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Monitoring Influenza Epidemics in China with Search Query from Baidu

2013; Public Library of Science; Volume: 8; Issue: 5 Linguagem: Inglês

10.1371/journal.pone.0064323

1932-6203

Qingyu Yuan, Elaine O. Nsoesie, Benfu Lv, Peng Geng, Rumi Chunara, John S. Brownstein,

Anomaly Detection Techniques and Applications

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.