Spatio-Temporal Epidemiology: Methods and Applications

时空流行病学：方法与应用

• 批准号: 7269420
• 负责人: JONATHAN C WAKEFIELD
• 金额: $ 18.65万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-30 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7269420
• 关键词: Accounting; Address; Air; Air Pollution; Area; Class; Classification; Cohort Studies; Communicable Diseases; Computer software; Count; Data; Databases; Dependence; Detection; Disease; Disease regression; Ecological Bias; Environmental Exposure; Epidemiologic Methods; Epidemiologist; Epidemiology; Etiology; Event; Geography; Goals; Health; Hybrids; Incidence; Individual; Intervention; Lead; Literature; Location; London; Malignant Neoplasms; Maps; Measurement; Measures; Medical Surveillance; Methodology; Methods; Modeling; Monitor; Numbers; Outcome; Phase; Pollution; Population; Populations at Risk; Prevention program; Public Health; Range; Rate; Research Personnel; Risk; Risk Factors; Sample Size; Sampling; Scanning; Sensitivity and Specificity; Soil; Spottings; Statistical Methods; Supplementation; Surface; Surveillance Methods; Surveillance Modeling; Techniques; Time; Washington; Water; Women' s Health; base; case control; design; disorder risk; health disparity; improved; interest; mortality; simulation; statistics; trend; user-friendly

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.

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：