Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation
Open accessPublished version of a preprint
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
False information and conspiracy theories can cause confusion and discourage people from taking the crisis seriously, especially when socially validated and spread.
“Spreading false information or even conspiracy theories that support implausible explanations of the causal forces at work behind the crisis may create serious confusion and even discourage people from taking the crisis seriously or responsibly, all the more so, the more such signals receive social validation and spread across social groups and communities 27 .”
From Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics (2020) · cites this paper as [27]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The spread of true and false news online
Vosoughi, S., Roy, D., & Aral, S. (2018) · Science · doi:10.1126/science.aap9559 · Cited by 8,847 · cited 1× · see citing works
“The spread of misinformation [11,12] can trigger behavioral responses that, in turn, can further expose individuals and communities to health risks.”
BackgroundLazer, D. M. J., Baum, M. A., Benkler, Y., Berinsky, A. J., Greenhill, K. M., Menczer, F., Metzger, M. J., Nyhan, B., Pennycook, G., Rothschild, D., et al. (2018) · Science · doi:10.1126/science.aao2998 · Cited by 4,160 · see citing works
The spread of low-credibility content by social bots
Shao, C., Ciampaglia, G. L., Varol, O., Yang, K.-C., Flammini, A., & Menczer, F. (2018) · Nature Communications · doi:10.1038/s41467-018-06930-7 · Cited by 1,125 · see citing works
The spread of low-credibility content by social bots
Shao, C., Ciampaglia, G. L., Varol, O., Yang, K.-C., Flammini, A., & Menczer, F. (2018) · RePEc: Research Papers in Economics · Cited by 574 · see citing works
Bots increase exposure to negative and inflammatory content in online social systems
Stella, M., Ferrara, E., & De Domenico, M. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1803470115 · Cited by 492 · see citing works
Addressing the COVID-19 related stigma and discrimination: a fight against "infodemic" in Bangladesh
Hasan, M. T., Hossain, S., Saran, T. R., & Ahmed, H. U. (2020) · Minerva Psichiatrica · doi:10.23736/s0391-1772.20.02088-9 · Cited by 21 · see citing works
Addressing the COVID-19 related stigma and discrimination: a fight against infodemic in BangladeshPreprint
Hasan, M. T. (2020) · doi:10.31234/osf.io/qpbj7 · Cited by 12 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [2]Munich Security Conference World Health Organization 2020 2 15 2020-04-26 https://www.who.int/dg/speeches/detail/munich-security-conference
Cited by
Sorted by citations
Infodemics and health misinformation: a systematic review of reviews
do Nascimento, I. J. B., Pizarro, A. B., Almeida, J. M., Muscat, N. A., Gonçalves, M. A., Björklund, M., & Novillo-Ortiz, D. (2022) · Bulletin of the World Health Organization · doi:10.2471/blt.21.287654 · Cited by 670 · see citing works
Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics
Gallotti, R., Valle, F., Castaldo, N., Sacco, P., & De Domenico, M. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00994-6 · Cited by 591 · see citing works
Self-citationHow to Fight an Infodemic: The Four Pillars of Infodemic Management
Eysenbach, G. (2020) · Journal of Medical Internet Research · doi:10.2196/21820 · Cited by 551 · see citing works
Rocha, Y. M., de Moura, G. A., Desidério, G. A., de Oliveira, C. H., Lourenço, F. D., & Nicolete, L. D. D. F. (2021) · Journal of Public Health · doi:10.1007/s10389-021-01658-z · Cited by 485 · see citing works
