Evidence map›Paper›PMID 37396687›Full record

ArticleJournal of migration and health2023

Socio-ecological barriers to access COVID-19 vaccination among Burmese irregular migrant workers in Thailand.

Tual Sawn Khai

Abstract read
In one paragraph

Article in Journal of migration and health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Tual Sawn KhaiSchool of Graduate Studies, Lingnan University, Hong Kong SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thailand is a migration hub in ASEAN (Association of Southeast Asian Nations), with more than 3.9 million migrant workers, accounting for 10% of the country's workforce. The government of Thailand has moved from a pandemic to an endemic state of living with the SAR-CoV2 virus as a new normal since over half of the population has been vaccinated. There is, however, an estimated 1.3 million irregular migrant workers in Thailand who are not covered by Social Security Schemes (SSS) and are likely to have not been vaccinated. This study examines the socio-ecological barriers to accessing vaccination among Burmese irregular migrant workers in Thailand. Qualitative and quantitative data were collected from NGO (Non-Government Organizations) workers and Burmese irregular migrants through an online survey and in-depth interviews. The study reported that over 90% of Burmese irregular migrants were unvaccinated. The main reasons for the low vaccination rate include exclusion from the vaccine distribution program, high cost of the vaccine, perceived low quality of vaccine, language barriers, lack of vaccine information, private and public discrimination against migrants, fear of being detained and deported, and difficulties in finding time and transportation to go to vaccination centres. The Thai government should employ culturally competent interpreters to disseminate vaccine information and potential side effects to encourage vaccinations in order to prevent further casualties and curb the global health crisis. Moreover, it is imperative that the Thai government provide free vaccines to all immigrants regardless of their status and amnesty from deportation and detention during the vaccination period.

Indexed as

Burmese/BurmaCOVID-19 vaccine barriersIrregular migrant workersThailandVaccination

Identifiers

PMID37396687
PMCPMC10292913

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.