Stevens Kim B, Jepson Rosanne, Holm Laura Phillipa, Walker David John, Cardwell Jacqueline Martina
Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK.
Kimene Analytics Ltd, London, UK.
Vet Rec. 2018 Oct 27;183(16):502. doi: 10.1136/vr.104892. Epub 2018 Aug 27.
The annual outbreaks of cutaneous and renal glomerular vasculopathy (CRGV) reported in UK dogs display a distinct seasonal pattern (November to May) suggesting possible climatic drivers of the disease. The objectives of this study were to explore disease clustering and identify associations between agroecological factors and CRGV occurrence. Kernel-smoothed maps were generated to show the annual reporting distribution of CRGV, Kuldorff's space-time permutation statistic used to identify significant spatiotemporal case clusters and a boosted regression tree model developed to quantify associations between CRGV case locations and a range of agroecological factors. The majority of diagnoses (92 per cent) were reported between November and May while the number of regions reporting the disease increased between 2012 and 2017. Two significant spatiotemporal clusters were identified-one in the New Forest during February and March 2013, and one adjacent to it (April 2015 to May 2017)-showing significantly higher and lower proportions of cases than the rest of the UK, respectively, for the indicated time periods. A moderately significant high-risk cluster (P=0.087) was also identified in the Manchester area of northern England between February and April 2014. Habitat was the predictor with the highest relative contribution to CRGV distribution (20.3 per cent). Cases were generally associated with woodlands, increasing mean maximum temperatures in winter, spring and autumn, increasing mean rainfall in winter and spring and decreasing cattle and sheep density. Understanding of such factors may help develop causal models for CRGV occurrence.
英国犬类中每年报告的皮肤和肾小球血管病(CRGV)暴发呈现出明显的季节性模式(11月至次年5月),这表明该病可能受气候因素驱动。本研究的目的是探讨疾病聚集情况,并确定农业生态因素与CRGV发生之间的关联。生成核平滑地图以显示CRGV的年度报告分布,使用库尔道夫时空置换统计量来识别显著的时空病例聚集,并开发了一个增强回归树模型来量化CRGV病例地点与一系列农业生态因素之间的关联。大多数诊断(92%)报告于11月至5月,而报告该病的地区数量在2012年至2017年期间有所增加。确定了两个显著的时空聚集——一个在2013年2月和3月的新森林地区,另一个与之相邻(2015年4月至2017年5月)——在指定时间段内,这两个聚集区的病例比例分别显著高于和低于英国其他地区。2014年2月至4月期间,在英格兰北部的曼彻斯特地区还发现了一个中等显著的高风险聚集区(P=0.087)。栖息地是对CRGV分布贡献相对最大的预测因子(20.3%)。病例通常与林地有关,冬季、春季和秋季的平均最高气温升高,冬季和春季的平均降雨量增加,牛羊密度降低。了解这些因素可能有助于建立CRGV发生的因果模型。