Spatial analysis of hemorrhagic fever with renal syndrome in China.
Spatial analysis of hemorrhagic fever with renal syndrome in China.
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DOI：
10.1186/1471-2334-6-77
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发表时间：
2006-04-26
影响因子：
3.7
通讯作者：
Cao, Wuchun
中科院分区：
文献类型：
--
作者：
Fang, Liqun;Yan, Lei;Liang, Song;de Vlas, Sake J.;Feng, Dan;Han, Xiaona;Zhao, Wenjuan;Xu, Bing;Bian, Ling;Yang, Hong;Gong, Peng;Richardus, Jan Hendrik;Cao, Wuchun
肾综合征出血热在多个省份流行，在内地中国是高发地区，尽管包括灭鼠、环境管理和疫苗接种在内的综合干预措施已经实施了十多年。在这项研究中，我们进行了基于地理信息系统(GIS)的全国HFRS病例分布的空间分析，目的是为公共卫生规划和资源分配的优先地区提供信息。利用内地中国1994年至1998年报告的肾综合征出血热病例，计算出县级年平均发病率。基于地理信息系统的空间分析用于检测全国县级肾综合征出血热病例的空间自相关性和聚集性。从粗发病、超危和空间平滑三个方面绘制了1994年至1998年内地中国肾综合征出血热病例的县级空间分布图。肾综合征出血热病例的空间分布是非随机的，呈聚集性，Moran‘s I=0.5044(p=0.001)。空间聚类分析表明，有26个和39个地区处于肾综合征出血热发病风险的增加状态(P<；0.01)，最大空间聚集度分别为总人口的≤20%和≤10%。地理信息系统的应用与空间统计技术一起，提供了一种量化明确的肾综合征出血热风险和进一步确定造成疾病风险增加的环境因素的手段。我们展示了将这种空间分析工具整合到肾综合征出血热流行病学研究和风险评估中的新视角。
Hemorrhagic fever with renal syndrome (HFRS) is endemic in many provinces with high incidence in mainland China, although integrated intervention measures including rodent control, environment management and vaccination have been implemented for over ten years. In this study, we conducted a geographic information system (GIS)-based spatial analysis on distribution of HFRS cases for the whole country with an objective to inform priority areas for public health planning and resource allocation. Annualized average incidence at a county level was calculated using HFRS cases reported during 1994–1998 in mainland China. GIS-based spatial analyses were conducted to detect spatial autocorrelation and clusters of HFRS incidence at the county level throughout the country. Spatial distribution of HFRS cases in mainland China from 1994 to 1998 was mapped at county level in the aspects of crude incidence, excess hazard and spatial smoothed incidence. The spatial distribution of HFRS cases was nonrandom and clustered with a Moran's I = 0.5044 (p = 0.001). Spatial cluster analyses suggested that 26 and 39 areas were at increased risks of HFRS (p < 0.01) with maximum spatial cluster sizes of ≤ 20% and ≤ 10% of the total population, respectively. The application of GIS, together with spatial statistical techniques, provide a means to quantify explicit HFRS risks and to further identify environmental factors responsible for the increasing disease risks. We demonstrate a new perspective of integrating such spatial analysis tools into the epidemiologic study and risk assessment of HFRS.
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影响因子：
0.8
作者：
Kulldorff, M
通讯作者：
Kulldorff, M
影响因子：
12.7
作者：
GLASS, GE;SCHWARTZ, BS;ISRAEL, E
通讯作者：
ISRAEL, E
影响因子：
3.6
作者：
ANSELIN, L
通讯作者：
ANSELIN, L
影响因子：
4.9
作者：
Nkhoma ET;Ed Hsu C;Hunt VI;Harris AM
通讯作者：
Harris AM
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4.9
作者：
Odoi A;Martin SW;Michel P;Middleton D;Holt J;Wilson J
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Wilson J