A New Perspective on Infection Forces with Demonstration by a DDE Infectious Disease Model

发布者:文明办发布时间:2022-05-24浏览次数:484



主讲人:邹幸福 加拿大西安大略大学应用数学系教授


时间:2022年5月29日9:00


地点:腾讯会议 478 127 447


举办单位:数理学院


主讲人介绍:邹幸福,加拿大西安大略大学应用数学系教授。分别在中山大学,湖南大学和加拿大York University获得学士,硕士和博士学位,并在加拿大University of Victoria, 和美国Georgia Institute of Technology 从事过博士后研究工作。曾任教于加拿大Memorial University of Newfoundland。研究兴趣为微分方程和动力系统的理论及应用,特别是反应扩散方程、常泛函微分方程及偏泛函微分方程及其在生物领域的应用方面取得了一系列有影响力的成果,在J. Diff. Eqns.,SIAM J. Appl. Math.,SIAM J. Math. Anal.等权威杂志发表研究论文100多篇,引用1700多次,最高单篇引用次数400多次。曾获加拿大国家自然科学和工程基金博士后奖,Petro-Canada青年研究创新奖,安大略省长杰出研究奖,UWO杰出研究教授奖等。主持完成了加拿大国家自然科学和工程基金个人项目、安达略自然资源部基金、加拿大MITACS PDF基金、加拿大全国性基金MITACS等。


内容介绍:In this talk, we will revisit the notion of infection force from a new angle which can offer a new perspective to motivate and justify some infection force functions. Our approach not only can explain many existing infection force functions in the literature, it can also motivate new forms of infection force functions, particularly infection forces depending on disease surveillance of the past. As a demonstration, we propose an SIRS model with delay. We comprehensively investigate the disease dynamics represented by this model, particularly focusing on the local bifurcation caused by the delay and another parameter that reflects the weight of the past epidemics in the infection force. We confirm Hopf bifurcations both theoretically and numerically. The results show that depending on how recent the disease surveillance data are, their assigned weight may have a different impact on disease control measures.



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