Fake news and vaccine hesitancy

DOI

As the COVID-19 pandemic continues to exact a heavy death toll, weakens health systems and devastates economies, the discovery and delivery of vaccines have rekindled hope. However, fake news has emerged as a serious obstacle to countries’ vaccination campaigns. Taking Cameroon as a case study, this article investigates the practices (types and contents) and sociopolitical implications at micro and macro levels of fake news on COVID-19 vaccines and vaccination campaign. It shows that vaccine hesitancy is mostly linked to conspiracy theories. Vaccine complacency, the first component of vaccine hesitancy, mainly relates to conspiracy theories about foreign extermination/experimentation plots. Vaccine confidence, the second component of vaccine hesitancy mostly correlates with conspiracy theories alleging the complicity of local authorities in these plots. Vaccine confidence, the third component of vaccine hesitancy, is linked to disinformation notably about acts of corruption. These translate into claims of alternative truth, infodemic, nationalism and distrust of elites at individual level, and the rise of vaccine hesitancy, the delegitimization of public institutions and claims of alternative truth at societal level. The phenomenon occurs in fairly similar ways as in the West but there are marked thematic differences. The article provides policy recommendations on the scientific, communication, and sociopolitical planes.

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Identifier
DOI https://doi.org/10.57745/OOOA1Q
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/OOOA1Q
Provenance
Creator Tawat Mahama ORCID logo
Publisher Recherche Data Gouv
Contributor TAWAT, Mahama; MARINI Jérôme; University of Montpellier; Nakala
Publication Year 2024
Funding Reference Montpellier Advanced Knowledge Institute on Transitions (MAKIT) https://makit.edu.umontpellier.fr/en/home/
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact TAWAT, Mahama (Jönköping University); MARINI Jérôme (University of Montpellier)
Representation
Resource Type Dataset
Format text/plain
Size 5021
Version 1.0
Discipline Life Sciences; Medicine