title: [A study regarding the applicability of WSARE algorithms in the early warning system of infectious disease outbreaks].
abstract: 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.
authors.affiliation: Sichuan Center for Disease Control and Prevention, Chengdu 610041, China.
authors.forename: Zi-Wu
authors.initials: ZW
authors.lastname: Zhang
authors.forename: Zi-Jian
authors.initials: ZJ
authors.lastname: Feng
authors.forename: Xiao-Song
authors.initials: XS
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003141:Communicable Diseases / Q000453:epidemiology; D004196:Disease Outbreaks; D006801:Humans; D008457:Measles / Q000453:epidemiology; D011159:Population Surveillance