Evidence map›Paper›PMID 35581560›Full record

ArticleBMC infectious diseases2022

The assistance gaps in combating COVID-19 in Brazil: for whom, where and when vaccination occurs.

Rafael da Silveira Moreira, Emilly Guaris Costa, Lucas Fernando Rodrigues Dos Santos, Luiz Henrique Lélis Miranda, Raiany Rodrigues de Oliveira, Ricardo Fusano Romão, Rodolfo Ferreira Cozer, Sarah Cavalcanti Guedes

Abstract read
In one paragraph

Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
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  4. 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.

Rafael da Silveira MoreiraPublic Health Department, Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Recife, Pernambuco, Brazil. rafael.moreira@fiocruz.br.ORCID http://orcid.org/0000-0003-0079-2901
Emilly Guaris CostaCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-5099-9313
Lucas Fernando Rodrigues Dos SantosPublic Health Department, Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-7993-0918
Luiz Henrique Lélis MirandaCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0003-0527-2753
Raiany Rodrigues de OliveiraCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-6792-8597
Ricardo Fusano RomãoCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-2893-306X
Rodolfo Ferreira CozerCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-4216-2871
Sarah Cavalcanti GuedesCentre for Medical Sciences, Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil.ORCID http://orcid.org/0000-0002-6330-9262

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFollowing the emergence of the COVID-19 pandemic, the number of infected Brazilian people has increased dramatically since February 2020, with Brazil being amongst the countries with the highest number of cases and deaths. Brazilian vaccination began in January 2021, aimed at priority groups. This study analysed the spatial and temporal evolution of vaccination in Brazil between the 3rd and 21st epidemiological weeks (EW) of 2021.

methodsSpatial and temporal analyses were performed comprising 19 EW. Cases were structured into priority groups-elderly population (EP); healthcare workers (HW); indigenous and quilombola populations (I/Q), dose, vaccine (CoronaVac or AstraZeneca), and place of vaccination. A sweep test was performed to identify vaccination rate clusters. Vaccination rates (VR) were calculated according to a spatial window for each Health Region, indicating clusters above/below expected VR. Based on the discrete Poisson probability model, spatial analysis was performed to detect high/low VR clusters, which were converted into Kernel maps. Points were generated from SaTScan analyses associated with Health Region centroids. Temporal analysis of VR was carried out to identify significant trends, and results were converted into temporal cluster graphs. P-value ≤ 0.05 was adopted.

resultsSoutheast region concentrated most of the vaccines of EP and HW, followed by the Northeast. The latter region had the largest contingent of I/Q vaccinated. In all priority age groups and all regions, a higher percentage of complete CoronaVac vaccination schedules were observed compared with AstraZeneca. The temporal analysis identified high VR clusters of CoronaVac first and second dose in the early weeks, except for the EP; of AstraZeneca first dose, only for HW in the early weeks, and for EP and I/Q in the final weeks; of AstraZeneca second dose for all priority groups in the final weeks. I/Q populations had the lowest general VR. The spatial profile of VR indicated significant regional cluster differences between the priority groups.

conclusionThis study highlights the importance of establishing vaccination priority groups, considering the asymmetries that a pandemic can trigger, notably in vast geographic areas, to contemplate the main objective of vaccination: to prevent casualties.

Indexed as

COVID-19VaccinesAgedBrazilCOVID-19 VaccinesHumansPandemicsSARS-CoV-2VaccinationCOVID-19 VaccinesVaccinesBrazilCOVID-19 pandemicsImmunisation programsSocial vulnerabilitySpatial analysisVaccination coverage

Identifiers

PMID35581560
PMCPMC9110943

What OpenQuestion holds

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Registered trials

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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.