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      What triggers online help-seeking retransmission during the COVID-19 period? Empirical evidence from Chinese social media

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      Author(s): 1 , 2 , 3 , * , 4 , * , 5
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      Publication date (Electronic):
      Journal: PLoS ONE
      Publisher: Public Library of Science

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          Abstract

          The past nine months witnessed COVID-19's fast-spreading at the global level. Limited by medical resources shortage and uneven facilities distribution, online help-seeking becomes an essential approach to cope with public health emergencies for many ordinaries. This study explores the driving forces behind the retransmission of online help-seeking posts. We built an analytical framework that emphasized content characteristics, including information completeness, proximity, support seeking type, disease severity, and emotion of help-seeking messages. A quantitative content analysis was conducted with a probability sample consisting of 727 posts. The results illustrate the importance of individual information completeness, high proximity, instrumental support seeking. This study also demonstrates slight inconformity with the severity principle but stresses the power of anger in help-seeking messages dissemination. As one of the first online help-seeking diffusion analyses in the COVID-19 period, our research provides a reference for constructing compelling and effective help-seeking posts during a particular period. It also reveals further possibilities for harnessing social media’s power to promote reciprocal and cooperative actions as a response to this deepening global concern.

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          Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study

          Joseph Wu, Kathy Leung, Gabriel Leung (2020)
          Summary Background Since Dec 31, 2019, the Chinese city of Wuhan has reported an outbreak of atypical pneumonia caused by the 2019 novel coronavirus (2019-nCoV). Cases have been exported to other Chinese cities, as well as internationally, threatening to trigger a global outbreak. Here, we provide an estimate of the size of the epidemic in Wuhan on the basis of the number of cases exported from Wuhan to cities outside mainland China and forecast the extent of the domestic and global public health risks of epidemics, accounting for social and non-pharmaceutical prevention interventions. Methods We used data from Dec 31, 2019, to Jan 28, 2020, on the number of cases exported from Wuhan internationally (known days of symptom onset from Dec 25, 2019, to Jan 19, 2020) to infer the number of infections in Wuhan from Dec 1, 2019, to Jan 25, 2020. Cases exported domestically were then estimated. We forecasted the national and global spread of 2019-nCoV, accounting for the effect of the metropolitan-wide quarantine of Wuhan and surrounding cities, which began Jan 23–24, 2020. We used data on monthly flight bookings from the Official Aviation Guide and data on human mobility across more than 300 prefecture-level cities in mainland China from the Tencent database. Data on confirmed cases were obtained from the reports published by the Chinese Center for Disease Control and Prevention. Serial interval estimates were based on previous studies of severe acute respiratory syndrome coronavirus (SARS-CoV). A susceptible-exposed-infectious-recovered metapopulation model was used to simulate the epidemics across all major cities in China. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credibile interval (CrI). Findings In our baseline scenario, we estimated that the basic reproductive number for 2019-nCoV was 2·68 (95% CrI 2·47–2·86) and that 75 815 individuals (95% CrI 37 304–130 330) have been infected in Wuhan as of Jan 25, 2020. The epidemic doubling time was 6·4 days (95% CrI 5·8–7·1). We estimated that in the baseline scenario, Chongqing, Beijing, Shanghai, Guangzhou, and Shenzhen had imported 461 (95% CrI 227–805), 113 (57–193), 98 (49–168), 111 (56–191), and 80 (40–139) infections from Wuhan, respectively. If the transmissibility of 2019-nCoV were similar everywhere domestically and over time, we inferred that epidemics are already growing exponentially in multiple major cities of China with a lag time behind the Wuhan outbreak of about 1–2 weeks. Interpretation Given that 2019-nCoV is no longer contained within Wuhan, other major Chinese cities are probably sustaining localised outbreaks. Large cities overseas with close transport links to China could also become outbreak epicentres, unless substantial public health interventions at both the population and personal levels are implemented immediately. Independent self-sustaining outbreaks in major cities globally could become inevitable because of substantial exportation of presymptomatic cases and in the absence of large-scale public health interventions. Preparedness plans and mitigation interventions should be readied for quick deployment globally. Funding Health and Medical Research Fund (Hong Kong, China).
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            Using social and behavioural science to support COVID-19 pandemic response

