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Baidu Index and COVID-19 Epidemic Forecast: Evidence From China

With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to th...

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Autores principales: Fang, Jianchun, Zhang, Xinyi, Tong, Yang, Xia, Yuxin, Liu, Hui, Wu, Keke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131679/
https://www.ncbi.nlm.nih.gov/pubmed/34026721
http://dx.doi.org/10.3389/fpubh.2021.685141
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author Fang, Jianchun
Zhang, Xinyi
Tong, Yang
Xia, Yuxin
Liu, Hui
Wu, Keke
author_facet Fang, Jianchun
Zhang, Xinyi
Tong, Yang
Xia, Yuxin
Liu, Hui
Wu, Keke
author_sort Fang, Jianchun
collection PubMed
description With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to the epidemic and the demand for N95 masks and other anti-epidemic materials and information. This kind of analysis has become an important part of information epidemiology. We have analyzed the use of the keywords “Coronavirus epidemic,” “N95 mask,” and “Wuhan epidemic” to judge whether the introduction of real-time search data has improved the efficiency of the Coronavirus epidemic prediction model. In general, the introduction of the Baidu index, whether in-sample or out-of-sample, significantly improves the prediction efficiency of the model.
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spelling pubmed-81316792021-05-20 Baidu Index and COVID-19 Epidemic Forecast: Evidence From China Fang, Jianchun Zhang, Xinyi Tong, Yang Xia, Yuxin Liu, Hui Wu, Keke Front Public Health Public Health With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to the epidemic and the demand for N95 masks and other anti-epidemic materials and information. This kind of analysis has become an important part of information epidemiology. We have analyzed the use of the keywords “Coronavirus epidemic,” “N95 mask,” and “Wuhan epidemic” to judge whether the introduction of real-time search data has improved the efficiency of the Coronavirus epidemic prediction model. In general, the introduction of the Baidu index, whether in-sample or out-of-sample, significantly improves the prediction efficiency of the model. Frontiers Media S.A. 2021-05-05 /pmc/articles/PMC8131679/ /pubmed/34026721 http://dx.doi.org/10.3389/fpubh.2021.685141 Text en Copyright © 2021 Fang, Zhang, Tong, Xia, Liu and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Fang, Jianchun
Zhang, Xinyi
Tong, Yang
Xia, Yuxin
Liu, Hui
Wu, Keke
Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title_full Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title_fullStr Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title_full_unstemmed Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title_short Baidu Index and COVID-19 Epidemic Forecast: Evidence From China
title_sort baidu index and covid-19 epidemic forecast: evidence from china
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8131679/
https://www.ncbi.nlm.nih.gov/pubmed/34026721
http://dx.doi.org/10.3389/fpubh.2021.685141
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