Beyea J
Consulting in the Public Interest, Lambertville, NJ 08530, USA.
Environ Health Perspect. 1999 Feb;107 Suppl 1(Suppl 1):181-90. doi: 10.1289/ehp.99107s1181.
Geographic modeling of individual exposures using air pollution modeling techniques can help in both the design of environmental epidemiologic studies and in the assignment of measures that delineate regions that receive the highest exposure in space and time. Geographic modeling can help in the interpretation of environmental sampling data associated with airborne concentration or deposition, and can act as a sophisticated interpolator for such data, allowing values to be assigned to locations between points where the data have actually been collected. Recent advances allow for quantification of the uncertainty in a geographic model and the resulting impact on estimates of association, variability, and study power. In this paper we present the terminology and methodology of geographic modeling, describe applications to date in the field of epidemiology, and evaluate the potential of this relatively new tool.
使用空气污染建模技术对个体暴露进行地理建模,有助于环境流行病学研究的设计,也有助于确定在空间和时间上暴露量最高区域的措施分配。地理建模有助于解释与空气传播浓度或沉降相关的环境采样数据,并可作为此类数据的精密插值工具,从而能够将这些数据值分配到实际收集数据的点之间的位置。最新进展使得能够对地理模型中的不确定性及其对关联估计、变异性和研究效能的影响进行量化。在本文中,我们介绍了地理建模的术语和方法,描述了其在流行病学领域的应用现状,并评估了这一相对较新工具的潜力。