Literature DB >> 32241328

Limited Early Warnings and Public Attention to Coronavirus Disease 2019 in China, January-February, 2020: A Longitudinal Cohort of Randomly Sampled Weibo Users.

Yuner Zhu1, King-Wa Fu1, Karen A Grépin2, Hai Liang3, Isaac Chun-Hai Fung4.   

Abstract

OBJECTIVE: Awareness and attentiveness have implications for the acceptance and adoption of disease prevention and control measures. Social media posts provide a record of the public's attention to an outbreak. To measure the attention of Chinese netizens to coronavirus disease 2019 (COVID-19), a pre-established nationally representative cohort of Weibo users was searched for COVID-19-related key words in their posts.
METHODS: COVID-19-related posts (N = 1101) were retrieved from a longitudinal cohort of 52 268 randomly sampled Weibo accounts (December 31, 2019-February 12, 2020).
RESULTS: Attention to COVID-19 was limited prior to China openly acknowledging human-to-human transmission on January 20. Following this date, attention quickly increased and has remained high over time. Particularly high levels of social media traffic appeared around when Wuhan was first placed in quarantine (January 23-24, 8-9% of the overall posts), when a scandal associated with the Red Cross Society of China occurred (February 1, 8%), and, following the death of Dr Li Wenliang (February 6-7, 11%), one of the whistleblowers who was reprimanded by the Chinese police in early January for discussing this outbreak online.
CONCLUSION: Limited early warnings represent missed opportunities to engage citizens earlier in the outbreak. Governments should more proactively communicate early warnings to the public in a transparent manner.

Entities:  

Keywords:  Weibo; awareness; coronavirus; health communication; social media

Year:  2020        PMID: 32241328      PMCID: PMC7171227          DOI: 10.1017/dmp.2020.68

Source DB:  PubMed          Journal:  Disaster Med Public Health Prep        ISSN: 1935-7893            Impact factor:   1.385


Since December 2019, the world witnessed an epidemic of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). After cases of coronavirus disease 2019 (COVID-19) appeared in the city of Wuhan, local health authorities made a public announcement and China notified the World Health Organization about the outbreak on December 31, 2019.[1] In a matter of weeks, tens of thousands of cases would appear throughout China and in many countries around the world. In a tightly controlled media environment, it is unclear when regular Chinese citizens became aware of the outbreak and if aware, how much attention they paid to it. Awareness and attentiveness may have implications for the acceptance and adoption of prevention and control measures. To measure the attention of Chinese netizens to COVID-19, we used a pre-established nationally representative cohort of randomly sampled Weibo users and searched for COVID-19-related key words in their posts.

METHODS

Sina Weibo is the largest microblog service provider in mainland China, that is, China’s equivalent of Twitter. The social media platform had 497 million monthly active users as of September 2019.[2] The data used herein were collected by Weiboscope, a research project led by coauthor KWF. Since 2010, the research team has been collecting the social media data through Sina Weibo’s Open Application Programming Interface by sampling a list of high-profile users and random users, whose posts are programmatically retrieved every 15–20 minutes by a cluster of computer servers.[3] If a once-published post is found to be absent in the next retrieval of the user’s timeline, an additional request is made to confirm whether the post is truly censored, that is, return of an error message of “permission denied” indicating a censored message.[3] The current study analyzed the posts from 52 268 randomly sampled accounts in the Weiboscope database, whose 10-digit unique user identity codes were randomly selected in 2015 and their published posts have been longitudinally recorded. This cohort constitutes a representative sample of the whole user population of Weibo.[4] We compiled a priori a list of key words in simplified Chinese characters that were pertinent to the COVID-19 outbreak in China. The key word list was checked and confirmed by all authors, including bilingual epidemiologists and communication scientists, to be sufficiently inclusive and specific (see Supplementary Technical Appendix). The time frame of our study was from December 31, 2019 through February 12, 2020. A daily percentage was computed by dividing the daily total number of COVID-19-related posts by the daily total number of published posts in the samples (Table 1, Figure 1). Daily cumulative counts of confirmed COVID-19 cases in mainland China were obtained from press releases published by the National Health Commission, Wuhan Municipal Health Commission, and Guangdong Provincial Health Commission. Both daily series were plotted on a time trend diagram (see Figure 1).
TABLE 1

Number and Percentage of COVID-19-Related Weibo Posts With Selected Key Words

Key WordEnglish TranslationNumber[*]Percentage[**]
疫情epidemic situation38334.79%
口罩mask25923.52%
病毒virus23020.89%
肺炎pneumonia19117.35%
冠状coronavirus13211.99%
感染infected11610.54%
确诊confirmed case1009.08%
隔离quarantine665.99%
防疫combat the outbreak383.45%
传染infection363.27%
新冠new coronavirus363.27%
钟南山Zhong Nanshan302.72%
封城lockdown282.54%
非典SARS272.45%
N95N95262.36%
李文亮Li Wenliang262.36%
蝙蝠bat191.73%
防护服hazmat suit171.54%
卫健委health commission111.00%
世卫WHO (abbreviated)100.91%
重症severe80.73%
疾控中心Center(s) for Disease Control and Prevention70.64%
李兰娟Li Lanjuan70.64%
流行病epidemiology60.55%
华南海鲜市场Huanan Seafood Market50.45%
人传人human-to-human transmission50.45%
管轶Guan Yi40.36%
世界卫生组织World Health Organization40.36%
消毒液bleach30.27%
洗手液hand sanitizer30.27%
危重critically ill30.27%
张文宏Zhang Wenhong30.27%
CDCCenter(s) for Disease Control and Prevention30.27%
高福Gao Fu (George F. Gao)20.18%
穿山甲pangolin20.18%
粪口传播fecal–oral transmission20.18%
WHOWorld Health Organization20.18%
飞沫传播droplets transmission20.18%
疑似病例suspected case20.18%
潜伏期incubation period10.09%

Key words may be occurring in the same piece of posts. Therefore, the totals in the numbers column will exceed 1101 and the totals in percentages column will exceed 100%.

Percentage of the population of posts identified with at least 1 of the given key words (N = 1101).

FIGURE 1

Time Series of Percentage of Daily Weibo Posts Pertinent to COVID-19 Posted by a Cohort of Randomly Sampled Weibo Users, and the Daily Cumulative Number of Confirmed Cases From December 31, 2019, Through February 12, 2020.

Number and Percentage of COVID-19-Related Weibo Posts With Selected Key Words Key words may be occurring in the same piece of posts. Therefore, the totals in the numbers column will exceed 1101 and the totals in percentages column will exceed 100%. Percentage of the population of posts identified with at least 1 of the given key words (N = 1101). Time Series of Percentage of Daily Weibo Posts Pertinent to COVID-19 Posted by a Cohort of Randomly Sampled Weibo Users, and the Daily Cumulative Number of Confirmed Cases From December 31, 2019, Through February 12, 2020.

RESULTS AND DISCUSSION

A total of 1101 Weibo posts pertinent to COVID-19 were identified. Table 1 shows the key word frequency in the published posts made by the random user samples in the study period. We found little evidence that Chinese netizens paid much attention to the outbreak before January 20 when the Chinese Government for the first time openly acknowledged that human-to-human transmission of the virus was happening and when China initiated nationwide reporting on the outbreak.[5,6] Our data show that, following this date, attention to the outbreak quickly increased and has remained high over time. Particularly high levels of social media traffic also appeared around when Wuhan was first placed in quarantine (January 23–24, 8–9% of the overall posts), when a scandal associated with the Red Cross Society of China occurred (February 1, 8%), and, following the death of Dr Li Wenliang (February 6–7, 11%), 1 of the whistleblowers who was reprimanded by the Chinese police in early January for discussing this outbreak on WeChat groups.[7] See Technical Appendix for sample posts for each of these events.

Limitations

This study has its limitations. First, our data collection system is not able to capture social media posts that were filtered by Sina Weibo’s interface or disappeared within the data retrieval intervals. Only 8 post-publication censored posts were detected among the random samples in the study period. The authors cannot completely rule out the impact of Internet censorship in China. Second, Weibo is only 1 of several popular social media platforms in mainland China. This study does not cover other platforms, such as WeChat.

CONCLUSION

Low levels of attention to the outbreak among Chinese citizens in early January may represent a missed window of opportunity to contain the outbreak. Given that the adoption of personal protective behaviors has been shown to be associated with trust in government and that large-scale social distancing measures have been put in place in many parts of China,[8,9] ensuring that citizens are aware of the true severity of the outbreak in its early stages is likely to increase acceptance and compliance with prevention and control measures. Governments worldwide should take note of lessons learned in China and should more proactively communicate early warnings to the public in a transparent manner.
  11 in total

Review 1.  #WuhanDiary and #WuhanLockdown: gendered posting patterns and behaviours on Weibo during the COVID-19 pandemic.

Authors:  Connie Cai Ru Gan; Shuo Feng; Huiyun Feng; King-Wa Fu; Sara E Davies; Karen A Grépin; Rosemary Morgan; Julia Smith; Clare Wenham
Journal:  BMJ Glob Health       Date:  2022-04

2.  Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.

Authors:  Cuihua Shen; Anfan Chen; Chen Luo; Jingwen Zhang; Bo Feng; Wang Liao
Journal:  J Med Internet Res       Date:  2020-05-28       Impact factor: 5.428

3.  Effects of Internet Hospital Consultations on Psychological Burdens and Disease Knowledge During the Early Outbreak of COVID-19 in China: Cross-Sectional Survey Study.

Authors:  Lin Li; Gang Liu; Weiguo Xu; Yun Zhang; Mei He
Journal:  J Med Internet Res       Date:  2020-08-04       Impact factor: 5.428

4.  Social Media Use and Mental Health during the COVID-19 Pandemic: Moderator Role of Disaster Stressor and Mediator Role of Negative Affect.

Authors:  Nan Zhao; Guangyu Zhou
Journal:  Appl Psychol Health Well Being       Date:  2020-09-17

5.  Attention dynamics on the Chinese social media Sina Weibo during the COVID-19 pandemic.

Authors:  Hao Cui; János Kertész
Journal:  EPJ Data Sci       Date:  2021-02-03       Impact factor: 3.184

Review 6.  What social media told us in the time of COVID-19: a scoping review.

Authors:  Shu-Feng Tsao; Helen Chen; Therese Tisseverasinghe; Yang Yang; Lianghua Li; Zahid A Butt
Journal:  Lancet Digit Health       Date:  2021-01-28

7.  Network Structure and Community Evolution Online: Behavioral and Emotional Changes in Response to COVID-19.

Authors:  Fan Fang; Tong Wang; Suoyi Tan; Saran Chen; Tao Zhou; Wei Zhang; Qiang Guo; Jianguo Liu; Petter Holme; Xin Lu
Journal:  Front Public Health       Date:  2022-01-11

8.  Social media mining under the COVID-19 context: Progress, challenges, and opportunities.

Authors:  Xiao Huang; Siqin Wang; Mengxi Zhang; Tao Hu; Alexander Hohl; Bing She; Xi Gong; Jianxin Li; Xiao Liu; Oliver Gruebner; Regina Liu; Xiao Li; Zhewei Liu; Xinyue Ye; Zhenlong Li
Journal:  Int J Appl Earth Obs Geoinf       Date:  2022-08-19

9.  Use of Facebook by Academic Medical Centers in Taiwan During the COVID-19 Pandemic: Observational Study.

Authors:  Wei-Min Chu; Gow-Jen Shieh; Shi-Liang Wu; Wayne Huey-Herng Sheu
Journal:  J Med Internet Res       Date:  2020-11-20       Impact factor: 5.428

Review 10.  Learning from combination HIV prevention programmes to face COVID-19 emerging pandemic.

Authors:  Ricardo Palacios; Augusto Mathias
Journal:  Colomb Med (Cali)       Date:  2020-06-30
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