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模拟落基山斑疹热疾病发病率与其传播媒介变异革蜱(美洲犬蜱)栖息地适宜度之间的空间一致性。

Modelling spatial concordance between Rocky Mountain spotted fever disease incidence and habitat probability of its vector Dermacentor variabilis (American dog tick).

作者信息

Atkinson Samuel F, Sarkar Sahotra, Aviña Aldo, Schuermann Jim A, Williamson Phillip

机构信息

Institute of Applied Science, Department of Biological Sciences, University of North Texas, Denton, TX 76203, USA.

出版信息

Geospat Health. 2012 Nov;7(1):91-100. doi: 10.4081/gh.2012.108.

Abstract

The spatial distribution of Dermacentor variabilis, the most commonly identified vector of the bacterium Rickettsia rickettsii which causes Rocky Mountain spotted fever (RMSF) in humans, and the spatial distribution of RMSF, have not been previously studied in the south central United States of America, particularly in Texas. From an epidemiological perspective, one would tend to hypothesise that there would be a high degree of spatial concordance between the habitat suitability for the tick and the incidence of the disease. Both maximum-entropy modelling of the tick's habitat suitability and spatially adaptive filters modelling of the human incidence of RMSF disease provide reliable portrayals of the spatial distributions of these phenomenons. Even though rates of human cases of RMSF in Texas and rates of Dermacentor ticks infected with Rickettsia bacteria are both relatively low in Texas, the best data currently available allows a preliminary indication that the assumption of high levels of spatial concordance would not be correct in Texas (Kappa coefficient of agreement = 0.17). 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.

摘要

变异革蜱是导致人类落基山斑疹热(RMSF)的立氏立克次体最常见的传播媒介,其空间分布以及RMSF的空间分布,此前在美国中南部,尤其是德克萨斯州尚未得到研究。从流行病学角度来看,人们往往会假设蜱虫的栖息地适宜性与疾病发病率之间存在高度的空间一致性。蜱虫栖息地适宜性的最大熵建模以及RMSF疾病人类发病率的空间自适应滤波器建模,都提供了这些现象空间分布的可靠描述。尽管德克萨斯州的人类RMSF病例率和感染立克次体细菌的变异革蜱率都相对较低,但目前可获得的最佳数据初步表明,在德克萨斯州,高度空间一致性的假设并不正确(一致性卡方系数 = 0.17)。需要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。

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