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首页> 外文期刊>Italian Journal of Public Health >Social vulnerability and Lyme disease incidence: a regional analysis of the United States, 2000-2014
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Social vulnerability and Lyme disease incidence: a regional analysis of the United States, 2000-2014

机译:社会脆弱性和莱姆病发病率:2000-2014年美国的区域分析

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摘要

Background : Lyme disease (LD), which is highly preventable communicable illness, is the most commonly reported vector borne disease in the USA. The Social Vulnerability Index (SoVI) is a county level measure of SES and vulnerability to environmental hazards or disease outbreaks, but has not yet been used in the study of LD. The purpose of this study was to determine if a relationship existed between the SoVI and LD incidence at the national level and regional division level in the United States between 2000 and 2014. Methods : County level LD data were downloaded from the CDC. County level SoVI were downloaded from the HVRI at the University of South Carolina and the CDC. Data were sorted into regional divisions as per the US Census Bureau and condense into three time intervals, 2000-2004, 2005-2009, and 2010-2014. QGIS was utilized to visually represent the data. Logarithmic OLS regression models were computed to determine the predictive power of the SoVI in LD incidence rates. Results : LD incidence was greatest in the Northeastern and upper Midwestern regions of the USA. The results of the regression analyses showed that SoVI exhibited a significant quadratic relationship with LD incidence rates at the national level. Conclusion : Our results showed that counties with the highest and lowest social vulnerability were at greatest risk for LD. The SoVI may be a useful risk assessment tool for public health practitioners within the context of LD control.
机译:背景:莱姆病(LD)是高度可预防的传染病,是美国最常报道的媒介传播疾病。社会脆弱性指数(SoVI)是县级对SES的评估以及对环境危害或疾病暴发的脆弱性,但尚未用于LD的研究中。这项研究的目的是确定在2000年至2014年间,美国在国家层面和地区划分层面上的SoVI与LD发病率之间是否存在关系。方法:从CDC下载县级LD数据。从南卡罗来纳大学和CDC的HVRI下载了县级的SoVI。根据美国人口普查局将数据分类为区域划分,并压缩为三个时间间隔,即2000-2004年,2005-2009年和2010-2014年。 QGIS被用来可视化地表示数据。计算对数OLS回归模型以确定SoVI在LD发生率中的预测能力。结果:LD发生率在美国东北部和中西部地区最高。回归分析的结果表明,SoVI与国家一级的LD发生率呈显着的二次关系。结论:我们的结果表明,社会脆弱性最高和最低的县遭受LD的风险最高。在LD控制的背景下,SoVI可能是公共卫生从业人员有用的风险评估工具。

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