報 告 人：宋鵬飛 博士

報告題目：Spatial-temporal modelling and analysis of infectious disease

報告時間：2023年11月23日（周四）上午8:30-11:30

報告地點：騰訊會議：149-223-166

主辦單位：數(shù)學與統(tǒng)計學院、數(shù)學研究院、科學技術(shù)研究院

報告人簡介：

       宋鵬飛，男，理學博士，西安交通大學助理教授。2014年獲得西安交通大學數(shù)學學士學位；2020年獲得西安交通大學數(shù)學博士學位，導師肖燕妮教授；2017-2019在俄亥俄州立大學聯(lián)合培養(yǎng)兩年，導師樓元教授；2021-2023在加拿大約克大學吳建宏教授課題組進行博士后研究。 主要研究方向是深度學習與微分方程耦合理論，偏微分方程、泛函微分方程以及傳染病多尺度模型研究，在《SIAM on Applied Mathematics》，《J. Differential Equations》，《J. Math. Biol.》，《Bull. Math. Biol.》等國際知名雜志發(fā)表論文14篇。

報告摘要：

       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.