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Reasons underlying the intention to vaccinate children aged 5-11 against COVID-19: A cross-sectional study of parents in Israel, November 2021.

Nicole G MorozovAmiel A DrorAmani DaoudNetanel EisenbachEdward KaykovMasad BarhoumTsvi ShelegEyal SelaMichael Edelstein
Published in: Human vaccines & immunotherapeutics (2022)
Vaccination is a key tool to mitigate impacts of the COVID-19 pandemic. In Israel, COVID-19 vaccines became available to adults in December 2020 and to 5-11-year-old children in November 2021. Ahead of the vaccine roll-out in children, we aimed to determine whether surveyed parents intended to vaccinate their children and describe reasons for their intentions. We collected information on parental socio-demographic characteristics, COVID-19 vaccine history, intention to vaccinate their children against COVID-19, and reasons for parental decisions using an anonymous online survey. We identified associations between parental characteristics and plans to vaccinate children using a logistic regression model and described reasons for intentions to vaccinate or not. Parental non-vaccination and having experienced major vaccination side effects were strongly associated with non-intention to vaccinate their children (OR 0.09 and 0.18 respectively, p  < .001). Parents who were younger, lived in the socio-economically deprived periphery, and belonged to the Arab population had lower intentions to vaccinate their children. Reasons for non-intention to vaccinate included concerns about vaccine safety and efficacy (53%, 95%CI 50-56) and the belief that COVID-19 is a mild disease (73%, 95%CI 73-79), while a frequent motive for vaccination was the return to normal social and educational life (89%, 95%CI 87-91). Understanding rationales for COVID-19 vaccine rejection or acceptance, as well as parental demographic data, can pave the way for intentional educational campaigns to encourage not only vaccination against COVID-19, but also regular childhood vaccine programming.
Keyphrases
  • coronavirus disease
  • sars cov
  • young adults
  • healthcare
  • respiratory syndrome coronavirus
  • machine learning
  • risk factors
  • health insurance
  • physical activity
  • big data