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Comparison of Public Responses to Containment Measures During the Initial Outbreak and Resurgence of COVID-19 in China: Infodemiology Study.
Zhou, Xinyu; Song, Yi; Jiang, Hao; Wang, Qian; Qu, Zhiqiang; Zhou, Xiaoyu; Jit, Mark; Hou, Zhiyuan; Lin, Leesa.
  • Zhou X; School of Public Health, Fudan University, Shanghai, China.
  • Song Y; School of Public Health, Fudan University, Shanghai, China.
  • Jiang H; School of Public Health, Fudan University, Shanghai, China.
  • Wang Q; School of Public Health, Fudan University, Shanghai, China.
  • Qu Z; School of Public Health, Fudan University, Shanghai, China.
  • Zhou X; School of Public Health, Fudan University, Shanghai, China.
  • Jit M; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
  • Hou Z; School of Public Health, Fudan University, Shanghai, China.
  • Lin L; NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China.
J Med Internet Res ; 23(4): e26518, 2021 04 05.
Article in English | MEDLINE | ID: covidwho-1195981
ABSTRACT

BACKGROUND:

COVID-19 cases resurged worldwide in the second half of 2020. Not much is known about the changes in public responses to containment measures from the initial outbreak to resurgence. Monitoring public responses is crucial to inform policy measures to prepare for COVID-19 resurgence.

OBJECTIVE:

This study aimed to assess and compare public responses to containment measures during the initial outbreak and resurgence of COVID-19 in China.

METHODS:

We curated all COVID-19-related posts from Sina Weibo (China's version of Twitter) during the initial outbreak and resurgence of COVID-19 in Beijing, China. With a Python script, we constructed subsets of Weibo posts focusing on 3 containment

measures:

lockdown, the test-trace-isolate strategy, and suspension of gatherings. The Baidu open-source sentiment analysis model and latent Dirichlet allocation topic modeling, a widely used machine learning algorithm, were used to assess public engagement, sentiments, and frequently discussed topics on each containment measure.

RESULTS:

A total of 8,985,221 Weibo posts were curated. In China, the containment measures evolved from a complete lockdown for the general population during the initial outbreak to a more targeted response strategy for high-risk populations during COVID-19 resurgence. Between the initial outbreak and resurgence, the average daily proportion of Weibo posts with negative sentiments decreased from 57% to 47% for the lockdown, 56% to 51% for the test-trace-isolate strategy, and 55% to 48% for the suspension of gatherings. Among the top 3 frequently discussed topics on lockdown measures, discussions on containment measures accounted for approximately 32% in both periods, but those on the second-most frequently discussed topic shifted from the expression of negative emotions (11%) to its impacts on daily life or work (26%). The public expressed a high level of panic (21%) during the initial outbreak but almost no panic (1%) during resurgence. The more targeted test-trace-isolate measure received the most support (60%) among all 3 containment measures in the initial outbreak, and its support rate approached 90% during resurgence.

CONCLUSIONS:

Compared to the initial outbreak, the public expressed less engagement and less negative sentiments on containment measures and were more supportive toward containment measures during resurgence. Targeted test-trace-isolate strategies were more acceptable to the public. Our results indicate that when COVID-19 resurges, more targeted test-trace-isolate strategies for high-risk populations should be promoted to balance pandemic control and its impact on daily life and the economy.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Opinion / Communicable Disease Control / Social Media / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26518

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Public Opinion / Communicable Disease Control / Social Media / COVID-19 Type of study: Observational study / Prognostic study / Qualitative research / Randomized controlled trials Limits: Humans Country/Region as subject: Asia Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26518