A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.
A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.
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DOI：
10.1186/1476-072x-12-21
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发表时间：
2013-04-15
影响因子：
4.9
通讯作者：
Morris JG Jr
中科院分区：
文献类型：
--
作者：
Curtis A;Blackburn JK;Widmer JM;Morris JG Jr
即使有病例数据，对具有挑战性的城市地区的健康风险进行精细和纵向地理空间分析也往往因缺乏其他空间层而受到限制。基本的人口统计，居住环境和相关的致病因素，如积水或垃圾地点往往是失踪，除非通过后勤困难，往往昂贵，调查收集。缺乏空间背景也阻碍了对结果的解释和围绕分析见解设计干预战略。本文提供了一个无处不在的空间数据收集方法，使用空间视频，可用于改善分析，并涉及参与式合作。一个案例研究将被用来说明这种方法与三个健康风险映射在街道规模的沿海社区在海地。空间视频被用来收集街道和建筑规模的信息，包括积水，垃圾堆积，狗的存在，队列特定的人口特征，和其他文化现象。这些数据被数字化到谷歌地球，然后编码和分析在地理信息系统使用内核密度和空间过滤方法。这些风险集中在地区学校周围，由于儿童高度集中和不同的卫生习惯，这些学校有时是疟疾感染的来源，这将表明该方法的实用性。此外，学校为霍乱教育干预措施提供了可能的场所。以前无法获得的细规模健康风险数据在整个城镇的集中度各不相同，一些学校靠近地图上风险更集中的地方。空间视频还用于验证这些“热点”内的编码数据和位置特定风险。空间视频是一种可以在任何环境中使用的工具，用于改善局部区域的健康分析和干预。这一过程是迅速的，可以在研究地点重复，随着时间的推移，以跟踪社区的时空动态。它的简单性还应用来鼓励地方参与性合作。
Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations.