Defining drivers of under-immunization and vaccine hesitancy in refugee and migrant populations
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Some refugee and migrant populations globally showed lower uptake of COVID-19 vaccines and are also considered to be an under-immunized group for routine vaccinations. These communities may experience a range of barriers to vaccination systems, yet there is a need to better explore drivers of under-immunization and vaccine hesitancy in these mobile groups. METHODS: We did a global rapid review to explore drivers of under-immunization and vaccine hesitancy to define strategies to strengthen both COVID-19 and routine vaccination uptake, searching MEDLINE, Embase, Global Health PsycINFO and grey literature. Qualitative data were analysed thematically to identify drivers of under-immunization and vaccine hesitancy, and then categorized using the 'Increasing Vaccination Model'. RESULTS: Sixty-three papers were included, reporting data on diverse population groups, including refugees, asylum seekers, labour migrants and undocumented migrants in 22 countries. Drivers of under-immunization and vaccine hesitancy pertaining to a wide range of vaccines were covered, including COVID-19 (n = 27), human papillomavirus (13), measles or Measles-mumps-rubella (MMR) (3), influenza (3), tetanus (1) and vaccination in general. We found a range of factors driving under-immunization and hesitancy in refugee and migrant groups, including unique awareness and access factors that need to be better considered in policy and service delivery. Acceptability of vaccination was often deeply rooted in social and historical context and influenced by personal risk perception. CONCLUSIONS: These findings hold direct relevance to current efforts to ensure high levels of global coverage for a range of vaccines and to ensure that marginalized refugee and migrant populations are included in the national vaccination plans of low-, middle- and high-income countries. We found a stark lack of research from low- and middle-income and humanitarian contexts on vaccination in mobile groups. This needs to be urgently rectified if we are to design and deliver effective programmes that ensure high coverage for COVID-19 and routine vaccinations.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".