TY - JOUR
T1 - Assessing united states county-level exposure for research on tropical cyclones and human health
AU - Brooke Anderson, G.
AU - Ferreri, Joshua
AU - Al-Hamdan, Mohammad
AU - Crosson, William
AU - Schumacher, Andrea
AU - Guikema, Seth
AU - Quiring, Steven
AU - Eddelbuettel, Dirk
AU - Yan, Meilin
AU - Peng, Roger D.
N1 - Funding Information:
This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), the Department of Energy (grant no. DE-FG02-08ER64644), and a NASA Applied Sciences Program/Public Health Program Grant (NNX09AV81G). Rainfall data are based on data acquired as part of the mission of the NASA’s Earth Science Division and archived and distributed by the Goddard Earth Sciences Data and Information Services Center. We have posted most study data as an open-source R package (Anderson et al. 2020a). We have posted remaining data and code at https:// github.com/geanders/county_hurricane_exposure.
Funding Information:
This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), the Department of Energy (grant no. DE-FG02-08ER64644), and a NASA Applied Sciences Program/Public Health Program Grant (NNX09AV81G). Rainfall data are based on data acquired as part of the mission of the NASA?s Earth Science Division and archived and distributed by the Goddard Earth Sciences Data and Information Services Center. We have posted most study data as an open-source R package (Anderson et al. 2020a). We have posted remaining data and code at https:// github.com/geanders/county_hurricane_exposure.
Publisher Copyright:
© 2020, Public Health Services, US Dept of Health and Human Services. All rights reserved.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - 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, rain-fall, 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.
AB - 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, rain-fall, 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.
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U2 - 10.1289/EHP6976
DO - 10.1289/EHP6976
M3 - Article
C2 - 33112191
AN - SCOPUS:85094864446
VL - 128
SP - 107009-1-107009-14
JO - Environmental Health Perspectives
JF - Environmental Health Perspectives
SN - 0091-6765
IS - 10
ER -