报告题目：
An Inverse Method to Extract the Time Dependent Transmission Coefficient from Infection Data（从感染数据提取时变传播系数的一个逆方法）
报告时间：2017年7月4日（周二）上午9:30-10:30
报告地点：bat365在线平台二楼会议室
报告摘要：The transmission rate of many acute infectious diseases varies significantly in time, but the underlying mechanisms are usually uncertain. They may include seasonal changes in the environment, contact rate, immune system response, etc. The transmission rate has been thought difficult to measure directly. We present a new algorithm to compute the time-dependent transmission rate directly from prevalence data, which makes no assumptions about the number of susceptible or vital rates. The algorithm follows our complete and explicit solution of a mathematical inverse problem for SIR-type transmission models. We prove that almost any infection profile can be perfectly fitted by an SIR model with variable transmission rate. This clearly shows a serious danger of overfitting such transmission models. We illustrate the algorithm with historic UK measles data and our observations support the common belief that measles transmission was predominantly driven by school contacts. We apply this inverse method to pre-vaccination and post-vaccination measles data in Liverpool and London. The comparison leads to some insightful observations.
报告人：王浩，加拿大阿拉伯塔（Alberta）大学教授。2003年毕业于中国科学技术大学，获数学和计算机科学双理学学士学位; 2006年于美国亚利桑那（Arizona）州立大学获博士学位; 2007年1月至7月为亚利桑那州立大学博士后; 2007年8月至2009年6月在乔治亚理工学院（美国大学）做博士后; 2009年7月至今在阿拉伯塔（Alberta）大学工作。 公开发表SCI论文40余篇，主持多项加拿大自然科学和工程研究基金(NSERC)。