Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Ave, Boston, MA, USA.
Department of Statistics, Harvard University, 1 Oxford St, Cambridge, MA, USA.
Biostatistics. 2023 Apr 14;24(2):449-464. doi: 10.1093/biostatistics/kxab047.
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 how TC meteorological features and socioeconomic/demographic characteristics of impacted communities are associated with health impacts. We apply it to a rich data platform containing detailed historic TC exposure information and records of all-cause mortality and cardiovascular- and respiratory-related hospitalization among Medicare recipients. We report a high degree of heterogeneity in the acute health impacts of historic TCs, both within and across TCs, and, on average, substantial TC-attributable increases in respiratory hospitalizations. TC-sustained windspeeds are found to be the primary driver of mortality and respiratory risks.
战略准备可以减轻飓风和热带风暴（统称为热带气旋，TCs）对健康的不利影响，但通过更全面和严格的 TC 流行病学特征描述，可以增强其保护作用。为了为高精度 TC 准备提供必要的见解和工具，我们引入了一种机器学习方法，该方法可标准化估算历史 TC 健康影响，发现这些健康影响中的常见模式和异质性来源，并能够确定未来 TC 中健康风险最高的社区。该模型集成了（i）因果推断组件，以量化近期历史 TCs 在高空间分辨率下对健康的直接影响，以及（ii）预测组件，用于捕获受影响社区的 TC 气象特征和社会经济/人口统计学特征与健康影响之间的关系。我们将其应用于一个包含详细历史 TC 暴露信息以及 Medicare 受助人全因死亡率和心血管及呼吸道相关住院记录的丰富数据平台。我们报告了历史 TCs 急性健康影响存在高度异质性，无论是在 TCs 内部还是在 TCs 之间，而且平均而言，呼吸道住院人数会大幅增加。TC 持续风速被发现是死亡和呼吸道风险的主要驱动因素。
