報告題目🦙：
An Inverse Method to Extract the Time Dependent Transmission Coefficient from Infection Data（從感染數據提取時變傳播系數的一個逆方法）
報告時間：2017年7月4日（周二）上午9:30-10:30
報告地點🍲✦：必一体育平台二樓會議室
報告摘要🎞：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.
報告人：王浩，加拿大阿拉伯塔（Alberta）大學教授。2003年畢業於中國科學技術大學，獲數學和計算機科學雙理學學士學位; 2006年於美國亞利桑那（Arizona）州立大學獲博士學位; 2007年1月至7月為亞利桑那州立大學博士後; 2007年8月至2009年6月在喬治亞理工必一（美國大學）做博士後; 2009年7月至今在阿拉伯塔（Alberta）大學工作👲🏼。 公開發表SCI論文40余篇，主持多項加拿大自然科學和工程研究基金(NSERC)。