哥伦比亚卡利登革热的时空格局

E. Delmelle, Irene Casas, J. H. Rojas, Alejandro Varela
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引用次数: 29

摘要

登革热是一种典型的热带虫媒病毒性疾病,可危及生命,如果控制不当可能导致流行病。由于缺乏有效的疫苗,预防病毒传播的战略成为最有效的控制手段。然而,由于个体和蚊子宿主(埃及伊蚊)的不断移动,这种策略的规划很困难。本文探讨了登革热流行年感染个体之间可能存在的时空关系。这项研究的动机在于,深入了解个体之间潜在的传播模式可能会导致更好的控制策略设计和规划。利用基于gis的健康探索性分析工具(HELP),通过空间k函数、核密度、时空k函数以及在重要的时间和空间间隔内连接病例对来计算时空关系。在50米和750米尺度上分别观察到显著聚类,在2天和5 ~ 8天尺度上确定时间显著性。虽然在厄尔尼诺现象导致的严重干旱后的几个月内病例有所增加,但聚集性病例的位置仍然相对稳定。这些现象在可能存在蚊子栖息地的区域附近观察到,如雨水沟、积水的坚硬表面(如花瓶、容器),但也在较贫穷的社区观察到。空间分析的结果为卫生保健管理人员在市政一级采取预防措施提供了有价值的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-Temporal Patterns of Dengue Fever in Cali, Colombia
Dengue fever is an arboviral disease typical of the tropics that can be life-threatening and if not controlled properly may result in an epidemic. The absence of an effective vaccine makes strategies to prevent the virus transmission the most effective means of control. The planning of such strategies, however, is difficult due to the constant movement of individuals and mosquito host (Aedes aegypti). In this paper, the spatial and temporal relations that might exist between infected individuals during a dengue-epidemic year are explored. This research is motivated in that a deep understanding of potential transmission patterns between individuals might lead to a better design and planning of control strategies. A GIS-based Health Exploratory AnaLysis Tool (HELP) is used to compute space-time relationships by means of spatial K-function, kernel density, space-time K-function and linking pairs of cases within significant time and space intervals. Significant clustering was observed at a scale of 50 meters and 750 meters, respectively while temporal significance was determined at two days and five to eight days. While an increase of cases occurs in the months following severe droughts due to an El NiA±o phenomenon, the location of clusters remains relatively stable. These are observed near areas where potential habitats for the mosquito exist such as storm drains, hard surfaces where water accumulates (e.g., vases, containers), but also in poorer neighborhoods. The results from the spatial analysis provide valuable information for health care managers to take preventive actions at the municipality level.
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