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BackgroundThe COVID-19 pandemic propelled immunology into global news and social media, resulting in the potential for misinterpreting and misusing complex scientific concepts.ObjectiveTo study the extent to which immunology is discussed in news articles and YouTube videos in English and Italian, and if related scientific concepts are used to support specific political or ideological narratives in the context of COVID-19.MethodsIn English and Italian we searched the period 11/09/2019 to 11/09/2022 on YouTube, using the software Mozdeh, for videos mentioning COVID-19 and one of nine immunological concepts: antibody-dependent enhancement, anergy, cytokine storm, herd immunity, hygiene hypothesis, immunity debt, original antigenic sin, oxidative stress and viral interference. We repeated this using MediaCloud for news articles.Four samples of 200 articles/videos were obtained from the randomised data gathered and analysed for mentions of concepts, stance on vaccines, masks, lockdown, social distancing, and political signifiers.ResultsVaccine-negative information was higher in videos than news (8-fold in English, 6-fold in Italian) and higher in Italian than English (4-fold in news, 3-fold in videos). We also observed the existence of information bubbles, where a negative stance towards one intervention was associated with a negative stance to other linked ideas. Some immunological concepts (immunity debt, viral interference, anergy and original antigenic sin) were associated with anti-vaccine or anti-NPI (non-pharmacological intervention) views. Videos in English mentioned politics more frequently than those in Italian and, in all media and languages, politics was more frequently mentioned in anti-guidelines and anti-vaccine media by a factor of 3 in video and of 3–5 in news.ConclusionThere is evidence that some immunological concepts are used to provide credibility to specific narratives and ideological views. The existence of information bubbles supports the concept of the “rabbit hole” effect, where interest in unconventional views/media leads to ever more extreme algorithmic recommendations. |
