A spatial analysis of power-dependent medical equipment and extreme weather risk in the southeastern United States

A spatial analysis of power-dependent medical equipment and extreme weather risk in the southeastern United States
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DOI:
10.1016/j.ijdrr.2023.103844
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发表时间:
2023-07
影响因子:
5
通讯作者:
Taylin Spurlock;Kelly Sewell;M. Sugg;J. Runkle;R. Mercado;J. Tyson;Jamie Russell
Taylin Spurlock;Kelly Sewell;M. Sugg;J. Runkle;R. Mercado;J. Tyson;Jamie Russell
中科院分区:
地球科学2区
文献类型:
--
作者:
Taylin Spurlock;Kelly Sewell;M. Sugg;J. Runkle;R. Mercado;J. Tyson;Jamie Russell

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极端天气事件危及关键的卫生基础设施,许多人依赖基础设施来满足其基本需求,例如家庭供暖、水和电力医疗设备。本研究的目的是确定由于这些极端天气事件导致的电力中断的空间明确风险人群。为了实现这一目标,我们使用了HHS授权应急计划数据集,该数据集的创建是为了帮助公共卫生当局规划和解决社区的需求。使用地理信息系统(GIS),我们将emPOWER数据与极端天气事件(包括野火、飓风、龙卷风和冰暴)的灾害声明频率叠加在一起。通过我们的分析,我们确定了灾害高发率的脆弱地区,以及沿海社区中依赖电力的耐用医疗设备(DME)。我们还发现,农村地区二甲醚的浓度高于城市地区。此外,我们发现,由于二甲醚个体的高度集中,美国东南部最不受特权经济地区不成比例地容易受到停电的影响。结果将告知公共卫生官员在哪里采取干预措施,以确保在社区一级停电期间对弱势群体的持续护理。
Extreme weather events endanger critical health infrastructure, and many individuals rely on infrastructure to meet their basic needs, such as in-home heating, water, and electric-powered medical devices. The purpose of this study is to identify spatially explicit at-risk populations for power outages due to these extreme weather events. To accomplish this, we used the HHS emPOWER Emergency Planning Dataset, which was created to help public health authorities plan for and address the needs of communities. Using Geographic Information Systems (GIS), we overlay emPOWER data with the frequency of disaster declarations for extreme weather events, including wildfires, hurricanes, tornadoes, and ice storms. Through our analysis, we identified vulnerable areas for high rates of disasters and electricity-dependent durable medical equipment (DME) to be located in communities along the coast. We also found a higher concentration of DME in rural areas compared to urban areas. In addition, we found least privileged economic locations are disproportionately vulnerable to power outages in the southeastern United States due to their high concentration of DME individuals. Results will inform public health officials where to target interventions to ensure continuity of care for vulnerable populations during power outages at the community level.