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Remote Laboratory Management: Respiratory Virus Diagnostics
Published on: April 6, 2019
Twitter reveals spatio-temporal variation in vaccine concerns in Sub-Saharan Africa
Devansh Jain1,2, Sunny Rai2,3, Juhi Mittal2
1Language Technologies Institute, School of Computer Science, Carnegie Mellon University.
Background:
COVID-19 vaccine hesitancy, fueled by concerns about vaccine development, side effects, and misinformation on social media platforms like Twitter, resulted in lower vaccination rates in Sub-Saharan Africa.
Methods:
We collected, preprocessed, and geolocated 6,546,893 tweets related to COVID-19 vaccination from Sub-Saharan Africa. Using a vaccine misinformation classifier trained on RoBERTa embeddings, we identified 371,965 tweets in our dataset that included misinformation. We characterized the relationship between specific COVID-19 vaccine topics and the prevalence of misinformation, examined temporal variation in misinformation, and separately described the prevalence of misinformation in clusters defined by country-level socioeconomic and development metrics and by COVID-19 epidemiology.
Results:
Misinformation in Sub-Saharan Africa is associated with discussions about pharmaceutical company profits, global access to vaccines and disparity, and trust in scientific research regarding vaccines. The prevalence of misinformation topics varied widely across country clusters as defined by socioeconomic development and COVID-19 epidemiology metrics.
Conclusions:
Social media data provides valuable insights about vaccine hesitancy and vaccine misinformation in Sub-Saharan Africa that can inform policy and programmatic interventions to support vaccine demand and vaccine promotion.
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