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Zip4 码在空间流行病学分析中的应用。

The utility of Zip4 codes in spatial epidemiological analysis.

机构信息

GIS Health & Hazards Lab, Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, Ohio, United States of America.

出版信息

PLoS One. 2023 May 31;18(5):e0285552. doi: 10.1371/journal.pone.0285552. eCollection 2023.

Abstract

There are many public health situations within the United States that require fine geographical scale data to effectively inform response and intervention strategies. However, a condition for accessing and analyzing such data, especially when multiple institutions are involved, is being able to preserve a degree of spatial privacy and confidentiality. Hospitals and state health departments, who are generally the custodians of these fine-scale health data, are sometimes understandably hesitant to collaborate with each other due to these concerns. This paper looks at the utility and pitfalls of using Zip4 codes, a data layer often included as it is believed to be "safe", as a source for sharing fine-scale spatial health data that enables privacy preservation while maintaining a suitable precision for spatial analysis. While the Zip4 is widely supplied, researchers seldom utilize it. Nor is its spatial characteristics known by data guardians. To address this gap, we use the context of a near-real time spatial response to an emerging health threat to show how the Zip4 aggregation preserves an underlying spatial structure making it potentially suitable dataset for analysis. Our results suggest that based on the density of urbanization, Zip4 centroids are within 150 meters of the real location almost 99% of the time. Spatial analysis experiments performed on these Zip4 data suggest a far more insightful geographic output than if using more commonly used aggregation units such as street lines and census block groups. However, this improvement in analytical output comes at a spatial privy cost as Zip4 centroids have a higher potential of compromising spatial anonymity with 73% of addresses having a spatial k anonymity value less than 5 when compared to other aggregations. We conclude that while offers an exciting opportunity to share data between organizations, researchers and analysts need to be made aware of the potential for serious confidentiality violations.

摘要

美国有许多公共卫生状况需要精细的地理尺度数据来有效地为应对策略和干预措施提供信息。然而,获取和分析这些数据的一个条件是,特别是当涉及多个机构时,能够保持一定程度的空间隐私和保密性。医院和州卫生部门通常是这些精细卫生数据的保管者,由于这些担忧,他们有时会出于理解而不愿意相互合作。本文探讨了使用 Zip4 代码(通常被认为是“安全”的数据层)作为共享精细空间卫生数据的来源的效用和陷阱,这种方法可以在保留隐私的同时为空间分析提供适当的精度。虽然 Zip4 代码被广泛提供,但研究人员很少使用它。数据保管者也不知道其空间特征。为了解决这一差距,我们使用了一个实时空间响应新兴健康威胁的案例,展示了 Zip4 聚合如何保留潜在的空间结构,使其成为适合分析的潜在数据集。我们的结果表明,基于城市化密度,Zip4 质心几乎 99%的时间都在真实位置的 150 米以内。对这些 Zip4 数据进行的空间分析实验表明,与使用更常用的聚合单位(如街道线和人口普查块组)相比,地理输出更具洞察力。然而,这种分析输出的改进是以空间隐私为代价的,因为与其他聚合相比,Zip4 质心在空间匿名方面存在更高的潜在风险,当与其他聚合相比时,73%的地址的空间 k 匿名值小于 5。我们得出的结论是,虽然提供了在组织之间共享数据的令人兴奋的机会,但研究人员和分析师需要意识到严重的机密性违规的潜在可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b53/10231782/444c490a58ba/pone.0285552.g001.jpg

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