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A New Algorithm to Recover the Time Dependent Transmission Coefficient from Infection Data
澳门新葡8455最新网站:2012年06月12日 00:00 点击数:

报告人:王皓

报告地点:澳门新葡8455最新网站615室

报告澳门新葡8455最新网站:2012年06月18日星期一15:30-17:00

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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. This work is in collaboration with Howie Weiss in Georgia Tech (US) and Mark Pollicott in University of Warwick (UK).

主讲人概况:

Dr. Hao Wang is an assistant professor in the Department of Mathematical & Statistical Sciences at the University of Alberta, an advisory board member of Centre for Mathematical Biology, an associate editor for International Journal of Numerical Analysis & Modeling – Series B, an editor for Nonlinear Dynamics and Systems Theory. He has organized many international conferences, minisymposia, workshops, and seminars. Dr. Wang has strong interests in interdisciplinary research of mathematical biology. His research group is working on areas as diverse as modeling stoichiometry-based ecological interactions, microbiology, infectious diseases, habitat destruction and biodiversity, risk assessment of oil sands pollution.

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