title: Forecasting influenza epidemics from multi-stream surveillance data in a subtropical city of China.
abstract: BACKGROUND
  Influenza has been associated with heavy burden of mortality and morbidity in subtropical regions. However, timely forecast of influenza epidemic in these regions has been hindered by unclear seasonality of influenza viruses. In this study, we developed a forecasting model by integrating multiple sentinel surveillance data to predict influenza epidemics in a subtropical city Shenzhen, China.
  
  
  METHODS
  Dynamic linear models with the predictors of single or multiple surveillance data for influenza-like illness (ILI) were adopted to forecast influenza epidemics from 2006 to 2012 in Shenzhen. Temporal coherence of these surveillance data with laboratory-confirmed influenza cases was evaluated by wavelet analysis and only the coherent data streams were entered into the model. Timeliness, sensitivity and specificity of these models were also evaluated to compare their performance.
  
  
  RESULTS
  Both influenza virology data and ILI consultation rates in Shenzhen demonstrated a significant annual seasonal cycle (p<0.05) during the entire study period, with occasional deviations observed in some data streams. The forecasting models that combined multi-stream ILI surveillance data generally outperformed the models with single-stream ILI data, by providing more timely, sensitive and specific alerts.
  
  
  CONCLUSIONS
  Forecasting models that combine multiple sentinel surveillance data can be considered to generate timely alerts for influenza epidemics in subtropical regions like Shenzhen.
authors.affiliation: School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.
authors.forename: Pei-Hua
authors.initials: PH
authors.lastname: Cao
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Xin
authors.initials: X
authors.lastname: Wang
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Shi-Song
authors.initials: SS
authors.lastname: Fang
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Xiao-Wen
authors.initials: XW
authors.lastname: Cheng
authors.affiliation: School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.
authors.forename: King-Pan
authors.initials: KP
authors.lastname: Chan
authors.affiliation: School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.
authors.forename: Xi-Ling
authors.initials: XL
authors.lastname: Wang
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Xing
authors.initials: X
authors.lastname: Lu
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Chun-Li
authors.initials: CL
authors.lastname: Wu
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Xiu-Juan
authors.initials: XJ
authors.lastname: Tang
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Ren-Li
authors.initials: RL
authors.lastname: Zhang
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Han-Wu
authors.initials: HW
authors.lastname: Ma
authors.affiliation: Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
authors.forename: Jin-Quan
authors.initials: JQ
authors.lastname: Cheng
authors.affiliation: School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.
authors.forename: Chit-Ming
authors.initials: CM
authors.lastname: Wong
authors.affiliation: School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China; School of Nursing, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China.
authors.forename: Lin
authors.initials: L
authors.lastname: Yang
mesh_terms: D002681:China / Q000453:epidemiology; D005843:Geography; D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D008962:Models, Theoretical; D011159:Population Surveillance / Q000379:methods; D015203:Reproducibility of Results