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Utility of Spatial Point-Pattern Analysis Using Residential and Workplace Geospatial Information to Localize Potential Outbreak Sources

机译:使用住宅和工作场所地理空间信息来定位潜在爆发来源的空间点图案分析的效用

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摘要

Identifying the source of an outbreak facilitates its control. Spatial methods are not optimally used in outbreak investigation, due to a mix of the complexities involved (e.g., methods requiring additional parameter selection), imperfect performance, and lack of confidence in existing options. We simulated 30 mock outbreaks and compared 5 simple methods that do not require parameter selection but could select between mock cases' residential and workplace addresses to localize the source. Each category of site had a unique spatial distribution; residential and workplace address were visually and statistically clustered around the residential neighborhood and city center sites respectively, suggesting that the value of workplace addresses is tied to the location where an outbreak might originate. A modification to centrographic statistics that we propose-the center of minimum geometric distance with address selection-was able to localize the mock outbreak source to within a 500 m radius in almost all instances when using workplace in combination with residential addresses. In the sensitivity analysis, when given sufficient workplace data, the method performed well in various scenarios with only 10 cases. It was also successful when applied to past outbreaks, except for a multisite outbreak from a common food supplier.
机译:确定爆发的来源有助于其控制权。由于涉及的复杂性混合(例如,需要额外参数选择的方法),不完美的性能,并且对现有选项缺乏信心,因此由于涉及的复杂性(例如,需要额外参数选择的方法),因此,空间方法在爆发调查中不可用于爆发调查。我们模拟了30模拟爆发,并比较了5个不需要参数选择的简单方法,但可以在模拟案例的住宅和工作场所地址之间进行定位来定位源。每个场地都有独特的空间分布;住宅和工作场所地址分别在居住街区和市中心站点围绕住宅和统计群集,表明工作场所地址的价值与爆发可能发起的位置绑定。对Firegrographic统计数据的修改 - 我们提出的 - 与地址选择的最小几何距离中心 - 在使用与住宅地址的组合使用工作场所时,几乎所有实例都能够将模拟爆发源本质化到500米半径内。在敏感性分析中,当给定足够的工作场所数据时,该方法在各种场景中表现良好,只有10例。在应用于过去的爆发时也是成功的,除了普通食品供应商的多路疫情。

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