Geostatistical software for the analysis of individual-level epidemiologic data

描述(由申请人提供)：该项目的总体目标是开发第一个基于地理信息系统的软件，提供专门用于汇总和个人健康数据地统计分析的工具，提供：癌症发病率和死亡率的空间模式描述和变异尺度识别，个人层面数据的空间内插以创建相对风险等值线图，识别发病率或死亡率显著高或低的集群和热点，检测不同族裔或种族群体健康结果之间的显著差异(健康差异)，可视化差异随时间的变化。该产品将有助于调查癌症诊断和生存数据的地理和种族差异，并探索健康结果与潜在因素之间的关系，如环境和职业暴露、社会经济条件、靠近筛查中心等，从而：(1)更好地了解在癌症发病率、死亡率和存活率方面观察到的地理和种族差异的原因，(2)对降低美国少数族裔和医疗服务不足者中癌症发病率和死亡率不成比例的发病率的现有战略的好处进行长期量化。将开发教学材料，在卫生科学家中推广使用这一相对较新的方法。该项目的第一阶段将：根据个人水平的数据绘制风险图，并进行统计测试，以检测不同亚群和不同空间之间癌症发病率的显著差异。进入软件：TerraSeer时空情报系统(Tm)(STIS(Tm))。地理和种族差异。这项研究的重大好处是它在访问、链接、绘制地图和分析各种基于人群和个人水平的数据方面的实用价值，包括癌症关键事件和社会经济、人口、行为和环境条件的衡量。该项目开发的方法将有助于了解在整个空间和亚人群中观察到的癌症发病率、死亡率和发病率差异的根本原因，并有助于更好地评估减少这些差异的现行战略的益处。

DESCRIPTION (provided by applicant): The overall objective of this project is to develop the first GIS-based software to offer tools that are specifically designed for the geostatistical analysis of both aggregated and individual-level health data, providing: description of spatial patterns of cancer incidence and mortality rates and identification of scales of variability, spatial interpolation of individual-level data to create isopleth maps of relative risk, identification of clusters and hotspots of significantly high or low incidence or mortality rates, detection of significant discrepancies between health outcomes for different ethnic or racial groups (health disparities), and visualization of changes in disparity through time. This product will allow the investigation of geographic and ethnic variations in cancer stage at diagnosis and survival data, and the exploration of relationships between health outcomes and potential factors, such as environmental and occupational exposures, socio-economic conditions, proximity to screening centers, leading to: (1) a better understanding of the causes underlying observed geographic and racial disparities in cancer incidence, mortality and survival, and (2) long-term quantification of the benefits of current strategies for reducing the disproportionate incidence of cancer morbidity and mortality among minorities and the medically underserved in the United States. Instructional materials will be developed to promote the use of this relatively new methodology among health scientists. Phase I of the project will: risk maps from individual-level data and statistical tests to detect significant differences in cancer rates among sub-populations and across space. into the software: TerraSeer Space-Time Intelligence System(tm) (STIS(tm)). geographical and racial disparities. The substantial benefit of this research is its utility in accessing, linking, mapping and analyzing diverse population-based and individual-level data including cancer vital events and measures of socioeconomic, demographic, behavioral and environmental conditions. The methods developed in this project will help understanding the causes underlying the disparities in cancer incidence, mortality and morbidity observed across space and among sub-populations, as well as lead to a better assessment of the benefits of current strategies for reducing these disparities.