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Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts

BACKGROUND: In December 2019, pneumonia cases of unknown origin were reported in Wuhan City, Hubei Province, China. Identified as the coronavirus disease (COVID-19), the number of cases grew rapidly by human-to-human transmission in Wuhan. Social media, especially Sina Weibo (a major Chinese microbl...

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Autores principales: Huang, Chunmei, Xu, Xinjie, Cai, Yuyang, Ge, Qinmin, Zeng, Guangwang, Li, Xiaopan, Zhang, Weide, Ji, Chen, Yang, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236610/
https://www.ncbi.nlm.nih.gov/pubmed/32401210
http://dx.doi.org/10.2196/19087
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author Huang, Chunmei
Xu, Xinjie
Cai, Yuyang
Ge, Qinmin
Zeng, Guangwang
Li, Xiaopan
Zhang, Weide
Ji, Chen
Yang, Ling
author_facet Huang, Chunmei
Xu, Xinjie
Cai, Yuyang
Ge, Qinmin
Zeng, Guangwang
Li, Xiaopan
Zhang, Weide
Ji, Chen
Yang, Ling
author_sort Huang, Chunmei
collection PubMed
description BACKGROUND: In December 2019, pneumonia cases of unknown origin were reported in Wuhan City, Hubei Province, China. Identified as the coronavirus disease (COVID-19), the number of cases grew rapidly by human-to-human transmission in Wuhan. Social media, especially Sina Weibo (a major Chinese microblogging social media site), has become an important platform for the public to obtain information and seek help. OBJECTIVE: This study aims to analyze the characteristics of suspected or laboratory-confirmed COVID-19 patients who asked for help on Sina Weibo. METHODS: We conducted data mining on Sina Weibo and extracted the data of 485 patients who presented with clinical symptoms and imaging descriptions of suspected or laboratory-confirmed cases of COVID-19. In total, 9878 posts seeking help on Sina Weibo from February 3 to 20, 2020 were analyzed. We used a descriptive research methodology to describe the distribution and other epidemiological characteristics of patients with suspected or laboratory-confirmed SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection. The distance between patients’ home and the nearest designated hospital was calculated using the geographic information system ArcGIS. RESULTS: All patients included in this study who sought help on Sina Weibo lived in Wuhan, with a median age of 63.0 years (IQR 55.0-71.0). Fever (408/485, 84.12%) was the most common symptom. Ground-glass opacity (237/314, 75.48%) was the most common pattern on chest computed tomography; 39.67% (167/421) of families had suspected and/or laboratory-confirmed family members; 36.58% (154/421) of families had 1 or 2 suspected and/or laboratory-confirmed members; and 70.52% (232/329) of patients needed to rely on their relatives for help. The median time from illness onset to real-time reverse transcription-polymerase chain reaction (RT-PCR) testing was 8 days (IQR 5.0-10.0), and the median time from illness onset to online help was 10 days (IQR 6.0-12.0). Of 481 patients, 32.22% (n=155) lived more than 3 kilometers away from the nearest designated hospital. CONCLUSIONS: Our findings show that patients seeking help on Sina Weibo lived in Wuhan and most were elderly. Most patients had fever symptoms, and ground-glass opacities were noted in chest computed tomography. The onset of the disease was characterized by family clustering and most families lived far from the designated hospital. Therefore, we recommend the following: (1) the most stringent centralized medical observation measures should be taken to avoid transmission in family clusters; and (2) social media can help these patients get early attention during Wuhan’s lockdown. These findings can help the government and the health department identify high-risk patients and accelerate emergency responses following public demands for help.
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spelling pubmed-72366102020-06-01 Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts Huang, Chunmei Xu, Xinjie Cai, Yuyang Ge, Qinmin Zeng, Guangwang Li, Xiaopan Zhang, Weide Ji, Chen Yang, Ling J Med Internet Res Original Paper BACKGROUND: In December 2019, pneumonia cases of unknown origin were reported in Wuhan City, Hubei Province, China. Identified as the coronavirus disease (COVID-19), the number of cases grew rapidly by human-to-human transmission in Wuhan. Social media, especially Sina Weibo (a major Chinese microblogging social media site), has become an important platform for the public to obtain information and seek help. OBJECTIVE: This study aims to analyze the characteristics of suspected or laboratory-confirmed COVID-19 patients who asked for help on Sina Weibo. METHODS: We conducted data mining on Sina Weibo and extracted the data of 485 patients who presented with clinical symptoms and imaging descriptions of suspected or laboratory-confirmed cases of COVID-19. In total, 9878 posts seeking help on Sina Weibo from February 3 to 20, 2020 were analyzed. We used a descriptive research methodology to describe the distribution and other epidemiological characteristics of patients with suspected or laboratory-confirmed SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) infection. The distance between patients’ home and the nearest designated hospital was calculated using the geographic information system ArcGIS. RESULTS: All patients included in this study who sought help on Sina Weibo lived in Wuhan, with a median age of 63.0 years (IQR 55.0-71.0). Fever (408/485, 84.12%) was the most common symptom. Ground-glass opacity (237/314, 75.48%) was the most common pattern on chest computed tomography; 39.67% (167/421) of families had suspected and/or laboratory-confirmed family members; 36.58% (154/421) of families had 1 or 2 suspected and/or laboratory-confirmed members; and 70.52% (232/329) of patients needed to rely on their relatives for help. The median time from illness onset to real-time reverse transcription-polymerase chain reaction (RT-PCR) testing was 8 days (IQR 5.0-10.0), and the median time from illness onset to online help was 10 days (IQR 6.0-12.0). Of 481 patients, 32.22% (n=155) lived more than 3 kilometers away from the nearest designated hospital. CONCLUSIONS: Our findings show that patients seeking help on Sina Weibo lived in Wuhan and most were elderly. Most patients had fever symptoms, and ground-glass opacities were noted in chest computed tomography. The onset of the disease was characterized by family clustering and most families lived far from the designated hospital. Therefore, we recommend the following: (1) the most stringent centralized medical observation measures should be taken to avoid transmission in family clusters; and (2) social media can help these patients get early attention during Wuhan’s lockdown. These findings can help the government and the health department identify high-risk patients and accelerate emergency responses following public demands for help. JMIR Publications 2020-05-17 /pmc/articles/PMC7236610/ /pubmed/32401210 http://dx.doi.org/10.2196/19087 Text en ©Chunmei Huang, Xinjie Xu, Yuyang Cai, Qinmin Ge, Guangwang Zeng, Xiaopan Li, Weide Zhang, Chen Ji, Ling Yang. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 17.05.2020. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Huang, Chunmei
Xu, Xinjie
Cai, Yuyang
Ge, Qinmin
Zeng, Guangwang
Li, Xiaopan
Zhang, Weide
Ji, Chen
Yang, Ling
Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title_full Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title_fullStr Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title_full_unstemmed Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title_short Mining the Characteristics of COVID-19 Patients in China: Analysis of Social Media Posts
title_sort mining the characteristics of covid-19 patients in china: analysis of social media posts
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236610/
https://www.ncbi.nlm.nih.gov/pubmed/32401210
http://dx.doi.org/10.2196/19087
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