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. 2013 May 30;8(5):e64323.
doi: 10.1371/journal.pone.0064323. Print 2013.

Monitoring influenza epidemics in china with search query from baidu

Qingyu Yuan  1 , Elaine O Nsoesie, Benfu Lv, Geng Peng, Rumi Chunara, John S Brownstein
Affiliations

Monitoring influenza epidemics in china with search query from baidu

Qingyu Yuan et al. PLoS One. .

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.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Influenza case data and composite search index.
Figure 2
Figure 2. Plot of influenza cases, fitted values and prediction based on model .
See this image and copyright information in PMC

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