期刊
STATISTICAL METHODS IN MEDICAL RESEARCH
卷 27, 期 4, 页码 1076-1087出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0962280216652156
关键词
Bayesian; Kullback-Leibler; SCPO; spatial; prospective surveillance; temporal
类别
资金
- NCI NIH HHS [R03 CA179665] Funding Source: Medline
Early detection of unusual health events depends on the ability to rapidly detect any substantial changes in disease, thus facilitating timely public health interventions. To assist public health practitioners to make decisions, statistical methods are adopted to assess unusual events in real time. We introduce a surveillance Kullback-Leibler measure for timely detection of disease outbreaks for small area health data. The detection methods are compared with the surveillance conditional predictive ordinate within the framework of Bayesian hierarchical Poisson modeling and applied to a case study of a group of respiratory system diseases observed weekly in South Carolina counties. Properties of the proposed surveillance techniques including timeliness and detection precision are investigated using a simulation study.
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