走向现代数学学术报告 - 黄国文副教授（No. 800)

报告题目：Statistical Methods for Short-term Environmental Health Effects: Challenges and Innovations

报 告 人：黄国文 副教授（Western University）

邀 请 人：王大斌 教授

报告时间：2025年6月18日 16:00

报告地点：东海岸校区-D实209

报告摘要：Short-term exposure to air pollution has significant impacts on population health, yet epidemiological studies often face challenges such as missing data, outliers, and exposure uncertainty. In this talk, I will discuss our recent work on pollution and health outcome models aimed at addressing these challenges. I will present a hierarchical pollution model that handles outliers, missing data, and seasonal variation in pollutant correlations, enabling accurate exposure estimation. I will also introduce a case-crossover framework for estimating short-term health risks, highlighting how overdispersion and exposure misclassification are accounted for. Our application to Canadian urban census divisions demonstrates the strong impacts of PM2.5, NO2, and O3 on respiratory and circulatory health. Finally, I will discuss ongoing work to refine AQHI and propose future directions for integrating spatial prediction and causal inference frameworks in environmental health studies.

个人简介：Dr. Guowen Huang is an Assistant Professor in Statistics at Western University. He earned his PhD in Statistics from the University of Glasgow and previously held postdoctoral research positions at National Tsing Hua University and the University of Toronto. Before joining Western, Dr. Huang was an Associate Professor at Shantou University. His research specializes in spatial statistics, particularly the statistical modeling of air pollution data and its effects on human health.