Evidence map›Paper›PMID 38233051›Full record

ArticleBMJ open2024

The Brazilian COVID-19 vaccination campaign: a modelling analysis of sociodemographic factors on uptake.

Sabrina L Li, Carlos A Prete, Alexander E Zarebski, Andreza Aruska de Souza Santos, Ester C Sabino, Vitor H Nascimento, Chieh-Hsi Wu, Jane P Messina

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.7field-weighted citation impact, top 7% of its field
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

9 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. Social environment and services at the Special Immunobiological Reference Centers: epidemiological study, Minas Gerais, 2022-2024.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2026
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  6. Observational
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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

8 authors at 6 institutions in 3 countries.

Sabrina L Li *School of Geography, University of Nottingham, Nottingham, UK sabrina.li@nottingham.ac.uk.ORCID 0000-0002-1183-126X
Carlos A Prete *Department of Electronic Systems Engineering, University of São Paulo, São Paulo, Brazil.ORCID 0000-0002-3907-423X
Alexander E Zarebski *School of Mathematics and Statistics, The University of Melbourne, Melbourne, Victoria, Australia.ORCID 0000-0003-1824-7653
Andreza Aruska de Souza SantosOxford School of Global and Area Studies and Latin American Centre, University of Oxford, Oxford, UK.ORCID 0000-0003-3585-8683
Ester C SabinoDepartamento de Molestias Infecciosas e Parasitarias & Instituto de Medicina Tropical da Faculdade de Medicina, University of São Paulo, São Paulo, Brazil.ORCID 0000-0003-2623-5126
Vitor H NascimentoDepartment of Electronic Systems Engineering, University of São Paulo, São Paulo, Brazil.ORCID 0000-0002-0543-4735
Chieh-Hsi WuSchool of Mathematical Sciences, University of Southhampton, Southhampton, UK.ORCID 0000-0001-9386-725X
Jane P MessinaSchool of Geography and the Environment, University of Oxford, Oxford, UK.ORCID 0000-0001-7829-1272
Universidade de São Paulo · BRKing's College London · GBThe University of Melbourne · AUUniversity of Nottingham · GBUniversity of Oxford · GBUniversity of Roehampton · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDose shortages delayed access to COVID-19 vaccination. We aim to characterise inequality in two-dose vaccination by sociodemographic group across Brazil.

designThis is a cross-sectional study.

settingWe used data retrieved from the Brazilian Ministry of Health databases published between 17 January 2021 and 6 September 2021.

methodsWe assessed geographical inequalities in full vaccination coverage and dose by age, sex, race and socioeconomic status. We developed a Campaign Optimality Index to characterise inequality in vaccination access due to premature vaccination towards younger populations before older and vulnerable populations were fully vaccinated. Generalised linear regression was used to investigate the risk of death and hospitalisation by age group, socioeconomic status and vaccination coverage.

resultsVaccination coverage is higher in the wealthier South and Southeast. Men, people of colour and low-income groups were more likely to be only partially vaccinated due to missing or delaying a second dose. Vaccination started prematurely for age groups under 50 years which may have hindered uptake in older age groups. Vaccination coverage was associated with a lower risk of death, especially in older age groups (ORs 9.7 to 29.0, 95% CI 9. 4 to 29.9). Risk of hospitalisation was greater in areas with higher vaccination rates due to higher access to care and reporting.

conclusionsVaccination inequality persists between states, age and demographic groups despite increasing uptake. The association between hospitalisation rates and vaccination is attributed to preferential delivery to areas of greater transmission and access to healthcare.

Indexed as

COVID-19COVID-19 VaccinesAgedBrazilCross-Sectional StudiesFemaleHumansImmunization ProgramsMaleMiddle AgedSociodemographic FactorsSocioeconomic FactorsVaccinationCOVID-19 VaccinesCOVID-19Health EquityPUBLIC HEALTHVaccination

Identifiers

PMID38233051
PMCPMC10806735
OpenAlexW4390955611

What OpenQuestion 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 OpenQuestion graph.