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威斯康星州莱姆病分布的空间分析。

Spatial analysis of the distribution of Lyme disease in Wisconsin.

作者信息

Kitron U, Kazmierczak J J

机构信息

College of Veterinary Medicine, University of Illinois, Urbana 61801, USA.

出版信息

Am J Epidemiol. 1997 Mar 15;145(6):558-66. doi: 10.1093/oxfordjournals.aje.a009145.

DOI:10.1093/oxfordjournals.aje.a009145
PMID:9063347
Abstract

Surveillance measures for human cases of Lyme disease in Wisconsin were compared and associated with tick distribution and vegetation coverage. During 1991-1994, 1,759 confirmed human cases of Lyme disease reported to the Wisconsin Division of Health were assigned a county of residence, but only 329 (19%) could be assigned with certainty a county of exposure. Distributions of cases by county of exposure and residence were often consistent from year to year. Tick distribution in 46 of 72 Wisconsin counties was mapped based on collections by researchers, statewide surveys of infested deer, and submissions from the public. Satellite data were used to calculate a normalized difference vegetation index (NDVI) for each county. A geographic information system (GIS) was used to map distributions of human Lyme disease cases, ticks, and degree of vegetation cover. Human case distribution by county of exposure was significantly correlated with tick distribution; both were positively correlated with high NDVI values in spring and fall, when wooded vegetation could be distinguished from agricultural crops in the satellite image. Statistical analysis of spatial patterns using a measure of spatial autocorrelation indicated that counties with most human cases and ticks were clustered in parts of western Wisconsin. A map delineating the counties with highest risk for Lyme disease transmission was generated based on numbers of exposed human cases and tick concentrations.

摘要

对威斯康星州莱姆病人类病例的监测措施进行了比较,并与蜱虫分布和植被覆盖情况相关联。在1991年至1994年期间,向威斯康星州卫生部报告的1759例确诊莱姆病人类病例被指定了居住县,但只有329例(19%)能够确定暴露县。按暴露县和居住县划分的病例分布每年通常是一致的。基于研究人员的采集、全州范围内对受感染鹿的调查以及公众提交的数据,绘制了威斯康星州72个县中46个县的蜱虫分布图。利用卫星数据计算了每个县的归一化植被指数(NDVI)。使用地理信息系统(GIS)绘制了人类莱姆病病例、蜱虫和植被覆盖程度的分布图。按暴露县划分的人类病例分布与蜱虫分布显著相关;在春季和秋季,当卫星图像中可以区分树木植被和农作物时,两者均与高NDVI值呈正相关。使用空间自相关度量对空间模式进行的统计分析表明,人类病例和蜱虫最多的县集中在威斯康星州西部的部分地区。根据暴露人类病例数量和蜱虫浓度绘制了一张描绘莱姆病传播风险最高的县的地图。

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