Topic: Bushfire Air Pollution and Risk Control: Epidemiological Statistical Methods for Respiratory Health Research

Lecturer: Dr. Xin Dai, research fellow at the University of Melbourne

Time: Friday, October 09, 2026, 09:00, UTC+8

Zoom Meeting ID: 824 3744 9199

Password: 147153

Biography: Dr. Xin Dai is a research fellow at the Allergy and Lung Health Unit, University of Melbourne. Her research explores environmental and early-life risk factors for respiratory diseases such as asthma, translating evidence into patient-centered interventions. She leads studies on long-term health effects of Australian bushfire smoke and evaluates mitigation measures, including HEPA air purifiers for people living with asthma and COPD. With rich experience in clinical trials and epidemiology, she teaches epidemiology at the university. Her collaborative research partners with clinics, research bodies, and industry to advance respiratory health globally.

Abstract: This lecture introduces the practical applications of epidemiological statistics through two ongoing respiratory health studies. The first part covers a double-blind randomized controlled trial that assesses the health impacts of household HEPA air purifiers on patients with asthma and COPD. It explains random allocation, the blinded design, the selection of primary and secondary outcomes, analysis of repeated-measures data, and approaches to evaluating intervention adherence and safety. The second part illustrates the application of machine learning in environmental epidemiology. The research team uses machine learning models to estimate daily concentrations of PM₂.₅ originating from bushfire smoke. By linking exposure data to residential addresses of long-term cohort participants across different time periods, the team further analyzes associations between long-term bushfire smoke exposure and asthma, lung dysfunction, and other respiratory diseases. With these two cases, the talk demonstrates that epidemiology is more than statistics. It organically integrates statistical models with public health implications to generate scientific evidence for environmental health and the prevention and management of chronic respiratory diseases.

Rewritten by: Mei Mengqi

Edited by: Yu Bingjie

Source: School of Mathematics and Statistics