Assessing United States County-Level Exposure for Research on Tropical Cyclones and Human Health

Abstract

Background: Tropical cyclone epidemiology can be advanced through exposure assessment methods that are comprehensive and consistent across space and time, as these facilitate multiyear, multistorm studies. Further, an understanding of patterns in and between exposure metrics that are based on specific hazards of the storm can help in designing tropical cyclone epidemiological research. Objectives: a ) Provide an open-source data set for tropical cyclone exposure assessment for epidemiological research; and b ) investigate patterns and agreement between county-level assessments of tropical cyclone exposure based on different storm hazards. Methods: We created an open-source data set with data at the county level on exposure to four tropical cyclone hazards: peak sustained wind, rainfall, flooding, and tornadoes. The data cover all eastern U.S. counties for all land-falling or near-land Atlantic basin storms, covering 1996–2011 for all metrics and up to 1988–2018 for specific metrics. We validated measurements against other data sources and investigated patterns and agreement among binary exposure classifications based on these metrics, as well as compared them to use of distance from the storm’s track, which has been used as a proxy for exposure in some epidemiological studies. Results: Our open-source data set was typically consistent with data from other sources, and we present and discuss areas of disagreement and other caveats. Over the study period and area, tropical cyclones typically brought different hazards to different counties. Therefore, when comparing exposure assessment between different hazard-specific metrics, agreement was usually low, as it also was when comparing exposure assessment based on a distance-based proxy measurement and any of the hazard-specific metrics. Discussion: Our results provide a multihazard data set that can be leveraged for epidemiological research on tropical cyclones, as well as insights that can inform the design and analysis for tropical cyclone epidemiological research. https://doi.org/10.1289/EHP6976

Tropical cyclone exposure is associated with increased hospitalization rates in older adults

“…Our results are based on patient county of residence; this may not necessarily be the location of the patient during a tropical cyclone. Furthermore, although we conducted analyses at the county level, tropical cyclone wind fields tend to be larger than the size of a county 58 . Any misclassification, nonetheless, is likely non-differential as it is not expected to be correlated with the outcomes assessed.…”

“…Exposure assessment. We obtained data on tropical cyclone wind exposure in the United States from the hurricaneexposure (version 0.1.1) and hurricaneexposuredata (version 0.1.0) packages in R, with full space and time coverage over our study period, and described in detail elsewhere 58,[62][63][64] . In brief, an exhaustive assessment of tropical cyclones was generated from those recorded in the HUR-DAT2 dataset based on wind field modeling and validation against observations from weather stations 65 .…”

“…First, all tropical cyclones were measured for how close they came to at least one US county. Cyclones that came within 250 km were retained for further wind modeling 58 . For these, the wind field at each county's population mean center was modeled every 15 min, while the storm was tracked, providing an estimate of peak local winds that the storm brought to that county 66 .…”

Tropical Cyclone Exposures and Health: A New Data Set to Assess Associations over Time

“…6 High winds and rainfall totals, for instance, may be consistent across a county, tornadoes or flooding may be much more localized. 1 If a county is very large, maybe only one part of it experiences flooding. Maybe houses in only a few neighborhoods are destroyed by a tornado.…”

“…In a recent paper published in Environmental Health Perspectives, Anderson and colleagues presented an open-source data set to help epidemiologists understand the health risks associated with tropical cyclones across the eastern half of the United States. 1 Forecasting technologies developed over the last several decades have led to better warning and evacuation systems. These systems have dramatically lowered deaths and injuries from direct causes when a terrible storm hits, Anderson says.…”