Evidence map›Paper›PMID 35945937›Full record

ArticlePeerJ2022

The COVID-19 infodemic in Brazil: trends in Google search data.

Maria da Penha Harb, Lena Veiga E Silva, Nandamudi Vijaykumar, Marcelino Silva da Silva, Carlos Renato Lisboa Frances

Abstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
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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

5 authors.

Maria da Penha HarbInstitute of Technology, Federal University of Pará, Belém, Pará, Brazil.
Lena Veiga E SilvaInstitute of Technology, Federal University of Pará, Belém, Pará, Brazil.
Nandamudi VijaykumarNational Institute for Space Research, São José dos Campos, São Paulo, Brazil.
Marcelino Silva da SilvaFederal University of Western Pará, Santarém, Pará, Brazil.
Carlos Renato Lisboa FrancesInstitute of Technology, Federal University of Pará, Belém, Pará, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Since the beginning of the new coronavirus pandemic, there has been much information about the disease and the virus has been in the spotlight, shared and commented upon on the Internet. However, much of this information is infodemics and can interfere with the advancement of the disease and that way that populations act. Thus, Brazil is a country that requires attention, as despite the fact that in almost two years of pandemic it has shown a devastating numbers of deaths and number of cases, and generates false, distorted and malicious news about the pandemic. This work intends to understand the attitudes of the Brazilian population using infodemic queries from the Google Trends search tool and social and income variables. Methods: Data from infodemic research carried out on Google Trends, between January 1, 2020 and June 30, 2021, with socioeconomic data, such as income and education, were unified in a single database: standardization and exploratory and multivalued techniques based on grouping were used in the study. Results: In the analysis of the search trend of infodemic terms, it is clear that the categories of Prevention and Beliefs should stand out in Brazil, where there is a diverse culture. It is followed by the COVID-19 Treatment category, with treatments that were not those recommended by the authorities. Income transfer programs and information on socioeconomic variables did not have much impact on infodemic surveys, but it was observed that states where President Bolsonaro has more supporters had researched more infodemic information. Conclusions: In a country as geographically large as Brazil, it is important that political authorities go to great lengths to disseminate reliable information and monitor the infodemic in the media and on the internet. It was concluded that the denial of the pandemic and the influence of political leaders influenced the search for infodemic information, contributing to a disorganization in the control of the disease and prevention measures.

Indexed as

COVID-19BrazilCOVID-19 Drug TreatmentHumansInfodemicSARS-CoV-2Search EngineBrazilClusteringCOVID-19DenialismGoogle TrendsInfodemic

Identifiers

PMID35945937
PMCPMC9357377

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.