Triply robust approach to evaluate the health impacts of extreme weather events
Authors/Creators/ Team Members: Lingzhi Chu, Kai Chen
Specific purpose of code: This code is designed to evaluate the relationships between extreme weather events and health outcomes.
General Application: The code was first designed to evaluate the mortality risk associated with flood in the contiguous United States (https://doi.org/10.1038/s41467-025-58236-0). The code could be used with other “pulse” events (e.g., extreme weather events) or other health outcomes (e.g., hospital visits).
How does or could this code allow researchers to assess research questions related to aging or life course?: This code could be used for any specific age group or subsets by age.
Data sets used:
- Population, socioeconomic, or health data: Mortality data from CDC National Center for Health Statistics.
- Climate, weather, disaster or environment data: NOAA Storm Events Database.
Are all the data publicly available or are some restricted-access? NOAA Storm Events Database is publicly available. The monthly county-level cause specific mortality data are protected and are not publicly available due to data privacy laws but can be requested from the National Center for Health Statistics (https:// www.cdc.gov/nchs/index.htm).
Links to data: https://github.com/CHENlab-Yale/Flood_mortality_US
Coding Language: R
Tools and Packages used: N/A
Output(s): https:// doi.org/10.1038/s41467-025-58236-0
Spatial extent: No restriction
Temporal extent: No restriction
Published papers that use this code:
Chu, Lingzhi, Joshua L. Warren, Erica S. Spatz, Sarah Lowe, Yuan Lu, Xiaomei Ma, Joseph S. Ross, Harlan M. Krumholz, and Kai Chen. “Floods and cause-specific mortality in the United States applying a triply robust approach.” Nature Communications 16, no. 1 (2025): 2853.