Integrated causal-predictive machine learning models for tropical cyclone epidemiology.

ABSTRACT: Strategic preparedness reduces the adverse health impacts of hurricanes and tropical storms, referred to collectively as tropical cyclones (TCs), but its protective impact could be enhanced by a more comprehensive and rigorous characterization of TC epidemiology. To generate the insights and tools necessary for high-precision TC preparedness, we introduce a machine learning approach that standardizes estimation of historic TC health impacts, discovers common patterns and sources of heterogeneity in those health impacts, and enables identification of communities at highest health risk for future TCs. The model integrates (i) a causal inference component to quantify the immediate health impacts of recent historic TCs at high spatial resolution and (ii) a predictive component that captures ho

SUBMITTER: Nethery RC 

PROVIDER: S-EPMC10102905 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature