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Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China

Reporting on brucellosis, a relatively rare infectious disease caused by Brucella, is often delayed or incomplete in traditional disease surveillance systems in China. Internet search engine data related to brucellosis can provide an economical and efficient complement to a conventional surveillance...

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Autores principales: Zhao, Chenhao, Yang, Yuhan, Wu, Songyu, Wu, Wenchao, Xue, Hetian, An, Kai, Zhen, Qing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125199/
https://www.ncbi.nlm.nih.gov/pubmed/32246053
http://dx.doi.org/10.1038/s41598-020-62517-7
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author Zhao, Chenhao
Yang, Yuhan
Wu, Songyu
Wu, Wenchao
Xue, Hetian
An, Kai
Zhen, Qing
author_facet Zhao, Chenhao
Yang, Yuhan
Wu, Songyu
Wu, Wenchao
Xue, Hetian
An, Kai
Zhen, Qing
author_sort Zhao, Chenhao
collection PubMed
description Reporting on brucellosis, a relatively rare infectious disease caused by Brucella, is often delayed or incomplete in traditional disease surveillance systems in China. Internet search engine data related to brucellosis can provide an economical and efficient complement to a conventional surveillance system because people tend to seek brucellosis-related health information from Baidu, the largest search engine in China. In this study, brucellosis incidence data reported by the CDC of China and Baidu index data were gathered to evaluate the relationship between them. We applied an autoregressive integrated moving average (ARIMA) model and an ARIMA model with Baidu search index data as the external variable (ARIMAX) to predict the incidence of brucellosis. The two models based on brucellosis incidence data were then compared, and the ARIMAX model performed better in all the measurements we applied. Our results illustrate that Baidu index data can enhance the traditional surveillance system to monitor and predict brucellosis epidemics in China.
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spelling pubmed-71251992020-04-08 Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China Zhao, Chenhao Yang, Yuhan Wu, Songyu Wu, Wenchao Xue, Hetian An, Kai Zhen, Qing Sci Rep Article Reporting on brucellosis, a relatively rare infectious disease caused by Brucella, is often delayed or incomplete in traditional disease surveillance systems in China. Internet search engine data related to brucellosis can provide an economical and efficient complement to a conventional surveillance system because people tend to seek brucellosis-related health information from Baidu, the largest search engine in China. In this study, brucellosis incidence data reported by the CDC of China and Baidu index data were gathered to evaluate the relationship between them. We applied an autoregressive integrated moving average (ARIMA) model and an ARIMA model with Baidu search index data as the external variable (ARIMAX) to predict the incidence of brucellosis. The two models based on brucellosis incidence data were then compared, and the ARIMAX model performed better in all the measurements we applied. Our results illustrate that Baidu index data can enhance the traditional surveillance system to monitor and predict brucellosis epidemics in China. Nature Publishing Group UK 2020-04-03 /pmc/articles/PMC7125199/ /pubmed/32246053 http://dx.doi.org/10.1038/s41598-020-62517-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Zhao, Chenhao
Yang, Yuhan
Wu, Songyu
Wu, Wenchao
Xue, Hetian
An, Kai
Zhen, Qing
Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title_full Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title_fullStr Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title_full_unstemmed Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title_short Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China
title_sort search trends and prediction of human brucellosis using baidu index data from 2011 to 2018 in china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125199/
https://www.ncbi.nlm.nih.gov/pubmed/32246053
http://dx.doi.org/10.1038/s41598-020-62517-7
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