Disease invasion risks on growing random networks
发布人: 曹思圆   发布时间: 2018-04-26   浏览次数: 10

主讲人:马君岭 教授
主持人:傅显隆 教授
开始时间:2018-4-28(周六) 下午13:45-14:30
主办单位:数学科学学院 科技处

马君岭教授2002年于普林斯顿大学取得应用数学专业哲学博士学位。现任职于加拿大维多利亚大学(University of Victoria)。从事传染病的数学建模研究。主要研究方向有艾滋病,流感的感染和死亡数据分析,建模,预测,以及传染病在接触网络上的传播的机理和数学描述。在《Annal of Internal Medicine》,《Procedings of National Academy of Sciences》,《Procedings of the Royal Society B》,《BMC Infectious Diseases》,《Journal of Mathematical Biology》,《Mathematical Biosciences》, 《Journal of Theoretical Biology》, 《Bulletin of Mathematical Biology》等较有影响的期刊发表过多篇论文。

Classical disease models predict that, if transmission rate between any pair of individuals remain constant, then the disease invasion risk in a population, measured by the basic reproduction number, increases linearly with the population size. However, on a growing random network, we found that the risk may reaches a maximum then decrease to an equilibrium risk while the population increases to an equilibrium. I will show that this is caused by the lack of proper modeling of the dynamics of contacts in classical models. After including the changes of the contact rate caused by births and deaths, classical disease models show the same behaviour in disease invasion risks.