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.
Highlights
Seasonal influenza epidemics result in an estimated three to five million cases of severe illness and 250,000 to 500,000 deaths worldwide each year [1]
Based on the filtering analysis, 14 out of the 94 keywords are not related to influenza epidemics, 20 keywords do not have sequential time series due to low search volume and only 40 keywords are significantly correlated to the case data
We develop a comprehensive method for pre-processing Internet search data for modeling and detecting influenza epidemics in China
Summary
Seasonal influenza epidemics result in an estimated three to five million cases of severe illness and 250,000 to 500,000 deaths worldwide each year [1]. Some novel approaches for rapid disease outbreak detection and surveillance include online surveillance systems utilizing informal sources such as news reports [2], social media data [3±16], and search query data [17±20]. The idea of using search query data for detecting outbreaks was first introduced in 2006 [17]. Several studies followed, which pointed to the effectiveness and limitations of detecting influenza epidemics using search query data [19], [20]. There are limitations, such as the lack of Internet access in some regions of the world and the noise of irrelevant information, Internet search query data is being explored as a low-cost approach to estimating disease activity in near real-time
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