Assessing United States County-Level Exposure for Research on Tropical Cyclones and Human Health.
Assessing United States County-Level Exposure for Research on Tropical Cyclones and Human Health.
复制标题
DOI：
10.1289/ehp6976
复制
发表时间：
2020-10
影响因子：
10.4
通讯作者：
Peng RD
中科院分区：
文献类型：
--
作者：
Anderson GB;Ferreri J;Al-Hamdan M;Crosson W;Schumacher A;Guikema S;Quiring S;Eddelbuettel D;Yan M;Peng RD
可以通过全面和跨时空一致的暴露评估方法推进热带气旋流行病学，因为这些方法有助于多年多风暴研究。此外，了解基于风暴具体危害的暴露指标内部和之间的模式有助于设计热带气旋流行病学研究。a）为流行病学研究提供热带气旋风险评估的开放源数据集;以及B）调查基于不同风暴危害的县级热带气旋风险评估之间的模式和一致性。我们创建了一个开源数据集，其中包含县级数据，这些数据涉及四种热带气旋危害：峰值持续风，降雨，洪水和龙卷风。这些数据涵盖了美国东部所有县的所有登陆或近陆大西洋盆地风暴，涵盖了1996-2011年的所有指标和1988-2018年的具体指标。我们验证了对其他数据源的测量，并调查了基于这些指标的二元暴露分类之间的模式和一致性，以及将它们与风暴轨道的距离进行比较，风暴轨道已被用作一些流行病学研究中暴露的代理。我们的开源数据集通常与其他来源的数据一致，我们提出并讨论了分歧和其他注意事项。在研究期间和研究区域内，热带气旋给不同国家带来的危害不同。因此，在比较不同的特定危害指标之间的暴露评估时，一致性通常较低，就像比较基于距离的代理测量的暴露评估和任何特定危害指标时一样。我们的研究结果提供了一个多灾害的数据集，可以利用流行病学研究的热带气旋，以及见解，可以告知设计和分析热带气旋流行病学研究。https://doi.org/10.1289/EHP6976
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. 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. 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. 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. 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