Evidence map›Paper›PMID 39363165›Full record

ArticleBMC health services research2024

Assessment of the COVID-19 impact on the Brazilian Unified Health System (SUS) financing: an analysis of the financing dynamics of 2020 and 2021.

Ana Carolina Costa Corrêa, Maria Luísa Oliveira Rigotti, Hugo Dilhermando Souza Lacerda, Bruno Pérez Ferreira

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Ana Carolina Costa CorrêaDepartment of Business Administration, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil. carolcorrea@yahoo.com.
Maria Luísa Oliveira RigottiDepartment of Economic Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Hugo Dilhermando Souza LacerdaDepartment of Economic Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
Bruno Pérez FerreiraDepartment of Business Administration, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAfter the establishment of the public health emergency of international concern in 2020, health systems worldwide and in Brazil observed the need to apply more extraordinary logistical efforts and possibly resources to combat the imminent pandemic.

methodsUsing the historical series of public expenditures of the National Health Fund (FNS), 2015 to 2021, the number of confirmed cases of COVID-19, and a seasonal ARIMAX model, we sought to assess how the increase in the new virus infections affected the systematic financing of the SUS in Brazil.

resultsThere were signs of seasonality and an increasing trend in the expenditure variable, which in practical terms, only indicated that the resource contributions followed an increasing trajectory already underway before the advent of the pandemic. The 1% increase in COVID-19 cases, with a one-month lag, contributes to the 0.062% increase in the variation in FNS expenditures but a decrease of 0.058% with a two-month lag.

conclusionThe tests showed no evidence to confirm a positive shift on FNS spending growth trajectory due to the increase of COVID-19 cases, only observing a significant increase one month after the occurrence of COVID cases, probably due to their worsening after this period, which was followed by a similar and comparable decrease in percentage of growth in the following month.

Indexed as

COVID-19Health ExpendituresBrazilFinancing, GovernmentHealthcare FinancingHumansNational Health ProgramsPandemicsSARS-CoV-2ARIMAXCOVID-19FinancingPandemicSpending policyUnified Health System (SUS)

Identifiers

PMID39363165
PMCPMC11447955

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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.