Goovaerts Pierre, Hermans Thomas, Goossens Peter F, Van De Vijver Ellen
BioMedware, Inc. 167 Little lake dr., Ann Arbor, MI 48103, USA.
Department of Geology, Ghent University, Campus Sterre, Krijgslaan 281, 9000 Ghent, Belgium.
ISPRS Int J Geoinf. 2023 Aug;12(8). doi: 10.3390/ijgi12080328. Epub 2023 Aug 5.
This paper addresses two common challenges in analyzing spatial epidemiological data, specifically disease incidence rates recorded over small areas: filtering noise caused by small local population sizes and deriving estimates at different spatial scales. Geostatistical techniques, including Poisson kriging (PK), have been used to address these issues by accounting for spatial correlation patterns and neighboring observations in smoothing and changing spatial support. However, PK has a limitation in that it can generate unrealistic rates that are either negative or greater than 100%. To overcome this limitation, an alternative method that relies on soft indicator kriging (IK) is presented. The performance of this method is compared to PK using daily COVID-19 incidence rates recorded in 2020-2021 for each of the 581 municipalities in Belgium. Both approaches are used to derive noise-filtered incidence rates for four different dates of the pandemic at the municipality level and at the nodes of a 1 km spacing grid covering the country. The IK approach has several attractive features: (1) the lack of negative kriging estimates, (2) the smaller smoothing effect, and (3) the better agreement with observed municipality-level rates after aggregation, in particular when the original rate was zero.
本文探讨了分析空间流行病学数据时面临的两个常见挑战，特别是在小区域记录的疾病发病率：过滤因当地人口规模小而产生的噪声，以及在不同空间尺度上得出估计值。包括泊松克里金法（PK）在内的地质统计技术已被用于解决这些问题，通过在平滑和改变空间支持时考虑空间相关模式和相邻观测值。然而，PK有一个局限性，即它可能会产生不现实的发病率，要么为负，要么大于100%。为了克服这一局限性，本文提出了一种依赖软指示克里金法（IK）的替代方法。使用2020 - 2021年比利时581个市镇每日记录的新冠肺炎发病率，将该方法的性能与PK进行比较。两种方法都用于在市镇层面以及覆盖该国的间距为1公里的网格节点上，得出大流行四个不同日期的噪声过滤发病率。IK方法有几个吸引人的特点：（1）没有负的克里金估计值，（2）平滑效果较小，（3）汇总后与观测到的市镇层面发病率的一致性更好，特别是当原始发病率为零时。
