Geolocation uncertainty is common in epidemiological studies that depend on addresses to determine exposure. We developed a spatial construct and statistical framework by which to characterize geolocation uncertainty, develop analysis methods, and compare those methods. Exposure is represented by a three-dimensional step function over the partitioned spatial surface and a person’s geolocation boundary is defined as the union of partition elements that cover the possible index location. Disease rates are defined by exposures from the partitioned surface. Standard process theory was used for analytic results and an empirical evaluation computer simulation method was used to compare methods. A case-control study of pesticide exposure and childhood cancer was used to illustrate the problem. Pesticide exposure was derived from geolocations determined from birth residences, where about half the reference addresses resolved to ZIP Codes while the rest resolve to smaller areas. We found that the centroid method has much worse power (0.35) to detect pesticide–disease effects than using either whole area proportion exposed (0.52) or when using an induced intensity approach (0.79). The latter approach properly accounted for the geolocation uncertainty even if only ZIP Code address information was used. ZIP Code address data had twice the variance compared to using the actual geolocation boundaries which had twice the variance compared to if there were no geolocation uncertainty. Our area based analytic approach confirms that geolocation ambiguity should be considered in the context of exposure–disease investigations that rely on address data for determining exposure.

地理定位不确定性在流行病学研究中很常见，这些研究依赖于地址来确定暴露。我们开发了一个空间构造和统计框架，通过它来表征地理定位的不确定性、开发分析方法并比较这些方法。曝光由分区空间表面上的三维阶跃函数表示，并且一个人的地理位置边界被定义为覆盖可能索引位置的分区元素的联合。疾病率由来自分区表面的暴露定义。标准过程理论用于分析结果，并使用经验评估计算机模拟方法来比较方法。一项关于农药暴露和儿童癌症的病例对照研究被用来说明这个问题。农药暴露来自出生住所确定的地理位置，其中大约一半的参考地址解析为邮政编码，而其余的解析为较小的区域。我们发现，与使用暴露的整个面积比例 (0.52) 或使用诱导强度方法 (0.79) 相比，质心方法检测农药-疾病影响的功效要差得多 (0.35)。即使仅使用邮政编码地址信息，后一种方法也正确地考虑了地理定位的不确定性。邮政编码地址数据的方差是使用实际地理定位边界的两倍，而实际地理定位边界的方差是没有地理定位不确定性的两倍。