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      Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation

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      , PhD, MD 1 , , MD, PhD 2 , , MSc 3 , , MSc 4 , , , MSc 5 , , PhD 6 , , MSc 7 , , PhD 8 , , MSc 9 , , MSc 10 , , MSc 11 , , MSc 11 , , MPH, JD, LLM 11 , , MD 4 , , MSc, , PhD 12 , , PhD 13 , 14 , 15 , 16 , , PhD 17 , , MA, JD 18 , , PhD 18 , , MSc 19 , , PhD 11
      (Reviewer)
      Journal of Medical Internet Research
      JMIR Publications
      COVID-19, infodemic, knowledge translation, message amplification, misinformation, information-seeking behavior, access to information, information literacy, communications media, internet, risk communication, evidence synthesis

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          Abstract

          Background

          An infodemic is an overabundance of information—some accurate and some not—that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it.

          Objective

          A World Health Organization (WHO) technical consultation on responding to the infodemic related to the coronavirus disease (COVID-19) pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management.

          Methods

          A group of policy makers, public health professionals, researchers, students, and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations, and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods, and technologies. A total of 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework.

          Results

          The analysis team distilled the suggestions into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behavior-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that these actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions, and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response, and to inform risk mitigation, and be enhanced through data science and sociobehavioral and other research.

          Conclusions

          The first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic, and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.

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          Most cited references10

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          WHO Coronavirus Disease (COVID-19) Dashboard

          (2020)
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            Bots increase exposure to negative and inflammatory content in online social systems

            Significance Social media can deeply influence reality perception, affecting millions of people’s voting behavior. Hence, maneuvering opinion dynamics by disseminating forged content over online ecosystems is an effective pathway for social hacking. We propose a framework for discovering such a potentially dangerous behavior promoted by automatic users, also called “bots,” in online social networks. We provide evidence that social bots target mainly human influencers but generate semantic content depending on the polarized stance of their targets. During the 2017 Catalan referendum, used as a case study, social bots generated and promoted violent content aimed at Independentists, ultimately exacerbating social conflict online. Our results open challenges for detecting and controlling the influence of such content on society.
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              Coronavirus disease 2019 (COVID-19) Situation Report – 72

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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J. Med. Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                June 2020
                26 June 2020
                26 June 2020
                : 22
                : 6
                : e19659
                Affiliations
                [1 ] International Health Policy Program Ministry of Public Health Nonthaburi Thailand
                [2 ] Directorate for Health Information and Research Ministry for Health Valetta Malta
                [3 ] High Impact Events Preparedness Global Infectious Hazards Preparedness Emergency Preparedness Geneva Switzerland
                [4 ] Department of Digital Health and Innovation Science Division World Health Organization Geneva Switzerland
                [5 ] Information Systems for Health Evidence and Intelligence for Action in Health Pan American Health Organization and World Health Organization Regional Office for the Americas Washington DC, DC United States
                [6 ] Evidence and Intelligence for Action in Health Pan American Health Organization and World Health Organization Regional Office for the Americas Washington, DC United States
                [7 ] Department of Health Systems Development Regional Office for South-East Asia World Health Organization New Delhi India
                [8 ] Department of Science, Information and Dissemination Eastern Mediterranean Regional Office World Health Organization Cairo Egypt
                [9 ] Division of Health Systems and Public Health Regional Office for Europe World Health Organization Copenhagen Denmark
                [10 ] Communications Department Regional Office for Africa World Health Organization Brazzaville Congo
                [11 ] Global Infectious Hazards Preparedness Emergency Preparedness World Health Organization Geneva Switzerland
                [12 ] Center for Health Informatics School of Information Sciences University of Illinois Champaign, IL United States
                [13 ] Fondazione Bruno Kessler Trento Italy
                [14 ] Venice Office Organisation for Economic Co-operation and Development Venice Italy
                [15 ] The University Institute for Modern Languages Milan Italy
                [16 ] Berkman-Klein Center for Internet and Society Harvard University Cambridge, MA United States
                [17 ] Complex Multilayer Networks (CoMuNe) Research Center for Information and Communication Technology Bruno Kessler Foundation Trento Italy
                [18 ] Ted Rogers School of Management Ryerson University Toronto, ON Canada
                [19 ] EU DisinfoLab Brussels Belgium
                Author notes
                Corresponding Author: Tina Purnat purnatt@ 123456who.int
                Author information
                https://orcid.org/0000-0003-3235-0091
                https://orcid.org/0000-0003-1800-2103
                https://orcid.org/0000-0002-6186-9362
                https://orcid.org/0000-0002-0257-6631
                https://orcid.org/0000-0002-6083-7713
                https://orcid.org/0000-0003-4455-3080
                https://orcid.org/0000-0001-8741-5409
                https://orcid.org/0000-0002-4005-5183
                https://orcid.org/0000-0001-7490-0691
                https://orcid.org/0000-0002-3441-9219
                https://orcid.org/0000-0002-4583-5998
                https://orcid.org/0000-0002-3996-1541
                https://orcid.org/0000-0001-9016-9026
                https://orcid.org/0000-0002-3550-6939
                https://orcid.org/0000-0002-6982-2382
                https://orcid.org/0000-0002-3793-3635
                https://orcid.org/0000-0002-5559-2889
                https://orcid.org/0000-0001-5158-8594
                https://orcid.org/0000-0002-6950-1220
                https://orcid.org/0000-0003-2366-5163
                https://orcid.org/0000-0001-6013-2687
                https://orcid.org/0000-0001-6929-5335
                Article
                v22i6e19659
                10.2196/19659
                7332158
                32558655
                d55990fb-738d-41eb-8415-804b67d85777
                ©Viroj Tangcharoensathien, Neville Calleja, Tim Nguyen, Tina Purnat, Marcelo D’Agostino, Sebastian Garcia-Saiso, Mark Landry, Arash Rashidian, Clayton Hamilton, Abdelhalim AbdAllah, Ioana Ghiga, Alexandra Hill, Daniel Hougendobler, Judith van Andel, Mark Nunn, Ian Brooks, Pier Luigi Sacco, Manlio De Domenico, Philip Mai, Anatoliy Gruzd, Alexandre Alaphilippe, Sylvie Briand. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 26.06.2020.

                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.

                History
                : 8 June 2020
                : 18 June 2020
                Categories
                Original Paper
                Original Paper

                Medicine
                covid-19,infodemic,knowledge translation,message amplification,misinformation,information-seeking behavior,access to information,information literacy,communications media,internet,risk communication,evidence synthesis

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