            Jay Bavel, Katherine Baicker, Paulo S Boggio … (2020)
            The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.
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              Fair Allocation of Scarce Medical Resources in the Time of Covid-19

              Ezekiel J. Emanuel, Govind Persad, Ross Upshur … (2020)
              Article 0 comments Cited 1338 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Chen Luo:
                ORCID: https://orcid.org/0000-0002-9736-0533
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Yuru Li: Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Writing – original draft
                Anfan Chen:
                ORCID: https://orcid.org/0000-0002-7406-0415
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Yulong Tang: Role: ConceptualizationRole: Writing – original draft
                Valerio Capraro: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 3 November 2020
                Publication date Collection: 2020
                Publication date PMC-release: 3 November 2020
                Volume: 15
                Issue: 11
                Electronic Location Identifier: e0241465
                Affiliations
                [1 ] School of Journalism and Communication, Tsinghua University, Beijing, China
                [2 ] Department of Communication, University of California, Davis, Davis, California, United States of America
                [3 ] Centre for Media, Communication & Information Research, University of Bremen, Bremen, Germany
                [4 ] School of Humanity and Social Science, University of Science and Technology of China, Hefei, Anhui, China
                [5 ] Institute of Communication Studies, Communication University of China, Beijing, China
                Middlesex University, UNITED KINGDOM
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-9736-0533
                https://orcid.org/0000-0002-7406-0415
                Article
                Publisher ID: PONE-D-20-18830
                DOI: 10.1371/journal.pone.0241465
                PMC ID: 7608884
                PubMed ID: 33141860
                SO-VID: 8f6d28f8-3d21-4ca2-a25a-1a883646f5f6
                Copyright © © 2020 Luo et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 19 June 2020
                Date accepted : 16 October 2020
                Page count
                Figures: 1, Tables: 3, Pages: 17
                Funding
                Funded by: Science Popularization and Risk Communication of Transgenic Biotechnologies Project
                Award ID: 2016ZX08015002
                Award Recipient :
                ORCID: https://orcid.org/0000-0002-7406-0415
                Funded by: funder-id http://dx.doi.org/10.13039/501100004543, China Scholarship Council;
                Award ID: 201906210115
                Award Recipient :
                ORCID: https://orcid.org/0000-0002-9736-0533
                This study is supported by the Science Popularization and Risk Communication of Transgenic Biotechnologies Project (Grant code: 2016ZX08015002) to CL and AC, China Scholarship (Grant code: 201906210115) to CL, the 25th department funding of USTC (Grant code: DA2110251001) to AC, 2019 New Humanities Funding of USTC (Grant code: YD2110002015) to AC. The funders had no role in the study design, data collection, analysis, decision to publish, or manuscript preparation.
                Categories
                Subject: Research Article
                Subject: Biology and Life Sciences
                Subject: Psychology
                Subject: Emotions
                Subject: Social Sciences
                Subject: Psychology
                Subject: Emotions
                Subject: Medicine and Health Sciences
                Subject: Medical Conditions
                Subject: Infectious Diseases
                Subject: Viral Diseases
                Subject: Covid 19
                Subject: Social Sciences
                Subject: Sociology
                Subject: Communications
                Subject: Social Communication
                Subject: Social Media
                Subject: Computer and Information Sciences
                Subject: Network Analysis
                Subject: Social Networks
                Subject: Social Media
                Subject: Social Sciences
                Subject: Sociology
                Subject: Social Networks
                Subject: Social Media
                Subject: Social Sciences
                Subject: Sociology
                Subject: Communications
                Subject: Social Communication
                Subject: Biology and Life Sciences
                Subject: Psychology
                Subject: Emotions
                Subject: Fear
                Subject: Social Sciences
                Subject: Psychology
                Subject: Emotions
                Subject: Fear
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Virus Testing
                Subject: Medicine and Health Sciences
                Subject: Epidemiology
                Subject: Pandemics
                Subject: Medicine and Health Sciences
                Subject: Critical Care and Emergency Medicine
                Custom metadata
                Data Availability Data are available via figshare: https://doi.org/10.6084/m9.figshare.12743726.v1 Statistical commands are also available via figshare: https://doi.org/10.6084/m9.figshare.12743750.v1
                Outbreaks COVID-19

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

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