A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.
A climate-based model predicts the spatial distribution of the Lyme disease vector Ixodes scapularis in the United States.
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DOI：
10.1289/ehp.6052
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发表时间：
2003-07
影响因子：
10.4
通讯作者：
Fish D
中科院分区：
文献类型：
--
作者：
Brownstein JS;Holford TR;Fish D
在美国大部分地区，对黑腿硬蜱空间分布的了解是评估人类患莱姆病风险的基本组成部分。尽管美国存在县级病媒分布图，但其准确性受到其报告存在的任意类别的限制。目前尚不清楚报告的阳性区域是否能够支持已确定的人口，以及阴性区域是否适合已确定的人口。在美国，肩鳍金枪鱼的分布范围不断扩大，这表明目前并没有占据所有合适的栖息地。因此，我们开发了一个空间预测的模型，在48个相邻的状态下，肩胛肌，以改进以前的媒介分布图。我们使用地面观测的环境数据来预测已建立的肩胛虫种群的概率。自体分析表明，最高、最低和平均温度以及水汽压对种群维持有显著贡献，准确率为95%(p<；0.0001)。通过敏感度分析得到生境适宜性的截止概率，并利用该概率对原分布图进行重新分类。肩关节存在与大规模环境数据之间的空间建模关系提供了一个稳健的适宜性模型，该模型揭示了栖息地适宜性的基本环境决定因素，预测了莱姆病风险的新兴区域，并生成了全美肩肩关节的未来模式。
An understanding of the spatial distribution of the black-legged tick, Ixodes scapularis, is a fundamental component in assessing human risk for Lyme disease in much of the United States. Although a county-level vector distribution map exists for the United States, its accuracy is limited by arbitrary categories of its reported presence. It is unknown whether reported positive areas can support established populations and whether negative areas are suitable for established populations. The steadily increasing range of I. scapularis in the United States suggests that all suitable habitats are not currently occupied. Therefore, we developed a spatially predictive logistic model for I. scapularis in the 48 conterminous states to improve the previous vector distribution map. We used ground-observed environmental data to predict the probability of established I. scapularis populations. The autologistic analysis showed that maximum, minimum, and mean temperatures as well as vapor pressure significantly contribute to population maintenance with an accuracy of 95% (p < 0.0001). A cutoff probability for habitat suitability was assessed by sensitivity analysis and was used to reclassify the previous distribution map. The spatially modeled relationship between I. scapularis presence and large-scale environmental data provides a robust suitability model that reveals essential environmental determinants of habitat suitability, predicts emerging areas of Lyme disease risk, and generates the future pattern of I. scapularis across the United States.
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影响因子：
5
作者：
Kitron, U;Kazmierczak, JJ
通讯作者：
Kazmierczak, JJ
影响因子：
2.1
作者：
Dohm, DJ;Rowton, ED;Turell, MJ
通讯作者：
Turell, MJ
影响因子：
2.1
作者：
DANIELS, TJ;FISH, D;LAPOINTE, DA
通讯作者：
LAPOINTE, DA
影响因子：
3.9
作者：
Cumming, GS
通讯作者：
Cumming, GS
影响因子：
2.1
作者：
DesVignes, F;Fish, D
通讯作者：
Fish, D