An exploration of COVID-19 vaccination models for newcomer refugees and immigrants in Calgary, Canada
Notice bibliographique
Résumé
BACKGROUND: The World Health Organization stresses the need for tailored COVID-19 models of vaccination to meet the needs of diverse populations and ultimately reach high rates of vaccination. However, little evidence exists on how COVID-19 models of vaccination operated in the novel context of the pandemic, how vulnerable populations, such as refugees, experience COVID-19 vaccination systems in high-income countries, and what lessons may be learned from vaccination efforts with vulnerable populations. To address this gap, this study explored COVID-19 vaccine delivery models available to newcomer refugees and immigrants, and refugee experiences across different COVID-19 vaccine delivery models in Calgary, Canada, and surrounding area in 2021 and 2022, to understand the barriers, strengths, and strategies of models to support access to COVID-19 vaccination for newcomer refugees and immigrants. METHODS: Researchers conducted structured interviews with Government Assisted Refugees (n = 39), and semi-structured interviews with Privately Sponsored Refugees (n = 6), private refugee sponsors (n = 3), and stakeholders involved in vaccination systems (n = 13) in 2022. Thematic analysis was conducted to draw out themes related to barriers, strengths, and strategies of vaccine delivery models and the intersections with patient experiences. RESULTS: Newcomer refugee and immigrant focused vaccination models and strategies were explored. They demonstrated how partnerships between organizations, multi-pronged approaches, and culturally responsive services were crucial to navigate ongoing and emergent factors, such as vaccine hesitancy, mandates, and other determinants of under-vaccination. Many vaccination models presented through interviews were not specific to refugees and included immigrants, temporary residents, ethnocultural community members, and other vulnerable populations in their design. CONCLUSIONS: Increasing COVID-19 vaccine uptake for newcomer refugees and immigrants, is complex and requires trust, ongoing information provision, and local partnerships to address ongoing and emerging factors. Three key policy implications were drawn. First, findings demonstrated the need for flexible funding to offer outreach, translation, cultural interpretation, and to meet the basic needs of patients prior to engaging in vaccinations. Second, the research showed that embedding culturally responsive strategies within services ensures community needs are met. Finally, collaborating with partners that reflect the diverse needs of communities is crucial for the success of any health efforts serving newcomers.
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 | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,027 | 0,009 |
| Communication savante | 0,007 | 0,002 |
| Science ouverte | 0,003 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».