Su, Z., McDonnell, D., Wen, J., Kozak, M., Abbas, J., Šegalo, S., Li, X. A., Aḥmad, J., Cheshmehzangi, A., Cai, Y., et al. (2021) · Globalization and Health · doi:10.1186/s12992-020-00654-4 · Cited by 424 · see citing works
Dadaczynski, K., Okan, O., Messer, M., Leung, A. Y. M., Rosário, R., Darlington, E., & Rathmann, K. (2021) · Journal of Medical Internet Research · doi:10.2196/24097 · Cited by 390 · see citing works
Knowledge, attitudes, and practices (KAP) toward COVID-19: a cross-sectional study in South Korea
Lee, M., Kang, B., & You, M. (2021) · BMC Public Health · doi:10.1186/s12889-021-10285-y · Cited by 380 · see citing works
COVID-19-related misinformation on social media: a systematic review
Gabarron, E., Oyeyemi, S. O., & Wynn, R. (2021) · Bulletin of the World Health Organization · doi:10.2471/blt.20.276782 · Cited by 345 · see citing works
Zhang, K. C., Fang, Y., Cao, H., Chen, H., Hu, T., Chen, Y., Zhou, X., & Wang, Z. J. (2020) · JMIR Pediatrics and Parenting · doi:10.2196/24827 · Cited by 239 · see citing works
Bots and Misinformation Spread on Social Media: Implications for COVID-19
Himelein-Wachowiak, M., Giorgi, S., Devoto, A., Rahman, M. M., Ungar, L., Schwartz, H. A., Epstein, D. H., Leggio, L., & Curtis, B. L. (2021) · Journal of Medical Internet Research · doi:10.2196/26933 · Cited by 238 · see citing works
Parents’ willingness and attitudes concerning the COVID‐19 vaccine: A cross‐sectional study
Yılmaz, M., & Şahin, M. K. (2021) · International Journal of Clinical Practice · doi:10.1111/ijcp.14364 · Cited by 203 · see citing works
Sallam, M., Dababseh, D., Yaseen, A., Al-Haidar, A., Taim, D., Eid, H., Ababneh, N. A., Bakri, F., & Mahafzah, A. (2020) · medRxiv · doi:10.1371/journal.pone.0243264 · Cited by 164 · see citing works
Pian, W., Chi, J., & Ma, F. (2021) · Information Processing & Management · doi:10.1016/j.ipm.2021.102713 · Cited by 180 · see citing works
Calleja, N., AbdAllah, A., Abad, N. S., Ahmed, N., Albarracín, D., Altieri, E., Anoko, J. N., Arcos, R., Azlan, A. A., Bayer, J., et al. (2021) · JMIR Infodemiology · doi:10.2196/30979 · Cited by 168 · see citing works
Self-citationRattay, P., Michalski, N., Domańska, O. M., Kaltwasser, A., Bock, F. D., Wieler, L. H., & Jordan, S. (2021) · PLoS ONE · doi:10.1371/journal.pone.0251694 · Cited by 166 · see citing works
Readiness for voice assistants to support healthcare delivery during a health crisis and pandemic
Sezgin, E., Huang, Y., Ramtekkar, U., & Lin, S. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00332-0 · Cited by 155 · see citing works
Examining Australian public perceptions and behaviors towards a future COVID-19 vaccine
Seale, H., Heywood, A. E., Leask, J., Sheel, M., Dürrheim, D. N., Alderman, K. B., & Kaur, R. (2021) · BMC Infectious Diseases · doi:10.1186/s12879-021-05833-1 · Cited by 154 · see citing works
Al-Hasan, A., Yim, D., & Khuntia, J. (2020) · Journal of Medical Internet Research · doi:10.2196/20634 · Cited by 150 · see citing works
Duplaga, M. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17217818 · Cited by 146 · see citing works
Bragazzi, N. L., Mansour, M., Bonsignore, A., & Ciliberti, R. (2020) · Pharmacy · doi:10.3390/pharmacy8030140 · Cited by 136 · see citing works
Berg, S. H., O'Hara, J. K., Shortt, M. T., Thune, H., Brønnick, K., Lungu, D. A., Røislien, J., & Wiig, S. (2021) · BMC Public Health · doi:10.1186/s12889-021-11468-3 · Cited by 136 · see citing works
Kinser, P. A., Jallo, N., Amstadter, A. B., Thacker, L. R., Jones, E. G., Moyer, S. W., Rider, A., Karjane, N. W., & Salisbury, A. L. (2021) · Journal of Women s Health · doi:10.1089/jwh.2020.8866 · Cited by 130 · see citing works
Infodemics: a new challenge for public health
