Dr. Dominici will provide an overview of data science methods, including methods for Bayesian analysis, causal inference and machine learning, that can inform environmental policy. Dominici draws on work analyzing a data platform of unprecedented size and representativeness, which includes more than 500 million observations on the health experience of over 95% of the U.S. population above age 65, linked to air pollution exposure and several confounders. Dominici will also provide an overview of studies on air pollution exposure, environmental racism and wildfires, and how these can exacerbate vulnerability to COVID-19.
Speaker: Francesca Dominici, PhD, Professor of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University
Register: http://tiny.cc/EpiBioEmailList