题目：Emerging disease dynamics in a model coupling within-host and between-host systems

演讲者：Zhilan Feng,  Purdue University，US

时间：2017年7月14日9:00至11:00

地点：理科楼408

摘要：Epidemiological models and immunological models have been studied largely independently. However, the two biological processes (within- and between-host interactions) occur jointly and models that couple the two processes may generate new biological insights. We developed and analyzed ODE models that link an SI epidemiological model and an immunological model for pathogen-cell dynamics. When the two sub-systems are considered in isolation, dynamics are standard and simple. That is, either the infection-free equilibrium is stable or a unique positive equilibrium is stable depending on the whether the relevant reproduction number is less or greater than 1. However, when the two sub-systems are dynamically coupled, the full system exhibits more complex dynamics including backward bifurcations; that is, multiple positive equilibria exist with one of which being stable even when the reproduction number is less than 1. The biological implications of such bifurcations are illustrated using an example concerning the spread and control of toxoplasmosis.

简介：Zhilan Feng studied mathematics at Jilin and Arizona State Universities, where she was a doctoral student of Horst Thieme. She was a post-doctoral and visiting fellow with Carlos Castillo-Chavez and Simon Levin at Cornell and Princeton Universities, respectively, before joining the faculty in the Department of Mathematics at Purdue University, where she became full professor in 2005. Her research includes mathematical modeling of ecology and epidemiology using ordinary, partial, and integro-differential equations. Many of her research projects had been partially supported by grants from NSF, CDC, James S. McDonnell Foundation, and Showalter Trust.  She is currently an editorial board member of the SIAM Journal of Applied Mathematics, Journal of Theoretical Biology, Mathematical Biosciences, and Mathematical Biosciences and Engineering.