Name Monitoring Influenza Epidemics with Search Queries
Source Chinese Academy of Sciences
Hyperlink to Source http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0064323
Description This study presents a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. 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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Lead Institution Chinese Academy of Sciences
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Partners Boston Children’s Hospital
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Info link http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0064323
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Type Research
Potential for reuse Medium
Open source N/A
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Plug & Play N/A
Outputs compatible with indicators from Official Statistics N/A
Status Pilot
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  • Areas of technological innovation
  • Log Data
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  • Real Time Data
  • Areas of management practice innovations
    Use of Alternative Data Sources
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    Created On 2014-04-12
    Updated On 2014-04-12
    Status Published
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