Evidence map›Paper›PMID 35309089›Full record

ArticleLancet regional health. Americas2022

Involvement of political and socio-economic factors in the spatial and temporal dynamics of COVID-19 outcomes in Brazil: A population-based study.

Diego Ricardo Xavier, Eliane Lima E Silva, Flávio Alves Lara, Gabriel R R E Silva, Marcus F Oliveira, Helen Gurgel, Christovam Barcellos

Abstract read
In one paragraph

Article in Lancet regional health. Americas, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

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

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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

7 authors.

Diego Ricardo XavierHealth Information Laboratory, Health Communication and Information Institute, Oswaldo Cruz Foundation (Fiocruz), Avenida Brasil 4365, Manguinhos, Rio de Janeiro, RJ 21045-900, Brazil.
Eliane Lima E SilvaInternational Joint Laboratory, LMI Sentinela (UnB - Fiocruz - IRD), Brasília-DF, Montpellier, France, Rio de Janeiro, RJ, Brazil.
Flávio Alves LaraCellular Microbiology Laboratory, Oswaldo Cruz Foundation (Fiocruz), Av. Brasil 4365, Rio de Janeiro, RJ, Brazil.
Gabriel R R E SilvaInternational Joint Laboratory, LMI Sentinela (UnB - Fiocruz - IRD), Brasília-DF, Montpellier, France, Rio de Janeiro, RJ, Brazil.
Marcus F OliveiraInstitute of Medical Biochemistry Leopoldo de Meis, Health Sciences Centre, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
Helen GurgelInternational Joint Laboratory, LMI Sentinela (UnB - Fiocruz - IRD), Brasília-DF, Montpellier, France, Rio de Janeiro, RJ, Brazil.
Christovam BarcellosHealth Information Laboratory, Health Communication and Information Institute, Oswaldo Cruz Foundation (Fiocruz), Avenida Brasil 4365, Manguinhos, Rio de Janeiro, RJ 21045-900, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Brazil has been severely impacted by COVID-19 pandemics that is aggravated by the absence of a scientifically-driven coordinated informative campaign and the interference in public health management, which ultimately affected health measures to avoid SARS-CoV2 spread. The decentralization and resultant conflicts in disease control activities produced different protection behaviours and local government measures. In the present study, we investigated how political partisanship and socio-economic factors determined the outcome of COVID-19 at the local level in Brazil. Methods: A retrospective study of COVID-19 deaths was carried out using mortality databases between Feb 2020, and Jun 2021 for the 5570 Brazilian municipalities. Socio-economic parameters including city categories, income and inequality indexes, health service quality and partisanship, assessed by the result of the second round of the 2018 Brazilian presidential elections, were included. Regression tree analysis was carried out to identify the statistical significance and conditioning relationships of variables. Findings: Municipalities that supported then-candidate Jair Bolsonaro in the 2018 elections were those that had the worst COVID-19 mortality rates, mainly during the second epidemic wave of 2021. This pattern was observed even considering structural inequalities among cities. Interpretation: In general, the first phase of the pandemic hit large and central cities hardest, while the second wave mostly impacted Bolsonarian municipalities, where scientific denialism among the population was stronger. Negative effects of partisanship towards the right-wing on COVID-19 outcomes counterbalances favourable socioeconomic indexes in affluent Brazilian cities. Our results underscore the fragility of public health policies which were undermined by the scientific denialism of right-wing supporters in Brazil. Funding: International joint laboratories of

Indexed as

BrazilCOVID-19Data miningPandemicPoliticsSocial inequalities

Identifiers

PMID35309089
PMCPMC8918677

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.