Ecosystem Management, School of Environmental and Rural Sciences, Faculty of Arts and Sciences, University of New England, Armidale, NSW 2351, Australia.
Sci Total Environ. 2012 Jul 15;430:144-9. doi: 10.1016/j.scitotenv.2012.05.001. Epub 2012 May 26.
It is important to have appropriate models for the surveillance and control of mosquito-borne diseases, such as dengue fever (DF). These models need to be based on appropriate temporal and spatial scales. The aim of this study was to illustrate the impact of different temporal and spatial scales on DF control decisions. We applied the Getis-Ord Gi* statistic at different temporal and spatial scales to examine the local level of spatial clusters at these scales in order to identify and visualize areas where numbers of adult female Aedes mosquitoes were extreme and geographically homogenous. The modeled hotspot areas were different, depending on whether they were modeled on weekly, monthly or yearly aggregated data. A similar result was found when using different spatial scales for modeling, with different scales giving different hotspot regions. For 2006, the highest risk areas (18 districts) were mostly identified in the central districts with a high rate of similarity (95%) compared to the highest risk areas (19) identified in the averaged five-year period model. Knowledge of appropriate temporal and spatial scales can provide an opportunity to specify the health burden of DF and its vector within the hotspots, as well as set a platform that can help to pursue further investigations into associated factors responsible for increased disease risk based on different temporal and spatial scales.
对于蚊媒疾病（例如登革热）的监测和控制，建立适当的模型非常重要。这些模型需要基于适当的时间和空间尺度。本研究的目的是说明不同时间和空间尺度对登革热控制决策的影响。我们应用 Getis-Ord Gi* 统计量在不同的时间和空间尺度上，以检查这些尺度上的局部空间聚类的水平，以识别和可视化成蚊数量极端且地理同质的区域。建模的热点区域因每周、每月或每年聚合数据而异。当使用不同的空间尺度进行建模时，也会得到不同的热点区域，结果类似。对于 2006 年，与在五年平均模型中识别的最高风险区域（19 个区）相比，高风险区域（18 个区）主要集中在中心区，相似度很高（95%）。了解适当的时间和空间尺度可以提供一个机会，以便在热点地区内确定登革热及其病媒的卫生负担，并建立一个平台，可根据不同的时间和空间尺度，有助于进一步调查与增加疾病风险相关的因素。
