The dynamical model for COVID-19 with asymptotic analysis and numerical implementations

发布日期:2021-06-09点击数:

报告人:刘继军(东南大学)

时间:2021年6月12日15:00开始

地点:理科楼LA107


摘要:The 2019 novel coronavirus (COVID-19) emerged at the end of 2019 has a great impact on China and all over the world. We establish a mathematical model for COVID-19 transmission involving the interactive effect of various factors for the infected people, including imported cases, isolating rate, diagnostic rate, recovery rate and also the mortality rate. Under the assumption that the random incubation period, the cure period and the diagnosis period are subject to the Weibull distribution, the quantity of daily existing infected people is finally governed by a linear integral-differential equation with convolution kernel. Based on the asymptotic behavior and the quantitative analysis on the model, we rigorously prove that, for limited external input patients, both the quantity of infected patients and its variation ratio will finally tend to zero, if the infected patients are sufficiently isolated or the infection rate is small enough. Finally, numerical performances for the proposed model as well as the comparisons between our simulations and the clinical data of the city Wuhan and Italy are demonstrated.


简介:刘继军,东南大学二级教授,博士生导师,享受国务院政府特殊津贴专家。现任中国工业与应用数学学会常务理事,全国老员工数学建模竞赛组委会委员,江苏省计算数学学会副理事长, 南京应用数学中心常务副主任,东南大学丘成桐中心副主任。 长期从事数学物理反问题、大规模科学计算和介质成像的数学理论和方法的研究。主持完成NSFC重大研究计划、面上项目、国际合作项目、天元基金、江苏省自然科学基金等项目的研究。已在SIAM系列杂志, Inverse Problems, Science China Mathematics, J. Comput. Maths., J. Sci. Comput.等发表学术论文130余篇,在科学出版社出版学术专著2本。曾受中国NSFC、德国DAAD、韩国21Brain Project等资助赴国外开展合作研究。现任国际SCI刊物J. Inverse Ill-posed Problems编委。 入选江苏省青蓝工程青年骨干教师、中青年学术带头人,江苏省333工程第三层次培养人选。获宝钢教育基金会全国优秀教师一等奖,作为主持人获江苏省教学成果一等奖,江苏省自然科学三等奖,教育部自然科学二等奖。


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