Briand, S. C., Cinelli, M., Nguyen, T., Lewis, R., Prybylski, D., Valensise, C. M., Colizza, V., Tozzi, A. E., Perra, N., Baronchelli, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.10.031 · Cited by 125 · see citing works
Self-citationInfodemics and infodemiology: a short history, a long future
Zielinski, C. (2021) · Revista Panamericana de Salud Pública · doi:10.26633/rpsp.2021.40 · Cited by 122 · see citing works
Nekliudov, N. A., Blyuss, O. B., Cheung, K. Y., Petrou, L., Genuneit, J., Sushentsev, N., Викторовна, Л. А., Comberiati, P., Warner, J. O., Tudor‐Williams, G., et al. (2020) · Journal of Medical Internet Research · doi:10.2196/20955 · Cited by 117 · see citing works
An, L. C., Bacon, E. M., Hawley, S. T., Yang, P., Russell, D. M., Huffman, S. B., & Resnicow, K. (2021) · Journal of Medical Internet Research · doi:10.2196/25042 · Cited by 113 · see citing works
Living with “long COVID”: A systematic review and meta-synthesis of qualitative evidence
Hossain, M. M., Das, J., Rahman, F., Nesa, F., Hossain, P., Islam, A. M. K., Tasnim, S., Faizah, F., Mazumder, H., Purohit, N., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0281884 · Cited by 132 · see citing works
Wong, F. H. C., Liu, T., Leung, D. K. Y., Zhang, A. Y., Au, W. S. H., Kwok, W. W., Shum, A. K. Y., Wong, G. H. Y., & Lum, T. Y. S. (2021) · Journal of Medical Internet Research · doi:10.2196/26570 · Cited by 106 · see citing works
Lyu, H., Wang, J., Wu, W., Duong, V., Zhang, X., Dye, T., & Luo, J. (2021) · Intelligent Medicine · doi:10.1016/j.imed.2021.08.001 · Cited by 101 · see citing works
Infodemia: excesso de quantidade em detrimento da qualidade das informações sobre a COVID-19
García, L. P., & Duarte, E. (2020) · Epidemiologia e Serviços de Saúde · doi:10.1590/s1679-49742020000400019 · Cited by 99 · see citing works
Health-related fake news on social media platforms: A systematic literature review
Melchior, C., & Oliveira, M. F. D. A. (2021) · New Media & Society · doi:10.1177/14614448211038762 · Cited by 97 · see citing works
COVID-19 information-related digital literacy among online health consumers in a low-income country
Abdulai, A., Tiffere, A.-H., Adam, F., & Kabanunye, M. M. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104322 · Cited by 95 · see citing works
Purnat, T. D., Vacca, P., Czerniak, C., Ball, S., Burzo, S., Zecchin, T., Wright, A., Bezbaruah, S., Tanggol, F., Dubé, È., et al. (2021) · JMIR Infodemiology · doi:10.2196/30971 · Cited by 87 · see citing works
Self-citationCOVID-19 Misinformation on Social Media: A Scoping Review
Joseph, A. M., Fernández, V., Kritzman, S., Eaddy, I., Cook, O. M., Lambros, S., Silva, C. E. J., Arguelles, D., Abraham, C., Dorgham, N., et al. (2022) · Cureus · doi:10.7759/cureus.24601 · Cited by 81 · see citing works
Ishizumi, A., Kolis, J., Abad, N., Prybylski, D., Brookmeyer, K. A., Voegeli, C., Wardle, C., & Chiou, H. (2024) · The Lancet Public Health · doi:10.1016/s2468-2667(24)00031-8 · Cited by 79 · see citing works
Conspiracy beliefs and vaccination intent for COVID-19 in an infodemic
Ghaddar, A., Khandaqji, S., Awad, Z., & Kansoun, R. (2022) · PLoS ONE · doi:10.1371/journal.pone.0261559 · Cited by 69 · see citing works
COVID-19: the deadly threat of misinformation
Galvão, J. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30721-0 · Cited by 69 · see citing works
An augmented multilingual Twitter dataset for studying the COVID-19 infodemic
Lopez, C. E., & Gallemore, C. T. (2021) · Social Network Analysis and Mining · doi:10.1007/s13278-021-00825-0 · Cited by 67 · see citing works
Rubinelli, S., Purnat, T. D., Wilhelm, E., Traicoff, D. A., Namageyo-Funa, A., Thomson, A., Wardle, C., Lamichhane, J., Briand, S. C., & Nguyen, T. (2022) · Human Resources for Health · doi:10.1186/s12960-022-00733-0 · Cited by 67 · see citing works
