Geostatistical software for the analysis of individual-level epidemiologic data

说明（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，提供专门为汇总和个人健康数据的地理统计分析设计的工具，提供：描述癌症发病率和死亡率的空间格局并确定变异尺度，对个人层面的数据进行空间插值以创建相对风险等线图，确定发病率或死亡率显著高或显著低的集群和热点，检测不同民族或种族群体健康结果之间的显著差异（健康差异），并可视化差异随时间的变化。该产品将允许调查癌症诊断阶段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（如环境和职业暴露、社会经济条件、靠近筛查中心）之间的关系，从而：(1)更好地理解在癌症发病率、死亡率和生存率方面观察到的地理和种族差异的原因；(2)长期量化当前战略的效益，以减少美国少数民族和医疗服务不足人群中不成比例的癌症发病率和死亡率。将编写教学材料，促进卫生科学家使用这种相对较新的方法。该项目的第一阶段将：从个人层面的数据和统计测试中绘制风险图，以发现亚人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)）。地域和种族差异。这项研究的实质好处是它在获取、连接、绘制和分析各种基于人群和个人层面的数据方面的效用，包括癌症生命事件和社会经济、人口、行为和环境条件的措施。本项目制定的方法将有助于了解在不同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当前战略的益处。

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.