Biostatistics Weekly Seminar

How much evidence do you need? Data science to inform environmental policy during the COVID-19 pandemic

Francesca Dominici, PhD
Harvard School of Public Health

On December 7, 2020, the New York Times reported that President Trump declined to tighten soot rules. This was despite strong evidence of the adverse health effects including a link to COVID-19 deaths. In this talk, I will provide an overview of data science methods, including methods for causal inference and machine learning, to inform environmental policy. This is based on my work analyzing a data platform of unprecedented size and representativeness. The platform includes more than 500 million observations on the health experience of over 95% of the US population older than 65 years old linked to air pollution exposure and several confounders. Finally, I provide an overview of my studies on air pollution exposure, environmental racism, wildfires, and how they also can exacerbate the vulnerability to COVID-19.

Zoom (Link to Follow)
31 March 2021

Speaker Itinerary

Topic revision: r2 - 24 Mar 2021, AndrewSpieker

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