Self-citationCharacterizing the COVID-19 Infodemic on Chinese Social Media: Exploratory Study
Zhang, S., Pian, W., Ma, F., Ni, Z., & Liu, Y. (2021) · JMIR Public Health and Surveillance · doi:10.2196/26090 · Cited by 65 · see citing works
Winters, M., Malik, A. A., & Omer, S. B. (2022) · PLoS ONE · doi:10.1371/journal.pone.0278622 · Cited by 65 · see citing works
White, S. J., Barello, S., Marco, E. C. D. S., Colombo, C., Eeckman, E., Gilligan, C., Graffigna, G., Jirasevijinda, T., Mosconi, P., Mullan, J., et al. (2020) · Patient Education and Counseling · doi:10.1016/j.pec.2020.12.025 · Cited by 64 · see citing works
The role of social media in promoting vaccine hesitancy
Clark, S. E., Bledsoe, M. C., & Harrison, C. J. (2022) · Current Opinion in Pediatrics · doi:10.1097/mop.0000000000001111 · Cited by 64 · see citing works
A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic
Liu, T., & Xiao, X. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.755808 · Cited by 61 · see citing works
Emotion, analytic thinking and susceptibility to misinformation during the COVID-19 outbreak
Li, M., Chen, Z., & Rao, L. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107295 · Cited by 61 · see citing works
Validation analysis of Global Health Security Index (GHSI) scores 2019
Boyd, M., Wilson, N., & Nelson, C. (2020) · BMJ Global Health · doi:10.1136/bmjgh-2020-003276 · Cited by 61 · see citing works
Agley, J. D., Xiao, Y., Thompson, E. E., Chen, X., & Golzarri‐Arroyo, L. (2021) · Journal of Medical Internet Research · doi:10.2196/32425 · Cited by 60 · see citing works
The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms
Zhi, H., Yang, Z., Li, Q., & Zhang, A. (2020) · Journal of Medical Internet Research · doi:10.2196/22639 · Cited by 61 · see citing works
COVID-19, Social Media, and the Role of the Public Physician
Topf, J. M., & Williams, P. N. (2021) · Blood Purification · doi:10.1159/000512707 · Cited by 59 · see citing works
Dynamics of social corrections to peers sharing COVID-19 misinformation on WhatsApp in Brazil
Vijaykumar, S., Rogerson, D., Jin, Y., & de Oliveira-Costa, M. S. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab219 · Cited by 59 · see citing works
Vaccines and the social amplification of risk
Larson, H. J., Lin, L. K., & Goble, R. L. (2022) · Risk Analysis · doi:10.1111/risa.13942 · Cited by 62 · see citing works
Adebesin, F., Smuts, H., Mawela, T., Maramba, G., & Hattingh, M. (2023) · JMIR Infodemiology · doi:10.2196/48620 · Cited by 57 · see citing works
Human information behavior during the Covid-19 health crisis. A literature review
Montesi, M. (2021) · Library & Information Science Research · doi:10.1016/j.lisr.2021.101122 · Cited by 58 · see citing works
Vijaykumar, S., McNeill, A., & Simpson, J. (2021) · Public Health Nutrition · doi:10.1017/s1368980021000124 · Cited by 55 · see citing works
Ma, W., Zhang, P., Zhao, X. J., & Xue, L. (2021) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2021.126558 · Cited by 53 · see citing works
Nurse, M. S., Ross, R. M., İşler, O., & Rooy, D. V. (2021) · Memory & Cognition · doi:10.3758/s13421-021-01219-5 · Cited by 53 · see citing works
Rethinking Fake News: Disinformation and Ideology during the time of COVID-19 Global Pandemic
Das, R., & Ahmed, W. (2021) · IIM Kozhikode Society & Management Review · doi:10.1177/22779752211027382 · Cited by 50 · see citing works
Combating the COVID-19 infodemic: a three-level approach for low and middle-income countries
Dash, S., Parray, A. A., Freitas, L. D., Mithu, M. I. H., Rahman, M. M., Aarthy, R., & Pandya, A. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2020-004671 · Cited by 50 · see citing works
