title: Optimizing use of multistream influenza sentinel surveillance data.
abstract: We applied time-series methods to multivariate sentinel surveillance data recorded in Hong Kong during 1998-2007. Our study demonstrates that simultaneous monitoring of multiple streams of influenza surveillance data can improve the accuracy and timeliness of alerts compared with monitoring of aggregate data or of any single stream alone.
authors.affiliation: University of Hong Kong, Hong Kong Special Administrative Region, People's Republic of China.
authors.forename: Eric H Y
authors.initials: EH
authors.lastname: Lau
authors.forename: Benjamin J
authors.initials: BJ
authors.lastname: Cowling
authors.forename: Lai-Ming
authors.initials: LM
authors.lastname: Ho
authors.forename: Gabriel M
authors.initials: GM
authors.lastname: Leung
mesh_terms: D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis* / Q000453:epidemiology; D012044:Regression Analysis; D012680:Sensitivity and Specificity; D018571:Sentinel Surveillance