期刊
SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY
卷 1, 期 2-3, 页码 105-116出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.sste.2009.12.001
关键词
Disease surveillance; Space-time; Scan statistics; Model-based; Cluster
资金
- Teasdale-Corti Global Health Research Partnership Program
- National Sciences and Engineering Research Council of Canada
- GeoConnections Canada
A review of some methods for analysis of space-time disease surveillance data is presented. Increasingly, surveillance systems are capturing spatial and temporal data on disease and health outcomes in a variety of public health contexts. A vast and growing suite of methods exists for detection of outbreaks and trends in surveillance data and the selection of appropriate methods in a given surveillance context is not always clear. While most reviews of methods focus on algorithm performance, in practice, a variety of factors determine what methods are appropriate for surveillance. In this review, we focus on the role of contextual factors such as scale, scope, surveillance objective, disease characteristics, and technical issues in relation to commonly used approaches to surveillance. Methods are classified as testing-based or model-based approaches. Reviewing methods in the context of factors other than algorithm performance highlights important aspects of implementing and selecting appropriate disease surveillance methods. (C) 2010 Elsevier Inc. All rights reserved.
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