Loss, J., Boklage, E., Jordan, S., Jenny, M. A., Weishaar, H. B., & Bcheraoui, C. E. (2021) · Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz · doi:10.1007/s00103-021-03283-3 · Cited by 50 · see citing works
“Immune Boosting” in the time of COVID: selling immunity on Instagram
Wagner, D. N., Marcon, A. R., & Caulfield, T. (2020) · Allergy Asthma and Clinical Immunology · doi:10.1186/s13223-020-00474-6 · Cited by 49 · see citing works
Molenaar, A., Lukose, D., Brennan, L. L., Jenkins, E. L., & McCaffrey, T. A. (2024) · Journal of Medical Internet Research · doi:10.2196/47826 · Cited by 47 · see citing works
Wilhelm, E., Ballalai, I., Belanger, M.-E., Benjamin, P., Bertrand-Ferrandis, C., Bezbaruah, S., Briand, S. C., Brooks, I. S., Bruns, R., Bucci, L. M., et al. (2023) · JMIR Infodemiology · doi:10.2196/44207 · Cited by 46 · see citing works
Self-citationMladenović, D., Todua, N., & Pavlović-Höck, N. (2023) · Telematics and Informatics · doi:10.1016/j.tele.2023.101966 · Cited by 50 · see citing works
Infodemia: noticias falsas y tendencias de mortalidad por COVID-19 en seis países de América Latina
Nieves-Cuervo, G. M., Hernández, E. F. M., Robledo-Colonia, A. F., & Ardila, E. K. G. (2021) · Revista Panamericana de Salud Pública · doi:10.26633/rpsp.2021.44 · Cited by 45 · see citing works
YouTube as a source of information on COVID-19 vaccination in rheumatic diseases
Koçyiğit, B. F., & Akyol, A. (2021) · Rheumatology International · doi:10.1007/s00296-021-05010-2 · Cited by 44 · see citing works
Castioni, P., Andrighetto, G., Gallotti, R., di Sorrentino, E. P., & Domenico, M. D. (2022) · Royal Society Open Science · doi:10.1098/rsos.220716 · Cited by 43 · see citing works
Chowdhury, A. H., Kabir, K. H., Abdulai, A., & Alam, M. F. (2023) · Sustainability · doi:10.3390/su15064753 · Cited by 50 · see citing works
Marin, L. (2020) · Ethics and Information Technology · doi:10.1007/s10676-020-09550-2 · Cited by 44 · see citing works
Bernardo, T. M., Sobkowich, K. E., Forrest, R. O., Stewart, L. S., D'Agostino, M. J., Gutiérrez, E. P., & Gillis, D. J. (2021) · JMIR Public Health and Surveillance · doi:10.2196/25935 · Cited by 44 · see citing works
Self-citationEnnab, F., Babar, M. S., Khan, A. R., Mittal, R. J., Nawaz, F. A., Essar, M. Y., & Fazel, S. S. (2022) · Clinical Epidemiology and Global Health · doi:10.1016/j.cegh.2022.100981 · Cited by 42 · see citing works
Ibarra-Estrada, M. Á., García-Salas, Y., Mireles‐Cabodevila, E., Pulgarín, J. A. L., Chávez-Peña, Q., García-Salcido, R., Mijangos, J., & Aguirre-Ávalos, G. (2021) · Critical Care Medicine · doi:10.1097/ccm.0000000000005312 · Cited by 41 · see citing works
The Future of Infodemic Surveillance as Public Health Surveillance
Chiou, H., Voegeli, C., Wilhelm, E., Kolis, J., Brookmeyer, K. A., & Prybylski, D. (2022) · Emerging infectious diseases · doi:10.3201/eid2813.220696 · Cited by 41 · see citing works
Fighting the infodemic: the 4 i Framework for Advancing Communication and Trust
Sundelson, A. E., Jamison, A., Huhn, N., Pasquino, S.-L., & Sell, T. K. (2023) · BMC Public Health · doi:10.1186/s12889-023-16612-9 · Cited by 40 · see citing works
Cha, M., Cha, C., Singh, K., Lima, G., Ahn, Y., Kulshrestha, J., & Varol, O. (2021) · JMIR Human Factors · doi:10.2196/23279 · Cited by 39 · see citing works
Lu, X., Vijaykumar, S., Jin, Y., & Rogerson, D. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101750 · Cited by 38 · see citing works
Public health challenges and opportunities after COVID-19
Sacco, P. L., & Domenico, M. D. (2021) · Bulletin of the World Health Organization · doi:10.2471/blt.20.267757 · Cited by 37 · see citing works
