Estimating Individual-Level Risk in Spatial Epidemiology Using Spatially Aggregated Information on the Population at Risk

• 成果类型: Article
• 署名作者: Diggle, Peter J.; Guan, Yongtao; Hart, Anthony C.; Paize, Fauzia; Stanton, Michelle
• 署名单位: Yale University; Lancaster University; Johns Hopkins University; Alder Hey Children's NHS Foundation Trust; University of Liverpool; University of Liverpool
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/jasa.2010.ap09323
• 发表日期: 2010
• 页码: 1394-1402
• 关键词: meningococcal disease; ecological inference; social deprivation; influenza; england

摘要

We propose a novel alternative to case-control sampling for the estimation of individual-level risk in spatial epidemiology. Our approach uses weighted estimating equations to estimate regression parameters in the intensity function of an inhomogeneous spatial point process, when information on risk-factors is available at the individual level for cases, but only at a spatially aggregated level for the population at risk. We develop data-driven methods to select the weights used in the estimating equations and show through simulation that the choice of weights can have a major impact on efficiency of estimation. We develop a formal test to detect non-Poisson behavior in the underlying point process and assess the performance of the test using simulations of Poisson and Poisson cluster point processes. We apply our methods to data on the spatial distribution of childhood meningococcal disease cases in Merseyside, U.K. between 1981 and 2007.