic influenza with 7 age groups, 51 spatial strata (states plus the District of Columbia) and a suitable two-level mixing function, we used the gradient to compare optimal and actual vaccination during the 2009-10 influenza pandemic in the United States (Feng et al. Submitted). We also showed that vaccination efforts could have been adjusted month-to-month during the fall of 2009 to ensure maximum impact. Together with colleagues at the China CDC, we are using this model to identify the optimal strategies for eliminating measles and controlling rubella in China.

 

报告人简介：冯芷兰，普渡大学数学系教授。冯芷兰教授是数学生物学领域知名学者，长期从事生物数学方向的研究工作，应用微分方程、随机分析、动力系统等数学理论建立模型，分析生物学、生态学、流行病学中的实际问题；结合得到的数学结论，分析其在生物领域的现实意义，并提出相应的应对措施；成功地建立了生物学家、生态学家、流行病学家、公共卫生决策者之间的联系，促进数学理论在生物学中的进一步实践应用。担任“Mathematical Biosciences、JTB”等多个国际生物数学界顶尖学术刊物的副主编。发表关于传染病研究方向学术文章100余篇。