Yuan, QingyuNsoesie, Elaine O.Lv, BenfuPeng, GengChunara, RumiBrownstein, John S.2018-10-192018-10-192013-05-30e64323http://hdl.handle.net/10919/85428Several 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.application/pdfenCreative Commons Attribution 4.0 InternationalArticle - Refereedhttps://doi.org/10.1371/journal.pone.006432385237501921932-6203