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2000 - 2008年美国境内西尼罗河病毒分布的时间变化

Temporal Variations in the Distribution of West Nile Virus Within the United States; 2000-2008.

作者信息

Carnes Alexander, Ogneva-Himmelberger Yelena

机构信息

1Department of International Development, Community, and Environment, Clark University, 950 Main Street, Worcester, MA 01610-1477 USA.

2Department of International Development, Community, and Environment, Clark University, 950 Main Street, Worcester, MA 01610-1477 USA.

出版信息

Appl Spat Anal Policy. 2012;5(3):211-229. doi: 10.1007/s12061-011-9067-7. Epub 2011 May 25.

DOI:10.1007/s12061-011-9067-7
PMID:32218878
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7090722/
Abstract

West Nile Virus (WNV) is a serious illness that has affected thousands of people in the United States. Over 1,000 disease related deaths have occurred since its introduction to American soil in 1999. Spatial statistics are used to analyze distributional trends of human WNV cases from 2000 to 2008 through four analyses: Weighted Mean Center, Standard Deviational Ellipses, Global Moran's I, and Getis-Ord-Gi* statistic (hot spot analysis). We conclude that the directional trend in cases has been from East to West with the area affected increasing with time. Hot spot analysis reveals that recurring counties with a high number of human cases have been in the metro areas of large cities. However, normalized results indicate that the rate of humans showing symptoms of WNV is greatest in rural areas, particularly the Great Plains. These results provide a foundation for future research in analyzing the most persistent hot spots in more detail. Furthermore, these findings may aid decision makers in identifying areas to target for mitigation strategies such as spraying, larval control, and public awareness.

摘要

西尼罗河病毒(WNV)是一种严重疾病,已在美国感染了数千人。自1999年传入美国本土以来,已发生了1000多例与该疾病相关的死亡病例。通过加权平均中心、标准差椭圆、全局莫兰指数和Getis-Ord-Gi*统计量(热点分析)这四种分析方法,运用空间统计学来分析2000年至2008年人类西尼罗河病毒病例的分布趋势。我们得出结论,病例的方向趋势是从东向西,且受影响的区域随时间增加。热点分析表明,人类病例数较多的反复出现的县位于大城市的都市区。然而,归一化结果表明,出现西尼罗河病毒症状的人类比例在农村地区最高,尤其是大平原地区。这些结果为未来更详细地分析最持久的热点地区的研究奠定了基础。此外,这些发现可能有助于决策者确定实施喷洒、幼虫控制和公众意识等缓解策略的目标区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/f96d6962e55b/12061_2011_9067_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/8cb94d27c9db/12061_2011_9067_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/ab0946c49d84/12061_2011_9067_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/e2c8d5783987/12061_2011_9067_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/e545c182d1ea/12061_2011_9067_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/513906b4ae48/12061_2011_9067_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/eac61b69ebd6/12061_2011_9067_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/a23d3629c20a/12061_2011_9067_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/f96d6962e55b/12061_2011_9067_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/8cb94d27c9db/12061_2011_9067_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/ab0946c49d84/12061_2011_9067_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/e2c8d5783987/12061_2011_9067_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/e545c182d1ea/12061_2011_9067_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/513906b4ae48/12061_2011_9067_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/eac61b69ebd6/12061_2011_9067_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/a23d3629c20a/12061_2011_9067_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab38/7090722/f96d6962e55b/12061_2011_9067_Fig8_HTML.jpg

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