Self-citationExamining the structure of credibility evaluation when sixth graders read online texts
Kiili, C., Räikkönen, E., Bråten, I., Strømsø, H. I., & Hagerman, M. S. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12779 · Cited by 38 · see citing works
Leveraging conversational technology to answer common COVID-19 questions
McKillop, M. M., South, B. R., Preininger, A. M., Mason, M., & Jackson, G. P. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocaa316 · Cited by 36 · see citing works
Studying the COVID-19 infodemic at scale
Gruzd, A. A., Domenico, M. D., Sacco, P. L., & Briand, S. C. (2021) · Big Data & Society · doi:10.1177/20539517211021115 · Cited by 36 · see citing works
Self-citationA Multifaceted Campaign to Combat COVID-19 Misinformation in the Hispanic Community
Silesky, M. D., Panchal, D., Fields, M., Peña, A. S., Diez, M., Magdaleno, A., Frausto-Rodriguez, P., & Bonnevie, E. (2022) · Journal of Community Health · doi:10.1007/s10900-022-01170-9 · Cited by 36 · see citing works
Zhang, X., Zhang, Z.-K., Wang, W., Hou, D., Xu, J., Ye, X., & Li, S. (2021) · International Journal of Digital Earth · doi:10.1080/17538947.2021.1888326 · Cited by 35 · see citing works
Official social media and its impact on public behavior during the first wave of COVID-19 in China
Liu, H. (2022) · BMC Public Health · doi:10.1186/s12889-022-12803-y · Cited by 35 · see citing works
Wu, J., Zuo, R., He, C., Xiong, H., Zhao, K., & Hu, Z. (2022) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2022.127119 · Cited by 34 · see citing works
Bella, E. L., Allen, C., & Lirussi, F. (2021) · Integrative Medicine Research · doi:10.1016/j.imr.2021.100731 · Cited by 33 · see citing works
Emergence of knowledge communities and information centralization during the COVID-19 pandemic
Sacco, P. L., Gallotti, R., Pilati, F., Castaldo, N., & Domenico, M. D. (2021) · Social Science & Medicine · doi:10.1016/j.socscimed.2021.114215 · Cited by 33 · see citing works
Self-citationBuller, D. B., Pagoto, S., Henry, K. L., Berteletti, J., Walkosz, B. J., Bibeau, J., Baker, K., Hillhouse, J., & Arroyo, K. M. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.683034 · Cited by 33 · see citing works
Stauch, L., Renninger, D., Rangnow, P., Hartmann, A., Fischer, L. M., Dadaczynski, K., & Okan, O. (2025) · Journal of Medical Internet Research · doi:10.2196/69170 · Cited by 32 · see citing works
Savoia, E., Harriman, N. W., Piltch-Loeb, R. N., Bonetti, M., Toffolutti, V., & Testa, M. A. (2022) · Vaccines · doi:10.3390/vaccines10050671 · Cited by 37 · see citing works
White, B. K., Martin, A., & White, J. A. (2022) · The Lancet Regional Health - Western Pacific · doi:10.1016/j.lanwpc.2022.100528 · Cited by 34 · see citing works
Zhang, T. (2020) · Scientometrics · doi:10.1007/s11192-020-03736-7 · Cited by 31 · see citing works
The Impact of the COVID-19 Pandemic on the Practice of Forensic Medicine: An Overview
Esposito, M., Salerno, M., Scoto, E., Nunno, N. R. D., & Sessa, F. (2022) · Healthcare · doi:10.3390/healthcare10020319 · Cited by 31 · see citing works
Cipolletta, S., & Gris, F. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182211832 · Cited by 30 · see citing works
Winters, M., Oppenheim, B., Sengeh, P., Jalloh, M. B., Webber, N., Pratt, S., Leigh, B., Mölsted-Alvesson, H., Zeebari, Z., Sundberg, C. J., et al. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2021-006954 · Cited by 31 · see citing works
Digital Marketing Communication Activities on Online Magazine Gettinlow
Teguh, M., Dumais, M. A. O., Wijaya, C. T., Torsten, P., & Vera, A. (2023) · Journal International Dakwah and Communication · doi:10.55849/jidc.v3i1.196 · Cited by 29 · see citing works
