Long Covid : online patient narratives, public health communication and vaccine hesitancy

Miyake, Esperanza and Martin, Sam (2021) Long Covid : online patient narratives, public health communication and vaccine hesitancy. Digital Health, 7. ISSN 2055-2076 (https://doi.org/10.1177/20552076211059649)

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Introduction: This study combines quantitative and qualitative analyses of social media data collected through three key stages of the pandemic, to highlight the following: ●'First wave' (March to May, 2020): negative consequences arising from a disconnect between official health communications, and unofficial Long Covid sufferers’ narratives online. ●'Second wave' (October 2020 to January 2021): closing the 'gap' between official health communications and unofficial patient narratives, leading to a better integration between patient voice, research and services. ●'Vaccination phase' (January 2021, early stages of the vaccination programme in the UK): continuing and new emerging concerns. Methods: We adopted a mixed methods approach involving quantitative and qualitative analyses of 1.38 million posts mentioning long-term symptoms of Covid-19, gathered across social media and news platforms between 1 January 2020 and 1 January 2021, on Twitter, Facebook, Blogs, and Forums. Our inductive thematic analysis was informed by our discourse analysis of words, and sentiment analysis of hashtags and emojis. Results: Results indicate that the negative impacts arise mostly from conflicting definitions of Covid-19, and fears around the Covid-19 vaccine for Long Covid sufferers. Key areas of concern are: time/duration; symptoms/testing; emotional impact; lack of support and resources. Conclusions: Whilst Covid-19 is a global issue, specific socio-cultural, political and economic contexts mean patients experience Long Covid at a localised level, needing appropriate localised responses. This can only happen if we build a knowledge base that begins with the patient, ultimately informing treatment and rehabilitation strategies for Long Covid.