Novel Assessments of the Health Impacts of Tropical Cyclones

项目摘要/摘要 在美国，热带气旋，如飓风和热带风暴， 社会然而，除了一些有限的研究之外，在了解全面的 热带气旋对健康的影响程度。本K99/R 00应用程序的目的是填补这项研究 在这方面，我们对热带气旋对健康的影响进行了几项新的评估。为了实现这一目标， 这种K99/R 00应用是跨学科的，涉及环境流行病学专家的合作， 暴露评估、贝叶斯统计、机器学习、计算机视觉和社会流行病学。K99 阶段的目的是通过课程，导师， 定向阅读，在（1）与气候相关的灾害流行病学和暴露评估方面进行专门培训; (2)先进的贝叶斯统计方法;（3）用于公共卫生的机器学习和计算机视觉; (4)灾害和公共卫生背景下的社会流行病学。在这个奖项获得的技能是至关重要的， 候选人的长期目标是成为一个领先的和方法强大的环境流行病学家 世卫组织进行严格的大规模研究，有助于社会对热带气旋的了解， 其他环境危害，以帮助美国和世界各地的政策。拟建项目 将利用丰富的数据源住院（医疗保险和医疗补助队列）;死亡（国家中心 卫生统计）;热带气旋影响;以及卫星和地面图像，所有这些都跨越几个 近几十年来，覆盖了美国所有遭受热带气旋袭击的地区。目标1（K99阶段）将得到改善 并通过以下方式协调每次命名飓风后过度住院和死亡的估计：（a）应用 将贝叶斯模型集成到住院和死亡数据中，以估计每周住院情况， 如果没有发生飓风，预计的死亡率;然后（B）比较实际的 历史住院率和死亡率，以计算超额住院和死亡。目标2（R 00阶段） 将（a）通过分析确定反复暴露于热带气旋对慢性健康结果的影响 热带气旋暴露与每月住院或死亡之间的关系 时空危害模型;然后（B）通过使用结果准确预测健康影响。目标3（R 00阶段） 将描述物理邻近特征如何解释热带气旋对健康影响的差异， (a)利用机器学习和计算机视觉技术来识别各种物理邻域特征， 使用卫星和街道级图像的热带气旋暴露区域;然后（B）将特征转换为度量， 健康模型，以调查热带气旋对健康的影响是否以及如何根据这些指标变化。拟议 培训和研究计划都与NIEHS的使命和战略计划密切相关，并且响应迅速 NIEHS的数据科学和大数据（主题I，目标7），环境健康差异和 环境正义（专题二，目标4）和新出现的环境健康问题（专题二，目标5）。

PROJECT SUMMARY/ABSTRACT In the United States, tropical cyclones, such as hurricanes and tropical storms, have a devastating impact on society. However, beyond some limited studies, there remains a critical research gap in understanding the full extent of the impact of tropical cyclones on health. The objective of this K99/R00 application is to fill this research gap with several novel assessments of the health impacts of tropical cyclones. To be able to fulfil this objective, this K99/R00 application is interdisciplinary, involving the collaboration of experts in environmental epidemiology, exposure assessment, Bayesian statistics, machine learning, computer vision, and social epidemiology. The K99 phase is designed to augment the candidate's prior research experience through coursework, mentorship, and directed readings, with specific training in (1) climate-related disaster epidemiology and exposure assessment; (2) advanced Bayesian statistics methodology; (3) machine learning and computer vision for public health; and (4) social epidemiology in a disaster and public health context. The skills gained during this award are critical to the candidate's long-term goal to become a leading and methodologically strong environmental epidemiologist who conducts rigorous large-scale research that contributes to society's understanding of tropical cyclones and other environmental hazards to help inform policies in the United States and worldwide. The proposed project will draw on rich data sources on hospitalization (Medicare and Medicaid cohorts); death (National Center for Health Statistics); tropical cyclone exposure; and satellite- and ground-based imagery, all of which span several recent decades and cover all of the United States exposed to tropical cyclones. Aim 1 (K99 phase) will improve and harmonize estimation of excess hospitalizations and deaths after each named hurricane by (a) applying an ensemble of Bayesian models to hospitalization and mortality data to estimate weekly hospitalization and deaths rates that would have been expected had hurricane exposure not occurred; then (b) comparing the actual historical hospitalization and death rates to calculate excess hospitalizations and deaths. Aim 2 (R00 phase) will (a) determine the impact of repeated tropical cyclone exposure on chronic health outcomes by analyzing the association between tropical cyclone exposure and monthly hospitalizations or deaths by applying Bayesian spatio-temporal hazard models; then (b) accurately forecast health impacts by using results. Aim 3 (R00 phase) will characterize how physical neighborhood features explain differences in health impacts of tropical cyclones by (a) utilizing machine learning and computer vision techniques to identify various physical neighborhood features in tropical cyclone-exposed areas using satellite and street-level imagery; then (b) converting features into metrics in health models to investigate if and how health impacts of tropical cyclones vary by those metrics. The proposed training and research program both closely align with NIEHS's mission and Strategic Plan, and is responsive to NIEHS's priorities of Data Science and Big Data (Theme I, Goal 7), Environmental Health Disparities and Environmental Justice (Theme II, Goal 4), and Emerging Environmental Health Issues (Theme II, Goal 5).