11月23日 西安交通大学宋鹏飞博士学术报告

发布时间:2023-11-20   浏览次数:372

报 告 人:宋鹏飞 博士

报告题目:Spatial-temporal modelling and analysis of infectious disease

报告时间:2023年11月23日(周四)上午8:30-11:30

报告地点:腾讯会议:149-223-166

主办单位:太阳成集团、数学研究院、科学技术研究院

报告人简介:

       宋鹏飞,男,理学博士,西安交通大学助理教授。2014年获得西安交通大学数学学士学位;2020年获得西安交通大学数学博士学位,导师肖燕妮教授;2017-2019在俄亥俄州立大学联合培养两年,导师楼元教授;2021-2023在加拿大约克大学吴建宏教授课题组进行博士后研究。 主要研究方向是深度学习与微分方程耦合理论,偏微分方程、泛函微分方程以及传染病多尺度模型研究,在《SIAM on Applied Mathematics》,《J. Differential Equations》,《J. Math. Biol.》,《Bull. Math. Biol.》等国际知名杂志发表论文14篇。

报告摘要:

       He will give this talk from theoretical and practical perspectives.

       For the first theoretical part, an SEIRS reaction-diffusion model with spatially heterogeneity was proposed. The basic reproduction number (R0) was showed to be connected with the principal eigenvalue of a linear cooperative elliptic system and threshold-type results on the global dynamics in terms of R0 were established. The monotonicity of R0 with respect to the diffusion rates of the exposed and infected individuals, which does not hold in general, is established in several cases. Finally, the asymptotic profile of the endemic equilibrium is investigated. These results reveal the importance of the movement of the exposed and recovered individuals in disease dynamics.

       For the second practical part, a multi-stage and multi-scale SEIR epidemic patch model with deterministic and random diffusions was established. The modeling approach was incorporated with the Eulerian diffusion and the Lagrangian diffusion, and built upon multi-source training data with time-dependent parameters, so that the model has strong adaptability and effectiveness, and can be applied to study and predict different stages of emerging diseases (Sporadic, Outbreak, Epidemic, Endemic, Pandemic) and the transmission patterns at different spatial scales. As a case study, the proposed model was used to analyze the spatial spread of the novel coronavirus between Wuhan and Beijing.