Zhang Zi-Wu, Feng Zi-Jian, Li Xiao-Song
Sichuan Center for Disease Control and Prevention, Chengdu 610041, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2010 Nov;31(11):1306-10.
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 multi-dimensional 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.
探讨WSARE（近期事件有何异常）算法在传染病暴发预警中的应用，探索检测传染病暴发的多维统计方法。分别以基于历史数据的WSARE算法和贝叶斯网络为基线，通过模拟2007年深圳市宝安区的实时监测和预警系统来分析麻疹数据。WSARE算法在检测特殊人群中麻疹异常增加方面被认为是有效且及时的。WSARE算法能够及时检测出特定本地人群中疾病的异常增加，因此在传染病暴发期间的预警系统应用中具有重要价值。
