Goldberg Daniel W, Cockburn Myles G
University of Southern California, Spatial Sciences Institute, Los Angeles, CA, USA.
Spat Spatiotemporal Epidemiol. 2012 Apr;3(1):39-54. doi: 10.1016/j.sste.2012.02.005. Epub 2012 Feb 10.
Geocoding is often used to produce maps of disease rates from the diagnosis addresses of incident cases to assist with disease surveillance, prevention, and control. In this process, diagnosis addresses are converted into latitude/longitude pairs which are then aggregated to produce rates at varying geographic scales such as Census tracts, neighborhoods, cities, counties, and states. The specific techniques used within geocoding systems have an impact on where the output geocode is located and can therefore have an effect on the derivation of disease rates at different geographic aggregations. This paper investigates how county-level cancer rates are affected by the choice of interpolation method when case data are geocoded to the ZIP code level. Four commonly used areal unit interpolation techniques are applied and the output of each is used to compute crude county-level five-year incidence rates of all cancers in California. We found that the rates observed for 44 out of the 58 counties in California vary based on which interpolation method is used, with rates in some counties increasing by nearly 400% between interpolation methods.
地理编码常用于根据新发病例的诊断地址生成疾病发病率地图，以协助疾病监测、预防和控制。在此过程中，诊断地址被转换为经纬度对，然后进行汇总，以生成不同地理尺度（如普查区、社区、城市、县和州）的发病率。地理编码系统中使用的具体技术会影响输出地理编码的位置，因此可能会对不同地理聚合层面疾病发病率的推导产生影响。本文研究了当病例数据被地理编码到邮政编码级别时，插值方法的选择如何影响县级癌症发病率。应用了四种常用的面元插值技术，并使用每种技术的输出结果计算加利福尼亚州所有癌症的县级粗五年发病率。我们发现，加利福尼亚州58个县中的44个县观察到的发病率因所使用的插值方法而异，某些县的发病率在不同插值方法之间增加了近400%。
