Evidence map›Paper›PMID 40018546›Full record

ArticleBMJ public health2024

Development of prediction models of COVID-19 vaccine uptake among Lebanese and Syrians in a district of Beirut, Lebanon: a population-based study.

Marie-Elizabeth Ragi, Hala Ghattas, Hazar Shamas, Jocelyn DeJong, Nada M Melhem, Stephen J McCall, CAEP Study Group

Erratum issuedAbstract read
In one paragraph

Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Marie-Elizabeth RagiCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.ORCID 0000-0002-8999-5803
Hala GhattasCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Hazar ShamasCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Jocelyn DeJongDepartment of Epidemiology and Population Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Nada M MelhemMedical Laboratory Sciences Program, Division of Health Professions, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
Stephen J McCallCenter for Research on Population and Health, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon.
CAEP Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Vaccines are essential to prevent infection and reduce the morbidity of infectious diseases. Previous evidence has shown that migrants and refugees are particularly vulnerable to exclusion and discrimination, and low COVID-19 vaccine intention and uptake were observed among refugees globally. This study aimed to develop and internally validate prediction models of COVID-19 vaccine uptake by nationality. Methods: This is a nested prognostic population-based cross-sectional analysis. Data were collected between June and October 2022 in Sin-El-Fil, a district of Beirut, Lebanon. The study population included a random sample of Lebanese adults and all Syrian adults residing in areas of low socioeconomic status. Data were collected through a telephone survey. The main outcome was the uptake of at least one dose of the COVID-19 vaccine. Predictors of COVID-19 vaccine uptake were assessed using the Least Absolute Shrinkage and Selection Operator regression for Lebanese and Syrian nationalities in separate models. Results: Of 2028 participants, 79% were Lebanese, 18% Syrians and 3% of other nationalities. COVID-19 vaccination uptake was higher among Lebanese (85% (95% CI 82% to 86%) compared to Syrians (47% (95% CI 43% to 51%)) (p<0.001); adjusted OR 6.2 (95% CI 4.9 to 7.7). Predictors of uptake of one or more COVID-19 vaccine doses for Lebanese were older age, presence of an older adult in the household, higher education, greater asset-based wealth index, private healthcare coverage, feeling susceptible to COVID-19, belief in the safety and efficacy of vaccines and previous receipt of the influenza vaccine. For Syrians, predictors were older age, male sex, completing school or higher education, receipt of cash assistance, presence of chronic illness, belief in the safety and efficacy of vaccines, previous receipt of the influenza vaccine and possession of a legal residency permit in Lebanon. Conclusions: These findings indicate barriers to vaccine uptake among Syrian refugees and migrants, including legal residency status. These findings call for urgent action to enable equitable access to vaccines by raising awareness about the importance of vaccination and the targeting of migrant and refugee populations through vaccination campaigns.

Indexed as

Community HealthCOVID-19Public HealthVaccination

Identifiers

PMID40018546
PMCPMC11816316

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.