title: Monitoring influenza epidemics in china with search query from baidu.
abstract: Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The objectives of the study are to present a comprehensive technique for: (i) keyword selection, (ii) keyword filtering, (iii) index composition and (iv) modeling and detection of influenza activity in China. Sequential time-series for the selected composite keyword index is significantly correlated with Chinese influenza case data. In addition, one-month ahead prediction of influenza cases for the first eight months of 2012 has a mean absolute percent error less than 11%. To our knowledge, this is the first study on the use of search query data from Baidu in conjunction with this approach for estimation of influenza activity in China.
authors.affiliation: Management School, University of Chinese Academy of Sciences, Beijing, China. Qingyu.Yuan@childrens.havard.edu
authors.forename: Qingyu
authors.initials: Q
authors.lastname: Yuan
authors.forename: Elaine O
authors.initials: EO
authors.lastname: Nsoesie
authors.forename: Benfu
authors.initials: B
authors.lastname: Lv
authors.forename: Geng
authors.initials: G
authors.lastname: Peng
authors.forename: Rumi
authors.initials: R
authors.lastname: Chunara
authors.forename: John S
authors.initials: JS
authors.lastname: Brownstein
mesh_terms: D006801:Humans; D007251:Influenza, Human / Q000453:epidemiology*; D015233:Models, Statistical; D011159:Population Surveillance; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D061108:Social Media