Vaccination models of delivery for refugees and migrants: a global scoping review
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".