Development of prediction models of COVID-19 vaccine uptake among Lebanese and Syrians in a district of Beirut, Lebanon: a population-based study
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Notice bibliographique
Résumé
Introduction: Vaccines are essential to prevent infection and reduce the 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 were 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 the uptake of at least one dose of the COVID-19 vaccine. Predictors of COVID-19 vaccine uptake were assessed using the Least Absolute Shrinkage and Selection Operator regression for Lebanese and Syrian nationalities in separate models. Results: Of 2028 participants, 79% were Lebanese, 18% Syrians and 3% of other nationalities. COVID-19 vaccination uptake was higher among Lebanese (85% (95% CI 82% to 86%) compared to Syrians (47% (95% CI 43% to 51%)) (p<0.001); adjusted OR 6.2 (95% CI 4.9 to 7.7). Predictors of uptake of one or more COVID-19 vaccine doses 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 the influenza vaccine. For Syrians, predictors were older age, male sex, completing school or higher education, receipt of cash assistance, presence of chronic illness, belief in the safety and efficacy of vaccines, previous receipt of the influenza vaccine and possession of a legal residency permit in Lebanon. Conclusions: These findings indicate barriers to vaccine uptake among Syrian refugees and migrants, including legal residency status. These findings 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.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle