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

报 告 人:宋鹏飞 讲师 西安交通大学

邀请人:李善兵

照片:

报告时间:2020年7月10日(周五) 15:00-16:00

腾讯会议ID:154 640 675

报告人简介:宋鹏飞,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,合作导师楼元教授。宋鹏飞的研究方向是偏微分方程、泛函微分方程以及传染病多尺度模型研究,在J. Differential Equations》,《J. Math. Biol.》,《Bull. Math. Biol.》等杂志发表论文5篇。

报告摘要: I 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.

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