International Journal of Health Geographics Geostatistical Analysis of Disease Data: Accounting for Spatial Support and Population Density in the Isopleth Mapping of Cancer Mortality Risk Using Area-to-point Poisson Kriging
International Journal of Health Geographics Geostatistical Analysis of Disease Data: Accounting for Spatial Support and Population Density in the Isopleth Mapping of Cancer Mortality Risk Using Area-to-point Poisson Kriging
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通讯作者：
P. Goovaerts
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作者：
P. Goovaerts
背景：最近开发了地统计技术，在过滤癌症死亡率等值线图时考虑了空间变化的人口规模和空间模式。它们的实施得益于所有地理单元都具有相同大小和形状的初始假设，这允许在半变异函数估计和克里金法中使用地理质心。另一个隐含的假设是，面临风险的人口均匀分布在每个单位内。本文提出了泊松克里金法的推广，其中行政单位的大小和形状以及人口密度被纳入噪声死亡率的过滤和等值线风险图的创建中。还提出了一种从聚合率（即面积数据）推断风险的点支持半变异函数的创新程序。
Background: Geostatistical techniques that account for spatially varying population sizes and spatial patterns in the filtering of choropleth maps of cancer mortality were recently developed. Their implementation was facilitated by the initial assumption that all geographical units are the same size and shape, which allowed the use of geographic centroids in semivariogram estimation and kriging. Another implicit assumption was that the population at risk is uniformly distributed within each unit. This paper presents a generalization of Poisson kriging whereby the size and shape of administrative units, as well as the population density, is incorporated into the filtering of noisy mortality rates and the creation of isopleth risk maps. An innovative procedure to infer the point-support semivariogram of the risk from aggregated rates (i.e. areal data) is also proposed.