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An Epidemic Avian Influenza Prediction Model Based on Google Trends

Author(s):

Bing Niu*, Yi Lu, Jianying Wang, Qin Chen, Xiang Zhou, Qiang Zhang, Kuo-Chen Chou and Shuo Wang   Pages 1 - 9 ( 9 )

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 influenzas, Prediction model, Multiple line regression model, Chou’s intuitive metrics

Affiliation:

Shanghai Unversity, School of Life Sciences, Shanghai Unversity, School of Life Sciences, Shanghai Unversity, School of Life Sciences, Shanghai Unversity, School of Life Sciences, Tongji University, Institute of Heating, Ventilating & Air Conditioning Engineering, School of Mechanical Engineering, Technical center for animal plant and food inspection and quarantine, Gordon Life Science Institute, Gordon Life Science Institute, Shanghai Unversity, School of Life Sciences



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