The Health Effects Institute (HEI) recently published a final report of the Accountability Research Program entitled Causal Inference Methods for Estimating Long-Term Health Effects of Air Quality Regulations by Zigler et al. In the study, the authors used existing and newly developed statistical methods in two case studies to assess the effects of air quality interventions to reduce PM10 concentrations in nonattainment areas, and to examine the impact of installation of scrubber technologies on emissions from coal-fired power plants.
The research team was led by Cory Zigler, and had the collaboration of Gary King, Director of the USC Institute for Global Health; Jon Samet, Director of the Harvard Institute for Quantitative Social Science; and Francesca Dominici. The team benefitted from the contributions of current and former Biostatistics postdocs Lauren Hund and Chanmin Kim, research scientists Christine Choirat and Yun Wang, and FAS undergraduate Barrett Hansen.
In assessing the report, the HEI Review Committee concluded that the study makes a major contribution to the field of accountability research in the context of air pollution and health and has provided a clear path toward further development and deployment of causal inference methods in other settings.
Our congratulations to Cory and the report coauthors!
