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stat.AP2026
A varying-coefficient model for characterizing duration-driven heterogeneity in flood-related health impacts
Sarika Aggarwal, Phillip B. Nicol, Brent A. Coull +1
Previous work revealed associations between flood exposure and adverse health outcomes during and in the aftermath of flood events. Floods are highly heterogeneous events, largely…
stat.AP2020
Integrated causal-predictive machine learning models for tropical cyclone epidemiology
Rachel C. Nethery, Nina Katz-Christy, Marianthi-Anna Kioumourtzoglou +3
Strategic preparedness has been shown to reduce the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protectiv…
stat.AP2019
Causal inference and machine learning approaches for evaluation of the health impacts of large-scale air quality regulations
Rachel C. Nethery, Fabrizia Mealli, Jason D. Sacks +1
We develop a causal inference approach to estimate the number of adverse health events prevented by large-scale air quality regulations via changes in exposure to multiple pollutan…