Evidence map›Paper›PMID 37937651›Full record

ArticleRevista de saude publica2023

Were public interventions relevant for containing the covid-19 pandemic in Brazil in 2020?

Vitória Berg Cattani, Thaís Araujo Dos Santos, Marcelo Ribeiro-Alves, Julio Castro-Alves

Abstract read
In one paragraph

Article in Revista de saude publica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Vitória Berg CattaniFundação Oswaldo Cruz . Instituto Nacional de Infectologia Evandro Chagas . Rio de Janeiro , RJ , Brasil .ORCID http://orcid.org/0000-0002-8148-403X
Thaís Araujo Dos SantosFundação Oswaldo Cruz . Instituto Nacional de Infectologia Evandro Chagas . Rio de Janeiro , RJ , Brasil .ORCID http://orcid.org/0000-0003-4870-2960
Marcelo Ribeiro-AlvesFundação Oswaldo Cruz . Instituto Nacional de Infectologia Evandro Chagas . Rio de Janeiro , RJ , Brasil .ORCID http://orcid.org/0000-0002-8663-3364
Julio Castro-AlvesFundação Oswaldo Cruz . Instituto Nacional de Infectologia Evandro Chagas . Rio de Janeiro , RJ , Brasil .ORCID http://orcid.org/0000-0003-4163-6112

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveFlattening the curve was the most promoted public health strategy worldwide, during the pandemic, to slow down the spread of the SARS-CoV-2 virus, and, consequently, to avoid overloading the healthcare systems. In Brazil, a relative success of public policies was evidenced. However, the association between public policies and the "flatten the curve" objectives remain unclear, as well as the association of different policies to reach this aim. This study aims to verify if the adoption of different public policies was associated with the flattening of the infection and death curves by covid-19 first wave in 2020.

methodsData from the Sistema de Informação da Vigilância Epidemiológica da Gripe (Influenza Epidemiological Surveillance Information System - SIVEP-Gripe) and the Instituto Brasileiro de Geografia e Estatística (Brazilian Institute of Geography and Statistics - IBGE) were used to compute standardized incidence and mortality rates. The Oxford Covid-19 Government Response Tracker (OxCGRT) was used to obtain information about governmental responses related to the mitigation of pandemic effects, and the Human Development Index (HDI) was used as a measure of socioeconomic status. A non-linear least-square method was used to estimate parameters of the five-parameter sigmoidal curve, obtaining the time to reach the peak and the incremental rate of the curves. Additionally, ordinary least-square linear models were used to assess the correlation between the curves and the public policies adopted.

resultsOut of 51 municipalities, 261,326 patients had SARS-CoV-2 infection. Stringency Index was associated with reducing covid-19 incremental incidence and death rates,in addition to delaying the time to reach the peak of both pandemic curves. Considering both parameters, economic support policies did not affect the incidence nor the mortality rate curves.

conclusionThe evidence highlighted the importance and effectiveness of social distancing policies during the first year of the pandemic in Brazil, flattening the curves of mortality and incidence rates. Other policies, such as those focused on economic support, were not effective in flattening the curves but met humanitarian and social outcomes.

Indexed as

COVID-19BrazilHumansPandemicsPublic PolicySARS-CoV-2

Identifiers

PMID37937651
PMCPMC10609658

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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.