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An Epidemic Avian Influenza Prediction Model Based on Google Trends

[ Vol. 16 , Issue. 4 ]

Author(s):

Yi Lu, Shuo Wang, Jianying Wang, Guangya Zhou, Qiang Zhang, Xiang Zhou*, Bing Niu*, Qin Chen* and Kuo-Chen Chou   Pages 303 - 310 ( 8 )

Abstract:


The occurrence of epidemic avian influenza (EAI) not only hinders the development of a country's agricultural economy, but also seriously affects human beings’ life. Recently, the information collected from Google Trends has been increasingly used to predict various epidemics. In this study, using the relevant keywords in Google Trends as well as the multiple linear regression approach, a model was developed to predict the occurrence of epidemic avian influenza. It was demonstrated by rigorous cross-validations that the success rates achieved by the new model were quite high, indicating the predictor will become a very useful tool for hospitals and health providers.

Keywords:

Google trends, H5N2, avian influenza, prediction model, multiple line regression model, Chou’s intuitive metrics.

Affiliation:

School of Life Sciences, Shanghai University, Shanghai, School of Life Sciences, Shanghai University, Shanghai, School of Life Sciences, Shanghai University, Shanghai, School of Life Sciences, Shanghai University, Shanghai, Technical Center for Animal Plant and Food Inspection and Quarantine, Shanghai, Institute of Heating, Ventilating & Air Conditioning Engineering, School of Mechanical Engineering, Tongji University, 1239 Siping Road, Shanghai, School of Life Sciences, Shanghai University, Shanghai, School of Life Sciences, Shanghai University, Shanghai, Gordon Life Science Institute, Boston, MA

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