Toft Nils, Innocent Giles T, McKendrick Iain J, Ternent Helen E, Mellor Dominic J, Gunn George J, Synge Barti, Reid Stuart W J
Department of Large Animal Sciences, The Royal Veterinary and Agricultural University, Grønnegårdsvej 8, DK-1870 Frederiksberg C, Denmark.
Prev Vet Med. 2005 Sep 30;71(1-2):45-56. doi: 10.1016/j.prevetmed.2005.05.010.
Using a sample of 949 Scottish farms with finishing cattle, the spatial distribution of Escherichia coli O157-positive farms was investigated using disease mapping models. The overall prevalence of E. coli O157-positive farms was estimated as 22%. The regions used in this study were the 16 postcode areas of Scotland. For each region, the posterior relative risk (RR) was estimated as a model-based alternative to the saturated standardized morbidity ratio (SMR), i.e., the ratio between observed and expected cases in a region. Three Bayesian hierarchical models with generalized linear modeling of the area-specific risks were used to estimate the posterior relative risk of E. coli O157-positive farms in the postcode areas: a random-effects model incorporating only spatially uncorrelated heterogeneity; a model incorporating both spatially correlated and uncorrelated heterogeneity; and a pseudo-mixture model with unstructured correlation and a weighted mix of two variance components representing the spatial correlation and a jump structure. None of the models identified any areas with a significant increase or decrease in risk. The deviance information criteria slightly favored the simplest model (RR range: 0.92--1.09). However, this model appeared to smooth out more of the variation in the RR compared to the pseudo-mixture model, which gave a more informative pattern of the posterior relative risks (range: 0.81--1.22).
利用949个有育肥牛的苏格兰农场样本，使用疾病地图模型研究了大肠杆菌O157阳性农场的空间分布。估计大肠杆菌O157阳性农场的总体患病率为22%。本研究使用的区域是苏格兰的16个邮政编码区。对于每个区域，估计后验相对风险（RR），作为基于模型的饱和标准化发病比（SMR）的替代指标，即一个区域内观察到的病例数与预期病例数之比。使用三个具有区域特定风险广义线性模型的贝叶斯分层模型来估计邮政编码区内大肠杆菌O157阳性农场的后验相对风险：一个仅纳入空间不相关异质性的随机效应模型；一个同时纳入空间相关和不相关异质性的模型；以及一个具有非结构化相关性和两个方差分量加权混合的伪混合模型，这两个方差分量分别代表空间相关性和跳跃结构。没有一个模型识别出风险显著增加或降低的区域。偏差信息准则略微倾向于最简单的模型（RR范围：0.92 - 1.09）。然而，与伪混合模型相比，该模型似乎平滑了RR中的更多变异，伪混合模型给出了更具信息性的后验相对风险模式（范围：0.81 - 1.22）。
