远程感测洪水数据集的评估,以估计在风哈维之后与洪水相关的紧急部门访问量
Balaji Ramesh1, Julia M Gohlke2, Benjamin Zaitchik3
1College of Public Health The Ohio State University Columbus OH USA.
GeoHealth
|December 29, 2025
概括
洪水增加了肠道传染病的紧急访问. 结合洪水数据可以更好地识别公共卫生干预的风险,突出需要关注的领域.
科学领域:
- 环境健康 环境健康
- 公共卫生 公共卫生
- 遥感 遥感 遥感 遥感
背景情况:
- 洪水对健康构成重大风险,包括受污染的水和食物引起的传染病.
- 遥感 (RS) 洪水数据有助于识别风险地区,但数据的变化可能会影响干预策略.
研究的目的:
- 评估不同的RS洪水数据集和暴露估计方法如何影响人口普查管 (CT) 洪水和肠道传染病急诊室 (IID-ED) 访问之间的关联.
- 为了确定是否结合RS洪水数据可以改善与洪水相关的健康风险增加的地区的识别.
主要方法:
- 利用两组哈维风洪水数据集,得出了四个暴露变量:土地被洪水淹没的百分比和人口被洪水淹没的百分比.
- 将CT级洪水暴露数据与IID-ED访问数据联系起来,以估计洪水和疾病风险之间的关联.
- 在不同的洪水数据集和暴露指标中比较了影响估计,并评估了结合数据集的影响.
主要成果:
- 土地被洪水增加10%与IID-ED访问风险增加6%有关;人口被洪水增加的百分比没有显著的关联.
- 在这两种洪水数据集或暴露表示方法之间,没有发现影响估计的显著差异.
- 结合洪水数据集改进了模型的合适性,显示在被洪水淹没的CT中,IID-ED访问的风险增加了1.30倍. 不一致的区域也显示出增加的风险.
结论:
- 结合多样化的RS洪水数据集,可以更好地识别洪水相关健康风险较高的地区.
- 这种综合方法可以克服单个数据集的局限性,从而更有效地定位公共卫生干预措施,以减轻洪水影响.
- 准确识别被洪水淹没的地区对于防止不良健康结果和优化洪水事件期间资源分配至关重要.
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