2nd Asia Summer School 2024 - Time-series Regression for Public Health

Facilitator Role - Time-series Regression for Public Health

I participated as a facilitator in the 2nd Asia Summer School 2024 on Time-series Regression for Public Health, an advanced short course designed to strengthen technical capacity in environmental and public-health time-series analyses.

The school focused on applying modern epidemiological designs (time-series, case-crossover, distributed-lag models, interrupted-time-series, multi-location studies) to assess health impacts of environmental exposures such as air pollution and extreme temperatures.

My Contributions

• Supported both conceptual lectures and practical R-based sessions, assisting instructors during hands-on coding exercises.
• Guided participants in building and interpreting time-series and distributed-lag models for real-world environmental-health datasets.
• Helped troubleshoot R scripts, package installation, and data-handling issues to ensure smooth participation during labs.
• Facilitated group work and discussions on model interpretation, assumptions, and presentation of epidemiologic evidence.
• Provided feedback on group presentations and encouraged collaborative problem-solving and peer-learning.

Program Highlights

• Date: 22 – 26 July 2024
• Venue: Room N101, Faculty of Medicine Bldg 3, Hongo Campus, University of Tokyo
• Daily Structure: Morning lectures on statistical and epidemiologic concepts; afternoon R-based practical sessions; group projects; invited seminars.
• Special Sessions:
  • Burden-of-disease estimation due to environmental exposures
  • Interrupted-time-series and policy evaluation
  • Two-stage multi-location meta-analysis
  • Invited seminars by Dr Shuhei Terada (ambient temperature & preterm birth, Japan multi-city study) and Dr Francesco Sera (causal inference in epidemiologic time-series).

Skills & Tools

• Epidemiologic study designs: time-series, case-crossover, distributed-lag, interrupted-time-series, multi-site meta-analysis
• R and RStudio for data manipulation, visualization, and regression modelling
• Application of cross-basis functions (DLNM) for distributed-lag effects
• Meta-analytic techniques and heterogeneity assessment (Cochran Q, I²)
• Collaborative facilitation and technical mentoring in an international training environment

Reference Material

• Core texts:
  • Gasparrini A. Distributed Lag Non-Linear Models in R (tutorial notes)
  • Bhaskaran K et al. Time-Series Regression and Environmental Epidemiology (selected readings)
• Software: R (≥4.3) & RStudio with packages dlnm, splines, ggplot2, metafor, Epi, etc.
• Other resources: WHO and IARC guidelines on environmental-health metrics and burden-of-disease estimation.

The 4th Edition of Asia Summer School is scheduled from 13th to 17th July 2026.
Learn more and apply for the 4th Asia Summer School Program.