Han, Y., Jiang, B., & Guo, R. (2021) · Journal of Medical Internet Research · doi:10.2196/23097 · Cited by 30 · see citing works
Mani, N. S., Ottosen, T., Fratta, M., & Yu, F. (2021) · Journal of the Medical Library Association JMLA · doi:10.5195/jmla.2021.1165 · Cited by 28 · see citing works
Advancing Infodemiology in a Digital Intensive Era
Mackey, T. K., Baur, C., & Eysenbach, G. (2022) · JMIR Infodemiology · doi:10.2196/37115 · Cited by 28 · see citing works
Lohiniva, A., Pensola, A., Hyökki, S., Sivelä, J., & Tammi, T. (2022) · BMC Public Health · doi:10.1186/s12889-022-14563-1 · Cited by 28 · see citing works
From Facebook to YouTube: The Potential Exposure to COVID-19 Anti-Vaccine Videos on Social Media
Gruzd, A. A., Abul‐Fottouh, D., Song, M. Y., & Saiphoo, A. N. (2023) · Social Media + Society · doi:10.1177/20563051221150403 · Cited by 28 · see citing works
Self-citationAnwar, A., Ilyas, H., Yaqub, U., & Zaman, S. (2021) · Annual International Conference on Digital Government Research · doi:10.1145/3463677.3463718 · Cited by 27 · see citing works
- Authors
- Tangcharoensathien, V., Calleja, N., Nguyen, T., Purnat, T., D’Agostino, M., Garcia-Saiso, S., Landry, M., Rashidian, A., Hamilton, C., AbdAllah, A., Ghiga, I., Hill, A., Hougendobler, D., van Andel, J., Nunn, M., Brooks, I., Sacco, P. L., De Domenico, M., Mai, P., Gruzd, A., Alaphilippe, A., & Briand, S.
- Affiliations
- Ministry of Public Health (TH)
- Ministry for Health (MT)
- World Health Organization (CH)
- World Health Organization Regional Office for South-East Asia (IN)
- World Health Organization Regional Office for the Eastern Mediterranean (EG)
- World Health Organization Regional Office for Europe (DK)
- World Health Organization Regional Office for Africa (CG)
- University of Illinois Urbana-Champaign (US)
- Organisation de Coopération et de Développement Economiques (FR)
- Toronto Metropolitan University (CA)
- Corresponding author
- Purnat, Tina
- ORCID
- Tangcharoensathien, Viroj
- Calleja, Neville
- Nguyen, Tim
- Purnat, Tina
- D’Agostino, Marcelo
- Garcia-Saiso, Sebastian
- Landry, Mark
- Rashidian, Arash
- Hamilton, Clayton
- AbdAllah, Abdelhalim
- Ghiga, Ioana
- Hill, Alexandra
- Hougendobler, Daniel
- van Andel, Judith
- Nunn, Mark
- Brooks, Ian
- Sacco, Pier Luigi
- De Domenico, Manlio
- Mai, Philip
- Gruzd, Anatoliy
- Alaphilippe, Alexandre
- Briand, Sylvie
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-06-26
- Volume
- 22
- Issue
- 6
- Pages
- e19659
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7332158
- OpenAlex
- W3036730291
- Cited by
- 561
- References
- 6
- Citations by year
- 2026: 55 · 2025: 49 · 2024: 70 · 2023: 92 · 2022: 118 · 2021: 144 · 2020: 33
- FWCI
- 129.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OAR@UM (University of Malta) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by)
- Greater South Information System
- Funders
- World Health Organization
- Topics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Social Sciences › Communication › Communication and COVID-19 Impact
- Social Sciences › Communication › Public Relations and Crisis Communication
- Keywords
- infodemic management, COVID-19 pandemic, misinformation, crowdsourcing, information management framework, social media, strategic partnership, public trust in health information, health policy implications, risk mitigation
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Disease Outbreaks, Health Education, Humans, Pneumonia, Viral, Public Health, World Health Organization, Coronavirus Infections, Pandemics, Social Media, Crowdsourcing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
