文章基本信息

标题：Statistical Models for Biosurveillance of Multiple Organisms
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作者：Doyo G. Enki ; Angela Noufaily ; C. P. Farrington 等
期刊名称：Online Journal of Public Health Informatics
电子版ISSN：1947-2579
出版年度：2013
卷号：5
期号：1
语种：English
出版社：University of Illinois at Chicago
摘要：Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. We analysed twenty yearsâ€°Ã›Âª data from a large laboratory surveillance database used for outbreak detection in England and Wales. Our aim is to inform the development of more effective outbreak detection algorithms. We describe the diversity of seasonal patterns, trends, artefacts and extra-Poisson variability that an effective multiple laboratory-based outbreak detection system must cope with. We provide empirical information to guide the selection of simple statistical models for automated surveillance of multiple organisms.