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

机译:利用居住点和工作场所地理空间信息进行空间点模式分析以定位潜在爆发源的实用程序

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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:确定爆发源有助于控制爆发。由于涉及到的复杂性(例如,需要额外参数选择的方法),性能不完善以及对现有选项缺乏信心,因此在爆发调查中未将空间方法最佳地使用。我们模拟了30次模拟爆发,并比较了5种简单的方法,这些方法不需要参数选择,但可以在模拟案例的住所和工作地点之间进行选择,以定位来源。每种场所都有独特的空间分布;居住地和工作地点的地址分别在视觉上和统计上聚集在居住区和市中心附近,这表明工作地点的价值与爆发地点可能相关。我们提出的对人口学统计数据的修改(使用地址选择的最小几何距离的中心)在将工作场所与居民住址结合使用的几乎所有情况下都能够将模拟爆发源定位在半径500 m以内。在敏感性分析中,当获得足够的工作场所数据时,该方法在只有10个案例的各种情况下效果良好。将其应用于过去的暴发也很成功,除了常见食品供应商的多地点暴发。

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