Vaccination models of delivery for refugees and migrants: a global scoping review
Notice bibliographique
Résumé
BACKGROUND: Refugees and migrants face inequities in healthcare and vaccination access. Diverse vaccination programs have been implemented globally among refugee and migrant populations targeting vaccine hesitancy and other barriers to vaccination. The aim of this scoping review was to provide an overview of current models of vaccination delivery of COVID-19 and other vaccines to inform best practices of vaccine delivery for refugee and migrant populations. METHODS: A scoping review was conducted according to PRISMA guidelines. Eleven electronic databases, including SCOPUS, Embase, Medline, and Web of Science, as well as grey literature, were searched with keywords including: 'COVID-19', 'vaccines','immunizations', 'refugees', 'asylum seekers', and 'migrants'. The search included all studies published between January 2000 and October 2023 to capture COVID-19 and other vaccine models of delivery. The main outcome was models of delivery of COVID-19 vaccines and other vaccines for refugee or migrant populations. Models of vaccination delivery were reviewed and analyzed with the 2022 World Health Organization's Strengthening COVID-19 vaccine demand and uptake in refugees and migrants: An operational guide (2022 WHO Guide) as a guiding framework. RESULTS: A total of n = 11,825 unique studies were identified through database searches. Thirty-three (n = 33) studies were included in this review. Fifteen studies (n = 15) related to the COVID-19 vaccine and eighteen studies (n = 18) focused on other vaccines. Studies were mainly implemented in high-income countries with the majority from the United States (n = 17). Studies targeted various migrant groupings (i.e., migrants, immigrants, refugees, and asylum-seekers), ethnic groups, and age groups globally, including various underserved populations including migrant populations. There was general alignment with most of the 2022 WHO Guide priority action areas across both COVID-19 and other vaccine studies, pointing to ongoing understandings of the importance of administratively accessible and culturally/linguistically appropriate models of vaccine delivery for refugee and migrant populations. Increasingly dominant approaches in the COVID-19 pandemic include multipronged strategies with wide community and multisectoral collaborations to co-design strategies addressing barriers. Additionally, COVID-19 vaccination models increasingly utilized innovative social media and customization strategies, including targeted communication campaigns responsive to misinformation. Although there are increased calls for the use of data to design and evaluate interventions, notable gaps remain in the collection, use and reporting of data used to conduct interventions. CONCLUSIONS: Findings summarize vaccination models of delivery for COVID-19 and other vaccines for diverse refugee and migrant populations globally. Healthcare professionals, policy makers, and vaccination campaign planners can draw and build from strategies employed in other settings as aligned with WHO priority actions to increase equitable access to vaccines for refugee and migrant communities. Further collection and use of disaggregated and real-time data to inform and evaluate customized strategies for specific migrant groups is recommended to improve understandings of equitable vaccine delivery models.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,008 |
| Bibliométrie | 0,014 | 0,012 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».