Evidence map›Paper›PMID 32638889›Full record

ArticleRevista da Sociedade Brasileira de Medicina Tropical2020

Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves.

Airandes de Sousa Pinto, Edval Gomes Dos Santos Júnior, Carlos Alberto Rodrigues, Paulo Cesar Mendes Nunes, Livia Almeida da Cruz, Matheus Gomes Reis Costa, Manoel Otávio da Costa Rocha

Abstract read
In one paragraph

Article in Revista da Sociedade Brasileira de Medicina Tropical, 2020. 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

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

2 citing papers in PubMed.

  1. Article
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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.

Airandes de Sousa PintoDepartamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, BA, Brasil.
Edval Gomes Dos Santos JúniorDepartamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, BA, Brasil.
Carlos Alberto RodriguesDepartamento de Ciências Exatas, Universidade Estadual de Feira de Santana, Feira de Santana, BA, Brasil.
Paulo Cesar Mendes NunesDepartamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, BA, Brasil.
Livia Almeida da CruzGrupo Baiano de Oncologia, Feira de Santana, BA, Brasil.
Matheus Gomes Reis CostaDepartamento de Saúde, Universidade Estadual de Feira de Santana, Feira de Santana, BA, Brasil.
Manoel Otávio da Costa RochaPrograma de Pós-Graduação em Infectologia e Medicina Tropical, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe acceleration of new cases is important for the characterization and comparison of epidemic curves. The objective of this study was to quantify the acceleration of daily confirmed cases and death curves using the polynomial interpolation method.

methodsCovid-19 epidemic curves from Brazil, Germany, the United States, and Russia were obtained. We calculated the instantaneous acceleration of the curve using the first derivative of the representative polynomial.

resultsThe acceleration for all curves was obtained.

conclusionsIncorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation.

Indexed as

BetacoronavirusBrazilCoronavirus InfectionsCOVID-19Data AnalysisGermanyHumansIncidenceNormal DistributionPandemicsPneumonia, ViralRussiaSARS-CoV-2United States

Identifiers

PMID32638889
PMCPMC7341827

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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.