WSARE计算方法在传染病暴发早期 预警中的应用

探讨异常模式探测方法--WSARE(What's Strange About Recent Events)在传染病暴发早期预警中的应用价值,拓展传染病病例监测数据的多维聚集性探测统计方法.分别采用基于历史数据和贝叶斯网络为基线的WSARE算法,对2007年深圳市宝安区麻疹发病模拟实时监测预警.结果 表明WSARE算法能够早期探测到麻疹在特定人群的异常增高,在传染病暴发早期预警中具有重要应用价值.

A study regarding the applicability of WSARE algorithms in the early warning system of infectious disease outbreaks

To investigate the application of WSARE (What' s Strange About Recent Events) algorithm in early warning on outbreaks of infectious diseases and to explore the multidimensional statistical methods for the detection of infectious diseases outbreak. Using WSARE algorithms based on historical data and Bayesian Network as baseline respectively, to analyze data on measles by mimicking the real-time monitoring and early warning system in Bao'an district,Shenzhen city, in 2007. WSARE algorithms were considered to be effective and timely in detecting the abnormally increase of measles among special population. WSARE algorithm could timely detect the abnormal increase of diseases among special local populations, thus having important value in the application of early warning system during the outbreak of infectious diseases.