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Exploring the beliefs and experiences with regard to COVID-19 vaccine hesitancy and acceptance in a slum of Karachi, Pakistan.

Rubina QasimHakim ShahAqsa SultanMuhammad YaqoobRukhsana HaroonSabuj Kanti MistryAmy BestmanMohammad Tahir YousafzaiUday Narayan Yadav
Published in: Health promotion international (2022)
The COVID-19-related misinformation and vaccine hesitancy is a widespread global concern and a recognized public health problem in Pakistan. The current research sought to explore the beliefs and experiences with regard to COVID-19, including vaccine hesitancy and acceptance, in a slum of Karachi, Pakistan. This study used an interpretivist epistemological approach for data collection and employed in-depth interviews (IDIs) and focus group discussions (FGDs) to explore the themes of interest. IDIs and FDGs were conducted in the local language (Pashtu) and Urdu, using semi-structured interview guides. A hybrid thematic analysis approach (use of both inductive and deductive coding) was used to analyze the data. We identified two key themes: the first related to vaccine hesitancy and refusal and included the role of personal belief systems, vaccine mistrust and public perceptions in hesitancy; the second related to vaccine acceptance and included knowledge and awareness about the vaccine and trusted sources of information. Religious beliefs and cultural norms influenced attitudes toward COVID-19 and vaccination. This study also found that awareness about the COVID-19 vaccine in this sample was influenced by sex, educational status and socioeconomic status. Participants with good health literacy and those from healthcare backgrounds were more likely to share views that indicated vaccine acceptance. The findings of this study are being used to co-design a comprehensive intervention to dispel COVID-19 misinformation and vaccine hesitancy across a range of stakeholders such as youths, community leaders, family members, faith leaders, schools and community-based local organizations in Pakistan.
Keyphrases
  • coronavirus disease
  • healthcare
  • sars cov
  • public health
  • mental health
  • randomized controlled trial
  • primary care
  • machine learning
  • big data
  • electronic health record
  • health information
  • drinking water
  • drug induced