报告一

报告题目：Asymptotic Behavior of The Principal Eigenvalue and Basic Reproduction Ratio for Periodic Patch Models

报告人：赵晓强(加拿大纽芬兰纪念大学)

报告时间：12月17日（星期六）上午8:30-9:30

报告地点：腾讯会议（977-202-589）

报告人简介：

赵晓强，加拿大纽芬兰纪念大学数学与统计系教授，该校University Research Professorship荣誉获得者。赵教授先后于1983年和1986年在西北大学数学系获学士和硕士学位，1990年在中国科学院应用数学研究所获博士学位。赵教授长期从事动力系统、微分方程和生物数学相关领域的研究，在单调动力学、一致持久性、行波解和渐近传播速度、基本再生数的理论及应用等方面的系列工作受到同行的广泛关注和引用。迄今为止，已在“Comm.Pure Appl.Math.、J.Eur.Math.Soc.、J.reine angew.Math.、J.Math.Pures Appl.、Trans. Amer.Math.Soc.、SIAM J.Math.Anal.”等国际知名期刊上发表论文100余篇，并在Springer出版专著“Dynamical Systems in Population Biology”。赵教授个人主页：https://www.math.mun.ca/~zhao/

报告摘要：

In this talk, I will report our recent research on the asymptotic behavior of the principal eigenvalue and basic reproduction ratio associated with periodic population models in a patchy environment for small and large dispersal rates. We first deal with the eigenspace corresponding to the zero eigenvalue of the connectivity matrix. Then we investigate the limiting profile of the principal eigenvalue of an associated periodic eigenvalue problem as the dispersal rate goes to zero and infinity, respectively. We further establish the asymptotic behavior of the basic reproduction ratio in the case of small and large dispersal rates. Finally, we apply these results to a periodic Ross-Macdonald patch model. This talk is based on a joint work with Dr. Lei Zhang.

报告二

报告题目：The importance of quarantine: modelling the COVID-19 testing process

报告人：王林 (加拿大新不伦瑞克大学)

报告时间：12月17日（星期六）9:40-10:40

报告地点：腾讯会议（977-202-589）

报告人简介：

王林,2003年纽芬兰纪念大学博士毕业,现为加拿大新不伦瑞克大学教授。主要研究领域为生物数学、生态学、神经网络、流行病学和计量经济学等。主持和参与加拿大国家自然与工程基金、中国自然科学基金、加拿大MITACS基金重点项目、加拿大自然与工程战略项目等17项。发表论文100余篇。指导博士后、博士、硕士和访问学者40余名。曾获麦凯恩基金青年学者奖。

报告摘要：

We incorporate the disease state and testing state into the formulation of a COVID-19 epidemic model. For this model, the basic reproduction number is identified and its dependence on model parameters related to the testing process and isolation efficacy is discussed. The relations between the basic reproduction number, the final epidemic and peak sizes, and the model parameters are further explored numerically. We find that fast test reporting does not always

benefit the control of the COVID-19 epidemic. Moreover, the final epidemic and peak sizes do not always increase along with the basic reproduction number. Under some circumstances, lowering the basic reproduction number increases the final epidemic and peak sizes. Our findings suggest that properly implementing isolation for individuals who are waiting for their testing results would lower the basic reproduction number as well as the final epidemic and peak sizes.