Atkinson Samuel F, Sarkar Sahotra, Aviña Aldo, Schuermann Jim A, Williamson Phillip
Institute of Applied Science, Department of Biological Sciences, University of North Texas, Denton, USA.
Integrative Biology and Philosophy, University of Texas, Austin, USA.
Geospat Health. 2014 Nov;9(1):203-12. doi: 10.4081/gh.2014.17.
The spatial distribution of Ixodes scapularis, the most common tick vector of the bacterium Borrelia burgdorferi, the cause of Lyme disease in humans, has not been studied previously in Texas, United States of America. It has only rarely been reported in this state, so its local, spatial relationship to the distribution of this disease is unknown. From an epidemiological perspective, one would tend to hypothesise that there should be a high degree of spatial concordance between habitat suitability for the tick and incidence of the disease. Both maximum-entropy modelling of the tick's habitat probability and modelling of human incidence of Lyme disease using spatially adaptive filters provide reliable portrayals of the spatial distributions of these phenomena. Even though rates of human cases of Lyme disease as well as rates of Ixodes ticks infected with Borrelia bacteria are both relatively low in Texas, the best data currently available indicate that the assumption of high levels of spatial concordance would not be correct in Texas (Kappa coefficient of agreement = 0.039). It will take substantially more data to provide conclusive findings and to understand the results reported here, but this study provides an approach to begin understanding the discrepancy.
肩突硬蜱是导致人类莱姆病的伯氏疏螺旋体最常见的蜱虫传播媒介，此前在美国得克萨斯州尚未对其空间分布进行过研究。该蜱虫在该州仅有极少的报道，因此其与这种疾病分布的局部空间关系尚不清楚。从流行病学角度来看，人们倾向于推测蜱虫适宜栖息地与疾病发病率之间应该存在高度的空间一致性。蜱虫栖息地概率的最大熵建模以及使用空间自适应滤波器对人类莱姆病发病率的建模，都能可靠地描绘这些现象的空间分布。尽管在得克萨斯州人类莱姆病病例率以及感染伯氏疏螺旋体的肩突硬蜱率都相对较低，但目前可得的最佳数据表明，在得克萨斯州，高度空间一致性的假设并不正确（一致性卡方系数 = 0.039）。需要大量更多的数据才能得出确凿的结论并理解此处报告的结果，但本研究提供了一种开始理解这种差异的方法。
