Predicting intention to vaccinate against COVID-19 in older Syrian refugees in Lebanon: Findings from a multi-wave study

COVID-19 vaccine acceptance among refugees in the Arab region remains low. This study aimed to examine the prevalence, reasons and predictors of intention to refuse the COVID-19 vaccine among older Syrian refugees in Lebanon. A nested cross-sectional study within a longitudinal study among older Syrian refugees in Lebanon. The sampling frame was a complete listing of beneficiary households of a humanitarian organization with at least one adult aged 50 years or older. Telephone surveys were completed at months 1 starting September 2020 (wave 1), months 2 (wave 2), months 5 (wave 3), months 6 (wave 4) and months 17 (wave 5) in March 2022. Logistic regression models were used to identify predictors of intention to refuse the COVID-19 vaccine. Models were internally validated using bootstrap methods and the models’ calibration and discrimination were presented. Of 3167 Syrian refugees, 61.3% intended to receive the COVID-19 vaccine, 31.3% refused, and 7.4% were undecided. Reasons for vaccine refusal were: preference to follow preventive measures (27.4%) and belief that the vaccine is not essential (20.7%). Furthermore, 57.1% of participants registered to take the COVID-19 vaccine in wave 5. Irrespective of vaccination intention, reasons for not registering included: not wanting to receive the vaccine, and being unsure whether to take it. Predictors of intention to refuse the COVID-19 vaccine included: being a female, older age, having elementary education or above, living outside informal tented settlements, perceiving COVID-19 as not severe and vaccines as not safe or effective, and using social media for information on COVID-19. After adjusting for optimization, the final model showed moderate discrimination (C-statistic: 0.651 (95% CI:0.630–0.672)) and good calibration (C-slope: 0.93 (95% CI: 0.823–1.065)). This study developed a predictive model for vaccination intention with a moderate discriminative ability and good calibration. Prediction models in humanitarian settings can help identify refugees at higher risk of not intending to receive the COVID-19 vaccine for public health targeting.