Spatio-Temporal Epidemiology: Methods and Applications

描述（由申请人提供）：本申请旨在支持开发时空区域数据分析方法。这些方法旨在：确定空间和（或）时间上的趋势；发现“热点”或“冷”风险点；评估干预措施的实施情况；发现存在健康差异的人群；并对可能的风险因素做出假设。综合时空疾病数据提出了独特的统计挑战，特别是必须考虑到：空间和时间依赖性；罕见事件的内在不稳定性；分子和分母的错误；以及由聚集引起的问题（如果不加以解决，可能会导致“生态偏见”）。这个应用程序解决了这些问题，并有具体的目标：

DESCRIPTION (provided by applicant): This application seeks support to develop methods for the analysis of spatio-temporal area data. These methods aim to: identify trends in space and/or time; detect "hot" or "cold" spots of risk; assess delivery of interventions; detect populations who are subject to health disparities; and generate hypotheses concerning possible risk factors. Aggregated spatio-temporal disease data present unique statistical challenges, in particular one must account for: spatial and temporal dependence; the inherent instability of rare events; errors in numerators and denominators; and problems due to aggregation (which if not addressed may lead to "ecological bias"). This application addresses each of these issues, and has specific aims: 1. To develop and apply spatio-temporal models, in particular to carry out surveillance. 2. To develop a framework for analysis of the association between aggregated health outcomes and environmental exposures (in air, water, or soil) measured at point locations. 3. To develop efficient designs for combining ecological- and individual-level data to provide a stronger analytic basis for ecological studies. The methods developed will be genetically applicable to non-infectious diseases and will be illustrated using a range of data including publicly-available U.S. cancer incidence and mortality data, and Washington State small-area cancer incidence data. Developed methods will be made available to researchers via implementation within freely-available software.