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| Mechanism and Empirical Research on Forecasting Influenza Epidemic Fused with Baidu Index |
| Wang Ruojia1,2 |
1. Department of Information Management, Peking University, Beijing 100871;
2. Institute of Ocean Research, Peking University, Beijing 100871 |
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Abstract This study explores the internal mechanism and possibility of forecasting an influenza epidemic based on both search queries and actual influenza data. First, the logical relationship is explored between online information searches and conventional surveillance data based on the concepts of information behaviors, information seeking behaviors, and so on. Then, the range selection method and cross-correlation analysis are used to select keywords according to the theoretical framework. Finally, three models are established and compared. The results show that (i) the empirical research proves the logical rationality of the theoretical framework: the keywords that could reflect flu trends ten weeks in advance are related to influenza vaccines; those a week in advance are related to influenza symptoms; and most of the simultaneous keywords are frequent terms related to influenza; (ii) all three models can predict influenza effectively, and support vector machine yields the most accurate forecasting result.
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Received: 25 June 2017
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