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

INTRODUCTION: The 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. METHODS: Covid-19 epidemic curves fro...

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Autores principales: Pinto, Airandes de Sousa, dos Santos, Edval Gomes, Rodrigues, Carlos Alberto, Nunes, Paulo Cesar Mendes, da Cruz, Livia Almeida, Costa, Matheus Gomes Reis, Rocha, Manoel Otávio da Costa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sociedade Brasileira de Medicina Tropical - SBMT 2020
Materias:
Short Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341827/
https://www.ncbi.nlm.nih.gov/pubmed/32638889
http://dx.doi.org/10.1590/0037-8682-0331-2020
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author Pinto, Airandes de Sousa
dos Santos, Edval Gomes
Rodrigues, Carlos Alberto
Nunes, Paulo Cesar Mendes
da Cruz, Livia Almeida
Costa, Matheus Gomes Reis
Rocha, Manoel Otávio da Costa
author_facet Pinto, Airandes de Sousa
dos Santos, Edval Gomes
Rodrigues, Carlos Alberto
Nunes, Paulo Cesar Mendes
da Cruz, Livia Almeida
Costa, Matheus Gomes Reis
Rocha, Manoel Otávio da Costa
author_sort Pinto, Airandes de Sousa
collection PubMed
description INTRODUCTION: The 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. METHODS: Covid-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. RESULTS: The acceleration for all curves was obtained. CONCLUSIONS: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation.
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spelling pubmed-73418272020-07-10 Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves Pinto, Airandes de Sousa dos Santos, Edval Gomes Rodrigues, Carlos Alberto Nunes, Paulo Cesar Mendes da Cruz, Livia Almeida Costa, Matheus Gomes Reis Rocha, Manoel Otávio da Costa Rev Soc Bras Med Trop Short Communication INTRODUCTION: The 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. METHODS: Covid-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. RESULTS: The acceleration for all curves was obtained. CONCLUSIONS: Incorporating acceleration into an analysis of the Covid-19 time series may enable a better understanding of the epidemiological situation. Sociedade Brasileira de Medicina Tropical - SBMT 2020-07-06 /pmc/articles/PMC7341827/ /pubmed/32638889 http://dx.doi.org/10.1590/0037-8682-0331-2020 Text en https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License
spellingShingle Short Communication
Pinto, Airandes de Sousa
dos Santos, Edval Gomes
Rodrigues, Carlos Alberto
Nunes, Paulo Cesar Mendes
da Cruz, Livia Almeida
Costa, Matheus Gomes Reis
Rocha, Manoel Otávio da Costa
Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title_full Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title_fullStr Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title_full_unstemmed Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title_short Covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
title_sort covid-19 growth rate analysis: application of a low-complexity tool for understanding and comparing epidemic curves
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341827/
https://www.ncbi.nlm.nih.gov/pubmed/32638889
http://dx.doi.org/10.1590/0037-8682-0331-2020
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