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Rocky Mountain spotted fever in Georgia 1961-75: analysis of social and environmental factors affecting occurrence.

机译:佐治亚州落基山斑疹热1961-75年:分析影响发生的社会和环境因素。

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摘要

For the period of 1961 through 1975, 10 geographic and sociologic variables in each of the 159 counties of Georgia were analyzed to determine how they were correlated with the occurrence of Rocky Mountain spotted fever (RMSF). Combinations of variables were transformed into a smaller number of factors using principal-component analysis. Based upon the relative values of these factors, geographic areas of similarity were delineated by cluster analysis. It was found by use of these analyses that the counties of the State formed four similarity clusters, which we called south, central, lower north and upper north. When the incidence of RMSF was subsequently calculated for each of these regions of similarity, the regions had differing RMSF incidence; low in the south and upper north, moderate in the central, and high in the lower north. The four similarity clusters agreed closely with the incidence of RMSF when both were plotted on a map. Thus, when analyzed simultaneously, the 10 variables selected could be used to predict the occurrence of RMSF. The most important variables were those of climate and geography. Of secondary, but still major importance, were the changes over the 15-year period in variables associated with humans and their environmental alterations. Detailed examination of these factors has permitted quantitative evaluation of the simultaneous impacts of the geographic and sociologic variables on the occurrence of RMSF in Georgia. These analyses could be updated to reflect changes in the relevant variables and tested as a means of identifying new high risk areas for RMSF in the State. More generally, this method might be adapted to clarify our understanding of the relative importance of individual variables in the ecology of other diseases or environmental health problems.
机译:在1961年至1975年期间,对佐治亚州159个县中的每个县的10个地理和社会学变量进行了分析,以确定它们与落基山斑疹热(RMSF)的发生如何相关。使用主成分分析将变量组合转化为较少的因子。根据这些因素的相对价值,通过聚类分析来描述相似的地理区域。通过这些分析发现,国家各县形成了四个相似性集群,我们称其为南方,中部,下北和上北。当随后针对这些相似区域中的每个区域计算RMSF发生率时,这些区域的RMSF发生率有所不同。南部和北部北部较低,中部中等,下部北部较高。当两个相似性聚类都绘制在地图上时,它们与RMSF的发生率非常吻合。因此,当同时分析时,选择的10个变量可用于预测RMSF的发生。最重要的变量是气候和地理变量。其次,但仍然非常重要的是在15年内与人类及其环境变化相关的变量的变化。对这些因素的详细检查使得可以定量评估地理和社会变量对佐治亚州RMSF发生的同时影响。可以更新这些分析以反映相关变量的变化,并进行测试,以识别该州RMSF的新高风险领域。更一般而言,可以采用这种方法来阐明我们对其他疾病生态学或环境健康问题中各个变量的相对重要性的理解。

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