An Epidemic Avian Influenza Prediction Model Based on Google Trends

Author(s): Yi Lu , Shuo Wang , Jianying Wang , Guangya Zhou , Qiang Zhang , Xiang Zhou* , Bing Niu* , Qin Chen* , Kuo-Chen Chou .

Journal Name: Letters in Organic Chemistry

Volume 16 , Issue 4 , 2019

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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.

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Article Details

VOLUME: 16
ISSUE: 4
Year: 2019
Page: [303 - 310]
Pages: 8
DOI: 10.2174/1570178615666180724103325
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