Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Republic of Singapore.
Environmental Health Institute, National Environment Agency, Singapore, Republic of Singapore.
Am J Epidemiol. 2019 May 1;188(5):940-949. doi: 10.1093/aje/kwy290.
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.
确定疫情源头有助于疫情的控制。由于涉及到各种复杂因素（例如，需要额外参数选择的方法）、方法性能不完善以及对现有选择缺乏信心等原因，空间方法在疫情调查中并没有得到最佳利用。我们模拟了 30 个模拟疫情，并比较了 5 种不需要参数选择但可以在模拟病例的居住地址和工作场所地址之间进行选择的简单方法，以确定源头位置。每个地点类别都有独特的空间分布；居住地址和工作场所地址分别围绕居住社区和市中心地点呈视觉和统计聚类，这表明工作场所地址的价值与疫情可能起源的位置有关。我们提出的一种对重心统计数据的修改——带有地址选择的最小几何距离中心——在使用工作场所地址和居住地址的情况下，几乎可以在所有情况下将模拟疫情的源头定位在 500 米半径内。在敏感性分析中，当有足够的工作场所数据时，该方法在只有 10 个病例的各种场景中表现良好。该方法在过去的疫情中也取得了成功，除了一个来自共同食品供应商的多地点疫情。
