Geospatial Imprecision With Constraints for Precision Public Health: Algorithm Development and Validation.

Daniel Harris, Chris Delcher
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Abstract

Background: Location and environmental social determinants of health are increasingly important factors in both an individual's health and the monitoring of community-level public health issues.

Objective: We aimed to measure the extent to which location obfuscation techniques, designed to protect an individual's privacy, can unintentionally shift geographical coordinates into neighborhoods with significantly different socioeconomic demographics, which limits the precision of findings for public health stakeholders.

Methods: Point obfuscation techniques intentionally blur geographic coordinates to conceal the original location. The pinwheel obfuscation method is an existing technique in which a point is moved along a pinwheel-like path given a randomly chosen angle and a maximum radius; we evaluate the impact of this technique using 2 data sets by comparing the demographics of the original point and the resulting shifted point by cross-referencing data from the United States Census Bureau.

Results: Using poverty measures showed that points from regions of low poverty may be shifted to regions of high poverty; similarly, points in regions with high poverty may be shifted into regions of low poverty. We varied the maximum allowable obfuscation radius; the mean difference in poverty rate before and after obfuscation ranged from 6.5% to 11.7%. Additionally, obfuscation inadvertently caused false hot spots for deaths by suicide in Cook County, Illinois.

Conclusions: Privacy concerns require patient locations to be imprecise to protect against risk of identification; precision public health requires accuracy. We propose a modified obfuscation technique that is constrained to generate a new point within a specified census-designated region to preserve both privacy and analytical accuracy by avoiding demographic shifts.

精确公共卫生的地理空间不精确性约束:算法开发与验证。
背景:位置和环境决定健康的社会因素在个人健康和社区公共卫生问题监测中日益成为重要因素:我们旨在测量为保护个人隐私而设计的位置混淆技术在多大程度上会无意中将地理坐标转移到社会经济人口统计学差异显著的社区,从而限制了公共卫生利益相关者调查结果的精确性:点混淆技术有意模糊地理坐标以掩盖原始位置。风车混淆法是一种现有技术,在该技术中,一个点会沿着风车状路径移动,并随机选择一个角度和最大半径;我们使用两个数据集评估了该技术的影响,通过交叉引用美国人口普查局的数据,比较了原始点和移动后的点的人口统计数据:使用贫困度量表明,低贫困地区的点可能会被转移到高贫困地区;同样,高贫困地区的点也可能会被转移到低贫困地区。我们改变了允许的最大混淆半径;混淆前后贫困率的平均差异从 6.5% 到 11.7% 不等。此外,在伊利诺伊州库克县,模糊处理无意中造成了自杀死亡的错误热点:结论:出于对隐私的考虑,病人的位置需要不精确,以防被识别的风险;而精确的公共卫生则需要准确性。我们提出了一种改进的混淆技术,该技术受限于在指定的人口普查区域内生成一个新点,从而通过避免人口变化来保护隐私和分析准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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