Abstract
Introduction: Vaccines are essential to prevent infection and reduce morbidity of infectious diseases. Previous evidence has shown that migrants and refugees are particularly vulnerable to exclusion and discrimination, and low COVID-19 vaccine intention and uptake were observed among refugees globally. This study aimed to develop and internally validate prediction models of COVID-19 vaccine uptake by nationality.
Methods: This is a nested prognostic population-based cross-sectional analysis. Data was collected between June and October 2022 in Sin-El-Fil, a district of Beirut, Lebanon. The study population included a random sample of Lebanese adults and all Syrian adults residing in areas of low socioeconomic status. Data were collected through a telephone survey. The main outcome was uptake of at least one dose of the COVID-19 vaccine. Predictors of COVID-19 vaccine uptake were assessed using LASSO regression for Lebanese and Syrian nationalities in separate models.
Results: Of 2,045 participants, 79% were Lebanese, 18% Syrians and 3% of other nationalities. COVID-19 vaccination uptake was higher among Lebanese (85% (95%CI:82-86) compared to Syrians (47% (95% CI:43-51)) (P<0.001); adjusted odds ratio (aOR) 6.8 (95%CI:5.5-8.4). Predictors of uptake of one or more vaccine dose for Lebanese were older age, presence of an older adult in the household, higher education, greater asset-based wealth index, private healthcare coverage, feeling susceptible to COVID-19, belief in the safety and efficacy of vaccines and previous receipt of flu vaccine. For Syrians predictors were older age, male, completing school or higher education, receipt of cash assistance, presence of chronic illness, belief in the safety and efficacy of vaccines, previous receipt of flu vaccine, and legal residency status in Lebanon.
Conclusions: These findings indicate barriers for vaccine uptake in Syrian migrants and refugees, including legal residency status. They call for urgent action to enable equitable access to vaccines by raising awareness about the importance of vaccination and the targeting of migrant and refugee populations through vaccination campaigns.
Methods: This is a nested prognostic population-based cross-sectional analysis. Data was collected between June and October 2022 in Sin-El-Fil, a district of Beirut, Lebanon. The study population included a random sample of Lebanese adults and all Syrian adults residing in areas of low socioeconomic status. Data were collected through a telephone survey. The main outcome was uptake of at least one dose of the COVID-19 vaccine. Predictors of COVID-19 vaccine uptake were assessed using LASSO regression for Lebanese and Syrian nationalities in separate models.
Results: Of 2,045 participants, 79% were Lebanese, 18% Syrians and 3% of other nationalities. COVID-19 vaccination uptake was higher among Lebanese (85% (95%CI:82-86) compared to Syrians (47% (95% CI:43-51)) (P<0.001); adjusted odds ratio (aOR) 6.8 (95%CI:5.5-8.4). Predictors of uptake of one or more vaccine dose for Lebanese were older age, presence of an older adult in the household, higher education, greater asset-based wealth index, private healthcare coverage, feeling susceptible to COVID-19, belief in the safety and efficacy of vaccines and previous receipt of flu vaccine. For Syrians predictors were older age, male, completing school or higher education, receipt of cash assistance, presence of chronic illness, belief in the safety and efficacy of vaccines, previous receipt of flu vaccine, and legal residency status in Lebanon.
Conclusions: These findings indicate barriers for vaccine uptake in Syrian migrants and refugees, including legal residency status. They call for urgent action to enable equitable access to vaccines by raising awareness about the importance of vaccination and the targeting of migrant and refugee populations through vaccination campaigns.
| Original language | English |
|---|---|
| Article number | e001240 |
| Number of pages | 11 |
| Journal | BMJ Public Health |
| Volume | 2 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 9 Oct 2024 |
Bibliographical note
AcknowledgmentsWe would like to thank the “Community Action for Equity in Pandemic preparedness and control” CAEP Study Group for supporting this work (Aline Germani, Fadi El-Jardali). We thank Berthe Abi Zeid for her support and expertise in data analysis. We acknowledge BOT (Bridge. Outsource. Transform) for their assistance in collecting the data required for the success of this study and the study participants for their participation.
Data Availability Statement
The anonymized data can be obtained upon reasonable request from the Center for Research on Population and Health at the American University of Beirut ([email protected]).Funding
This work was funded by the International Development Research Centre (IDRC) – Canada (grant number: 103964; project number: 25941)
| Funders | Funder number |
|---|---|
| International Development Research Centre | 103964 |
Keywords
- COVID-19
- Vaccination
- Prediction model
- Health inequalities
Access to Document
- Ragi_etal_BMJPH_Development_Of_Prediction_VOR
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