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

被引:42
|
作者
Huang, Chunmei [1 ]
Xu, Xinjie [2 ]
Cai, Yuyang [3 ]
Ge, Qinmin [2 ]
Zeng, Guangwang [1 ,4 ]
Li, Xiaopan [5 ,6 ]
Zhang, Weide [7 ]
Ji, Chen [8 ]
Yang, Ling [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Dept Geriatr, 1665 Kongjiang Rd, Shanghai, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Med, Xinhua Hosp, Dept Emergency, Shanghai, Peoples R China
[3] Shanghai Jiao Tong Univ, Sch Med, Sch Publ Hlth, Shanghai, Peoples R China
[4] Hlth Ctr Nansheng Town, Wuzhishan, Peoples R China
[5] Ctr Dis Control & Prevent, Shanghai, Peoples R China
[6] Fudan Univ, Pudong Inst Prevent Med, Shanghai, Peoples R China
[7] Fudan Univ, Zhongshan Hosp, Big Data & Artificial Intelligence Ctr, Shanghai, Peoples R China
[8] Warwick Med Sch, Warwick Clin Trials Unit, Coventry, W Midlands, England
基金
中国国家自然科学基金;
关键词
SARS-CoV-2; COVID-19; coronavirus disease; social media; Sina Weibo; help; ZIKA VIRUS; EBOLA; DISEASE;
D O I
10.2196/19087
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
引用
收藏
页数:11
相关论文
共 50 条
  • [1] An Ecological Model Analysis of COVID-19 Social Media Posts
    Grossman, Suzanne
    Alber, Julia M.
    Henry, Dayna S.
    Askay, David
    Glanz, Hunter
    Marts, Erika
    Ostrander, Anna
    [J]. JOURNAL OF CONSUMER HEALTH ON THE INTERNET, 2022, 26 (03) : 248 - 258
  • [2] A retrospective analysis of social media posts pertaining to COVID-19 vaccination side effects
    Lentzen, Max-Philipp
    Huebenthal, Viola
    Kaiser, Rolf
    Kreppel, Matthias
    Zoeller, Joachim E.
    Zirk, Matthias
    [J]. VACCINE, 2022, 40 (01) : 43 - 51
  • [3] The Impact of the COVID-19 Epidemic on Orthodontic Patients in China: An Analysis of Posts on Weibo
    Guo, Feiyang
    Tang, Bojun
    Qin, Danchen
    Zhao, Tingting
    Su, Yu-xiong
    McGrath, Colman
    Hua, Fang
    He, Hong
    [J]. FRONTIERS IN MEDICINE, 2020, 7
  • [4] Characteristics of Misinformation Spreading on Social Media During the COVID-19 Outbreak in China: A Descriptive Analysis
    Chen, Kelin
    Luo, Yuni
    Hu, Anyang
    Zhao, Ji
    Zhang, Liwei
    [J]. RISK MANAGEMENT AND HEALTHCARE POLICY, 2021, 14 : 1869 - 1879
  • [5] Social representations, media, and iconography: A semiodiscursive analysis of Facebook posts related to the COVID-19 pandemic
    Cohen, Golda
    Bessin, Mathieu
    Gaymard, Sandrine
    [J]. EUROPEAN JOURNAL OF COMMUNICATION, 2022, 37 (06) : 629 - 645
  • [6] Impact of the COVID-19 Pandemic on Disordered Eating Behavior: Qualitative Analysis of Social Media Posts
    Nutley, Sara K.
    Falise, Alyssa M.
    Henderson, Rebecca
    Apostolou, Vasiliki
    Mathews, Carol A.
    Striley, Catherine W.
    [J]. JMIR MENTAL HEALTH, 2021, 8 (01):
  • [7] Sex Workers' Lived Experiences With COVID-19 on Social Media: Content Analysis of Twitter Posts
    Al-Rawi, Ahmed
    Zemenchik, Kiana
    [J]. JMIR FORMATIVE RESEARCH, 2022, 6 (07)
  • [8] Public moral motivation during the COVID-19 pandemic: Analysis of posts on Chinese social media
    Zhao, Liang
    Ding, Xiaojun
    Yu, Feng
    [J]. SOCIAL BEHAVIOR AND PERSONALITY, 2020, 48 (11):
  • [9] Long-term Effects of the COVID-19 Pandemic on Public Sentiments in Mainland China: Sentiment Analysis of Social Media Posts
    Tan, Hao
    Peng, Sheng-Lan
    Zhu, Chun-Peng
    You, Zuo
    Miao, Ming-Cheng
    Kuai, Shu-Guang
    [J]. JOURNAL OF MEDICAL INTERNET RESEARCH, 2021, 23 (08)
  • [10] Effect of visual imagery in COVID-19 social media posts on users’ perception
    Al-nuwaiser, Waleed M.
    [J]. PeerJ Computer Science, 2022, 8