Spatial distribution of Escherichia coli O157-positive farms in Scotland

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• 作者：Nils Toft ; Giles T. Innocent ; Iain J. McKendrick ; Helen E. Ternent ; Dominic J. Mellor ; George J. Gunn ; Barti Synge and Stuart W.J. Reid
• 关键词：Standardized morbidity ratio (SMR) ; Relative risk ; Disease mapping ; Bayesian hierarchical models
• 刊名：Preventive Veterinary Medicine
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：71
• 期：1-2
• 页码：45-56
• 全文大小：454 K

文摘

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).