Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand
Spatio-Temporal Diffusion Pattern and Hotspot Detection of Dengue in Chachoengsao Province, Thailand
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DOI：
10.3390/ijerph8010051
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发表时间：
2011-01-01
影响因子：
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通讯作者：
Souris, Marc
中科院分区：
文献类型：
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作者：
Jeefoo, Phaisarn;Tripathi, Nitin Kumar;Souris, Marc
近年来，登革热已成为一个主要的国际公共卫生问题。在泰国，这也是一个重要的担忧，因为在过去十年中报告了几起登革热疫情。本文提出了一种分析登革热流行时空动态的地理信息系统方法。这项研究的主要目的是检查登革热报告病例的空间扩散模式和热点识别。调查了2007年登革热暴发的地理空间扩散格局。为暴发的153天绘制了每日病例地图。这项研究使用了泰国Chachoengsao省的流行病学数据(1999-2007年报告的登革热病例)。为了分析登革热暴发的动态时空模式，所有病例都定位在村级的空间上。在(按性别和年龄组)进行一般统计分析之后，随后分析了数据的时间模式以及与气候数据(特别是降雨量)、空间模式和聚类分析以及流行期间热点的时空模式的相关性。结果揭示了1999-2007年间的空间扩散格局，表现为空间聚集格局，不同村庄之间存在显着差异。城市边缘的村庄报告的发病率更高。病例的空间和时间表现为暴发运动和传播模式，可能与昆虫学和流行病学因素有关。各热点呈现出登革热扩散的空间趋势。这项研究提供了与登革热暴发在空间和时间上的模式有关的有用信息，并可能有助于公共卫生部门规划控制疾病传播的战略。该方法对时空分析具有通用性，也可用于其他传染病的分析。
In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999-2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999-2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.