A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil

Abstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction...

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Autores principales: Yuanji Tang, Tamires D. A. Serdan, Amanda L. Alecrim, Diego R. Souza, Bruno R. M. Nacano, Flaviano L. R. Silva, Eliane B. Silva, Sarah O. Poma, Matheus Gennari-Felipe, Patrícia N. Iser-Bem, Laureane N. Masi, Sherry Tang, Adriana C. Levada-Pires, Elaine Hatanaka, Maria F. Cury-Boaventura, Fernanda T. Borges, Tania C. Pithon-Curi, Marli C. Curpertino, Jarlei Fiamoncini, Carol Gois Leandro, Renata Gorjao, Rui Curi, Sandro Massao Hirabara
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Publicado: Nature Portfolio 2021
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spelling oai:doaj.org-article:6489676b149943b9be31d453fad56b732021-12-02T16:28:06ZA simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil10.1038/s41598-021-95815-92045-2322https://doaj.org/article/6489676b149943b9be31d453fad56b732021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95815-9https://doaj.org/toc/2045-2322Abstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.Yuanji TangTamires D. A. SerdanAmanda L. AlecrimDiego R. SouzaBruno R. M. NacanoFlaviano L. R. SilvaEliane B. SilvaSarah O. PomaMatheus Gennari-FelipePatrícia N. Iser-BemLaureane N. MasiSherry TangAdriana C. Levada-PiresElaine HatanakaMaria F. Cury-BoaventuraFernanda T. BorgesTania C. Pithon-CuriMarli C. CurpertinoJarlei FiamonciniCarol Gois LeandroRenata GorjaoRui CuriSandro Massao HirabaraNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Yuanji Tang
Tamires D. A. Serdan
Amanda L. Alecrim
Diego R. Souza
Bruno R. M. Nacano
Flaviano L. R. Silva
Eliane B. Silva
Sarah O. Poma
Matheus Gennari-Felipe
Patrícia N. Iser-Bem
Laureane N. Masi
Sherry Tang
Adriana C. Levada-Pires
Elaine Hatanaka
Maria F. Cury-Boaventura
Fernanda T. Borges
Tania C. Pithon-Curi
Marli C. Curpertino
Jarlei Fiamoncini
Carol Gois Leandro
Renata Gorjao
Rui Curi
Sandro Massao Hirabara
A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
description Abstract We propose herein a mathematical model to predict the COVID-19 evolution and evaluate the impact of governmental decisions on this evolution, attempting to explain the long duration of the pandemic in the 26 Brazilian states and their capitals well as in the Federative Unit. The prediction was performed based on the growth rate of new cases in a stable period, and the graphics plotted with the significant governmental decisions to evaluate the impact on the epidemic curve in each Brazilian state and city. Analysis of the predicted new cases was correlated with the total number of hospitalizations and deaths related to COVID-19. Because Brazil is a vast country, with high heterogeneity and complexity of the regional/local characteristics and governmental authorities among Brazilian states and cities, we individually predicted the epidemic curve based on a specific stable period with reduced or minimal interference on the growth rate of new cases. We found good accuracy, mainly in a short period (weeks). The most critical governmental decisions had a significant temporal impact on pandemic curve growth. A good relationship was found between the predicted number of new cases and the total number of inpatients and deaths related to COVID-19. In summary, we demonstrated that interventional and preventive measures directly and significantly impact the COVID-19 pandemic using a simple mathematical model. This model can easily be applied, helping, and directing health and governmental authorities to make further decisions to combat the pandemic.
format article
author Yuanji Tang
Tamires D. A. Serdan
Amanda L. Alecrim
Diego R. Souza
Bruno R. M. Nacano
Flaviano L. R. Silva
Eliane B. Silva
Sarah O. Poma
Matheus Gennari-Felipe
Patrícia N. Iser-Bem
Laureane N. Masi
Sherry Tang
Adriana C. Levada-Pires
Elaine Hatanaka
Maria F. Cury-Boaventura
Fernanda T. Borges
Tania C. Pithon-Curi
Marli C. Curpertino
Jarlei Fiamoncini
Carol Gois Leandro
Renata Gorjao
Rui Curi
Sandro Massao Hirabara
author_facet Yuanji Tang
Tamires D. A. Serdan
Amanda L. Alecrim
Diego R. Souza
Bruno R. M. Nacano
Flaviano L. R. Silva
Eliane B. Silva
Sarah O. Poma
Matheus Gennari-Felipe
Patrícia N. Iser-Bem
Laureane N. Masi
Sherry Tang
Adriana C. Levada-Pires
Elaine Hatanaka
Maria F. Cury-Boaventura
Fernanda T. Borges
Tania C. Pithon-Curi
Marli C. Curpertino
Jarlei Fiamoncini
Carol Gois Leandro
Renata Gorjao
Rui Curi
Sandro Massao Hirabara
author_sort Yuanji Tang
title A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
title_short A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
title_full A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
title_fullStr A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
title_full_unstemmed A simple mathematical model for the evaluation of the long first wave of the COVID-19 pandemic in Brazil
title_sort simple mathematical model for the evaluation of the long first wave of the covid-19 pandemic in brazil
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/6489676b149943b9be31d453fad56b73
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