Visualization and exploratory analysis of epidemiologic data using a novel space time information system.
Visualization and exploratory analysis of epidemiologic data using a novel space time information system.
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DOI：
10.1186/1476-072x-3-26
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发表时间：
2004-11-08
影响因子：
4.9
通讯作者：
Nriagu JO
中科院分区：
文献类型：
--
作者：
Avruskin GA;Jacquez GM;Meliker JR;Slotnick MJ;Kaufmann AM;Nriagu JO
近年来，地理信息系统（GIS）在环境健康研究中的应用得到了扩展。在这一领域，GIS可用于检测疾病聚集，分析医院急诊的可及性，预测环境爆发，以及估计有毒化合物的暴露。尽管有这些进步，GIS无法正确处理时间信息越来越被认为是一个重要的限制。因此，空间和时间维度的有效表示和可视化预计将大大提高我们利用时间参考地理空间数据进行环境健康研究的能力。特别是对于潜伏期较长的疾病（如癌症）而言，能够代表、量化和模拟各个时间段的暴露是风险估计的一个关键组成部分。为了满足这一需要，开发了一个STIS -一个时空信息系统，通过空间和时间同时对物体进行可视化和分析。在本文中，我们提出了一个“第一次使用”的STIS在密歇根州东南部砷暴露和膀胱癌之间的关系的病例对照研究。个人砷暴露重建纳入时空数据，包括住宅流动性和饮用水的习惯。STIS的独特贡献是它能够在不同的时间尺度上可视化和分析居住历史。使用动态视图查看和统计分析参与者信息，在动态视图中，属性值随时间变化。这些视图包括表格、图形（如直方图和散点图）和地图。此外，这些视图还可以链接和同步，以便使用制图画笔、统计画笔和动画进行复杂的数据探索。STIS提供了新的和强大的方法来可视化和分析个人暴露和相关的环境变量如何随时间变化。我们希望看到创新的时空方法被用于未来的环境健康研究，现在已经成功地“首次使用”的STIS暴露重建。
Recent years have seen an expansion in the use of Geographic Information Systems (GIS) in environmental health research. In this field GIS can be used to detect disease clustering, to analyze access to hospital emergency care, to predict environmental outbreaks, and to estimate exposure to toxic compounds. Despite these advances the inability of GIS to properly handle temporal information is increasingly recognised as a significant constraint. The effective representation and visualization of both spatial and temporal dimensions therefore is expected to significantly enhance our ability to undertake environmental health research using time-referenced geospatial data. Especially for diseases with long latency periods (such as cancer) the ability to represent, quantify and model individual exposure through time is a critical component of risk estimation. In response to this need a STIS – a Space Time Information System has been developed to visualize and analyze objects simultaneously through space and time. In this paper we present a "first use" of a STIS in a case-control study of the relationship between arsenic exposure and bladder cancer in south eastern Michigan. Individual arsenic exposure is reconstructed by incorporating spatiotemporal data including residential mobility and drinking water habits. The unique contribution of the STIS is its ability to visualize and analyze residential histories over different temporal scales. Participant information is viewed and statistically analyzed using dynamic views in which values of an attribute change through time. These views include tables, graphs (such as histograms and scatterplots), and maps. In addition, these views can be linked and synchronized for complex data exploration using cartographic brushing, statistical brushing, and animation. The STIS provides new and powerful ways to visualize and analyze how individual exposure and associated environmental variables change through time. We expect to see innovative space-time methods being utilized in future environmental health research now that the successful "first use" of a STIS in exposure reconstruction has been accomplished.