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Early detection of an epidemic erythromelalgia outbreak using Baidu search data

Dozens of epidemic erythromelalgia (EM) outbreaks have been reported in China since the mid-twentieth century, and the most recent happened in Foshan City, Guangdong Province early 2014. This study compared the daily case counts of this recent epidemic EM outbreak from February 11 to March 3 with Ba...

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Autores principales: Gu, Yuzhou, Chen, Fengling, Liu, Tao, Lv, Xiaojuan, Shao, Zhaoming, Lin, Hualiang, Liang, Chaobin, Zeng, Weilin, Xiao, Jianpeng, Zhang, Yonghui, Huang, Cunrui, Rutherford, Shannon, Ma, Wenjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517510/
https://www.ncbi.nlm.nih.gov/pubmed/26218589
http://dx.doi.org/10.1038/srep12649
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author Gu, Yuzhou
Chen, Fengling
Liu, Tao
Lv, Xiaojuan
Shao, Zhaoming
Lin, Hualiang
Liang, Chaobin
Zeng, Weilin
Xiao, Jianpeng
Zhang, Yonghui
Huang, Cunrui
Rutherford, Shannon
Ma, Wenjun
author_facet Gu, Yuzhou
Chen, Fengling
Liu, Tao
Lv, Xiaojuan
Shao, Zhaoming
Lin, Hualiang
Liang, Chaobin
Zeng, Weilin
Xiao, Jianpeng
Zhang, Yonghui
Huang, Cunrui
Rutherford, Shannon
Ma, Wenjun
author_sort Gu, Yuzhou
collection PubMed
description Dozens of epidemic erythromelalgia (EM) outbreaks have been reported in China since the mid-twentieth century, and the most recent happened in Foshan City, Guangdong Province early 2014. This study compared the daily case counts of this recent epidemic EM outbreak from February 11 to March 3 with Baidu search data for the same period. After keyword selection, filtering and composition, the most correlated lag of the EM Search Index was used for comparison and linear regression model development. This study also explored the spatial distribution of epidemic EM in China during this period based on EM Search Index. The EM Search Index at lag 2 was most significantly associated with daily case counts in Foshan (ρ = 0.863, P < 0.001). It captured an upward trend in the outbreak about one week ahead of official report and the linear regression analysis indicated that every 1.071 increase in the EM Search Index reflected a rise of 1 EM cases 2 days earlier. The spatial analysis found that the number of EM Search Indexes increased in the middle of Guangdong Province and South China during the outbreak period. The EM Search Index may be a good early indicator of an epidemic EM outbreak.
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spelling pubmed-45175102015-07-30 Early detection of an epidemic erythromelalgia outbreak using Baidu search data Gu, Yuzhou Chen, Fengling Liu, Tao Lv, Xiaojuan Shao, Zhaoming Lin, Hualiang Liang, Chaobin Zeng, Weilin Xiao, Jianpeng Zhang, Yonghui Huang, Cunrui Rutherford, Shannon Ma, Wenjun Sci Rep Article Dozens of epidemic erythromelalgia (EM) outbreaks have been reported in China since the mid-twentieth century, and the most recent happened in Foshan City, Guangdong Province early 2014. This study compared the daily case counts of this recent epidemic EM outbreak from February 11 to March 3 with Baidu search data for the same period. After keyword selection, filtering and composition, the most correlated lag of the EM Search Index was used for comparison and linear regression model development. This study also explored the spatial distribution of epidemic EM in China during this period based on EM Search Index. The EM Search Index at lag 2 was most significantly associated with daily case counts in Foshan (ρ = 0.863, P < 0.001). It captured an upward trend in the outbreak about one week ahead of official report and the linear regression analysis indicated that every 1.071 increase in the EM Search Index reflected a rise of 1 EM cases 2 days earlier. The spatial analysis found that the number of EM Search Indexes increased in the middle of Guangdong Province and South China during the outbreak period. The EM Search Index may be a good early indicator of an epidemic EM outbreak. Nature Publishing Group 2015-07-28 /pmc/articles/PMC4517510/ /pubmed/26218589 http://dx.doi.org/10.1038/srep12649 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Gu, Yuzhou
Chen, Fengling
Liu, Tao
Lv, Xiaojuan
Shao, Zhaoming
Lin, Hualiang
Liang, Chaobin
Zeng, Weilin
Xiao, Jianpeng
Zhang, Yonghui
Huang, Cunrui
Rutherford, Shannon
Ma, Wenjun
Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title_full Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title_fullStr Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title_full_unstemmed Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title_short Early detection of an epidemic erythromelalgia outbreak using Baidu search data
title_sort early detection of an epidemic erythromelalgia outbreak using baidu search data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4517510/
https://www.ncbi.nlm.nih.gov/pubmed/26218589
http://dx.doi.org/10.1038/srep12649
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