A cluster model for space-time disease counts |
| |
Authors: | Yan Ping Clayton Murray K |
| |
Institution: | Department of Statistics, University of Wisconsin-Madison, 1300 University Avenue, Madison, WI 53706, USA. yanp@stat.wisc.edu |
| |
Abstract: | Modelling disease clustering over space and time can be helpful in providing indications of possible exposures and planning corresponding public health practices. Though a considerable number of studies focus on modelling spatio-temporal patterns of disease, most of them do not directly model a spatio-temporal clustering structure and could be ineffective for detecting clusters. In this paper, we extend a purely spatial cluster model to accommodate space-time clustering. Inference is performed in a Bayesian framework using reversible jump Markov chain Monte Carlo. This idea is illustrated using data on female breast cancer mortality from Japan. A hierarchical parametric space-time model for mapping disease is used for comparison. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|