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Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index

BACKGROUND: The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. OBJECTIVE: This study aims to use online search data (Baidu Index) to monitor...

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Detalles Bibliográficos
Autores principales: Gong, Xue, Han, Yangyang, Hou, Mengchi, Guo, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584450/
https://www.ncbi.nlm.nih.gov/pubmed/32960177
http://dx.doi.org/10.2196/23098
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author Gong, Xue
Han, Yangyang
Hou, Mengchi
Guo, Rui
author_facet Gong, Xue
Han, Yangyang
Hou, Mengchi
Guo, Rui
author_sort Gong, Xue
collection PubMed
description BACKGROUND: The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. OBJECTIVE: This study aims to use online search data (Baidu Index) to monitor the public’s attention and verify internet search engines’ function in public attention monitoring of public health emergencies. METHODS: We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention’s temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis. RESULTS: The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases. CONCLUSIONS: The national public’s demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public’s attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.
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spelling pubmed-75844502020-10-28 Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index Gong, Xue Han, Yangyang Hou, Mengchi Guo, Rui JMIR Public Health Surveill Original Paper BACKGROUND: The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. OBJECTIVE: This study aims to use online search data (Baidu Index) to monitor the public’s attention and verify internet search engines’ function in public attention monitoring of public health emergencies. METHODS: We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention’s temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis. RESULTS: The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases. CONCLUSIONS: The national public’s demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public’s attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic. JMIR Publications 2020-10-22 /pmc/articles/PMC7584450/ /pubmed/32960177 http://dx.doi.org/10.2196/23098 Text en ©Xue Gong, Yangyang Han, Mengchi Hou, Rui Guo. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 22.10.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Gong, Xue
Han, Yangyang
Hou, Mengchi
Guo, Rui
Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title_full Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title_fullStr Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title_full_unstemmed Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title_short Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index
title_sort online public attention during the early days of the covid-19 pandemic: infoveillance study based on baidu index
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584450/
https://www.ncbi.nlm.nih.gov/pubmed/32960177
http://dx.doi.org/10.2196/23098
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