Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study

Detalhes bibliográficos
Autor(a) principal: Melo, Géssyca Cavalcante de
Data de Publicação: 2020
Outros Autores: Araújo Neto, Renato Américo de, Araújo, Karina Conceição Gomes Machado de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/42190
Resumo: The COVID-19 death rate in Northeast Brazil is much higher when compared to the national average, demanding a study into the prognosis of the region for planning control measures and preventing the collapse of the health care system. We estimated the potential total cumulative cases of COVID-19 in the region for the next three months. Our study included all confirmed cases, from March 8 until April 28, 2020, collected from the official website that reports the situation of COVID-19 infections in Brazil. The Boltzmann function was applied to a data simulation for each set of data regarding different states. The model data were well fitted, with R2 values close to 0.999. Up to April 28, 20,665 cases were confirmed in the region. The state of Ceará has the highest rate of accumulated cases per 100,000 inhabitants (75.75), followed by Pernambuco. We estimated that the states of Ceará, Sergipe and Paraíba will experience a dramatic increase in the rate of cumulative cases until July 31. Maranhão, Pernambuco, Rio Grande do Norte and Piauí showed a more discreet increase in the model. For Bahia and Alagoas, a 4.7 and 6.6-fold increase in the rate was estimated, respectively. We estimate a substantial increase in the rate of cumulative cases per 100,000 inhabitants in the region within three months, especially for Ceará, Sergipe and Paraíba. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can help planning the measures to contain COVID-19.
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spelling Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling studyProjeção da taxa de casos acumulados de COVID-19 no Nordeste brasileiro: um estudo de modelagem com base na função de BoltzmannPrevisión de la tasa de incidencia acumulada por infección de COVID-19 en la región nordeste de Brasil: un estudio de modelado basado en funciones de BoltzmannCOVID-19EpidemiologyMathematical modelsPandemicEpidemiologiaModelos teóricosPandemiasEpidemiologíaThe COVID-19 death rate in Northeast Brazil is much higher when compared to the national average, demanding a study into the prognosis of the region for planning control measures and preventing the collapse of the health care system. We estimated the potential total cumulative cases of COVID-19 in the region for the next three months. Our study included all confirmed cases, from March 8 until April 28, 2020, collected from the official website that reports the situation of COVID-19 infections in Brazil. The Boltzmann function was applied to a data simulation for each set of data regarding different states. The model data were well fitted, with R2 values close to 0.999. Up to April 28, 20,665 cases were confirmed in the region. The state of Ceará has the highest rate of accumulated cases per 100,000 inhabitants (75.75), followed by Pernambuco. We estimated that the states of Ceará, Sergipe and Paraíba will experience a dramatic increase in the rate of cumulative cases until July 31. Maranhão, Pernambuco, Rio Grande do Norte and Piauí showed a more discreet increase in the model. For Bahia and Alagoas, a 4.7 and 6.6-fold increase in the rate was estimated, respectively. We estimate a substantial increase in the rate of cumulative cases per 100,000 inhabitants in the region within three months, especially for Ceará, Sergipe and Paraíba. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can help planning the measures to contain COVID-19.A Região Nordeste do Brasil tem uma taxa de letalidade muito mais elevada por COVID-19, comparado com a média nacional, o que exige uma investigação do prognóstico da região para o planejamento de medidas de controle e para prevenir o colapso do sistema de saúde. Estimamos o total potencial de casos acumulados de COVID-19 na região nos próximos três meses. O estudo incluiu todos os casos confirmados de COVID-19, desde o primeiro caso confirmado, em 8 de março, até 28 de abril de 2020, coletados no site oficial que relata a situação das infecções por COVID-19 no Brasil. A função de Boltzmann foi aplicada a uma simulação de dados para cada conjunto de dados dos diversos estados do Nordeste. Os dados do modelo mostraram bom ajuste, com valores de R2 próximos a 0,999. Até 28 de abril, haviam sido confirmados 20.665 casos na Região Nordeste. O estado do Ceará apresenta a maior taxa de casos acumulados por 100.000 habitantes (75,75), seguido pelo estado de Pernambuco. Estimamos que Ceará, Sergipe e Paraíba apresentarão um aumento dramático na taxa de casos acumulados até 31 de julho. Maranhão, Pernambuco, Rio Grande do Norte e Piauí mostraram aumentos mais discretos de acordo com o modelo. Para Bahia e Alagoas, foram estimados aumentos de 4,7 e 6,6 vezes nas taxas, respectivamente. Estimamos um aumento substancial na taxa de casos acumulados por 100.000 habitantes na Região Nordeste ao longo dos próximos três meses, especialmente no Ceará, Sergipe e Paraíba. A função de Boltzmann mostrou ser uma ferramenta simples para projeções epidemiológicas, podendo auxiliar no planejamento de medidas para conter a COVID-19.Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz2020-08-04T12:00:47Z2020-08-04T12:00:47Z2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfMELO, G. C. de; ARAÚJO NETO, R. A. de; ARAÚJO, K. C. G. M. de. Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study. Cadernos de Saúde Pública, Rio de Janeiro, v. 36, n. 6, 2020.http://repositorio.ufla.br/jspui/handle/1/42190Cadernos de Saúde Públicareponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessMelo, Géssyca Cavalcante deAraújo Neto, Renato Américo deAraújo, Karina Conceição Gomes Machado deeng2020-08-04T12:00:47Zoai:localhost:1/42190Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2020-08-04T12:00:47Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
Projeção da taxa de casos acumulados de COVID-19 no Nordeste brasileiro: um estudo de modelagem com base na função de Boltzmann
Previsión de la tasa de incidencia acumulada por infección de COVID-19 en la región nordeste de Brasil: un estudio de modelado basado en funciones de Boltzmann
title Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
spellingShingle Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
Melo, Géssyca Cavalcante de
COVID-19
Epidemiology
Mathematical models
Pandemic
Epidemiologia
Modelos teóricos
Pandemias
Epidemiología
title_short Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
title_full Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
title_fullStr Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
title_full_unstemmed Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
title_sort Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study
author Melo, Géssyca Cavalcante de
author_facet Melo, Géssyca Cavalcante de
Araújo Neto, Renato Américo de
Araújo, Karina Conceição Gomes Machado de
author_role author
author2 Araújo Neto, Renato Américo de
Araújo, Karina Conceição Gomes Machado de
author2_role author
author
dc.contributor.author.fl_str_mv Melo, Géssyca Cavalcante de
Araújo Neto, Renato Américo de
Araújo, Karina Conceição Gomes Machado de
dc.subject.por.fl_str_mv COVID-19
Epidemiology
Mathematical models
Pandemic
Epidemiologia
Modelos teóricos
Pandemias
Epidemiología
topic COVID-19
Epidemiology
Mathematical models
Pandemic
Epidemiologia
Modelos teóricos
Pandemias
Epidemiología
description The COVID-19 death rate in Northeast Brazil is much higher when compared to the national average, demanding a study into the prognosis of the region for planning control measures and preventing the collapse of the health care system. We estimated the potential total cumulative cases of COVID-19 in the region for the next three months. Our study included all confirmed cases, from March 8 until April 28, 2020, collected from the official website that reports the situation of COVID-19 infections in Brazil. The Boltzmann function was applied to a data simulation for each set of data regarding different states. The model data were well fitted, with R2 values close to 0.999. Up to April 28, 20,665 cases were confirmed in the region. The state of Ceará has the highest rate of accumulated cases per 100,000 inhabitants (75.75), followed by Pernambuco. We estimated that the states of Ceará, Sergipe and Paraíba will experience a dramatic increase in the rate of cumulative cases until July 31. Maranhão, Pernambuco, Rio Grande do Norte and Piauí showed a more discreet increase in the model. For Bahia and Alagoas, a 4.7 and 6.6-fold increase in the rate was estimated, respectively. We estimate a substantial increase in the rate of cumulative cases per 100,000 inhabitants in the region within three months, especially for Ceará, Sergipe and Paraíba. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can help planning the measures to contain COVID-19.
publishDate 2020
dc.date.none.fl_str_mv 2020-08-04T12:00:47Z
2020-08-04T12:00:47Z
2020
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv MELO, G. C. de; ARAÚJO NETO, R. A. de; ARAÚJO, K. C. G. M. de. Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study. Cadernos de Saúde Pública, Rio de Janeiro, v. 36, n. 6, 2020.
http://repositorio.ufla.br/jspui/handle/1/42190
identifier_str_mv MELO, G. C. de; ARAÚJO NETO, R. A. de; ARAÚJO, K. C. G. M. de. Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based modeling study. Cadernos de Saúde Pública, Rio de Janeiro, v. 36, n. 6, 2020.
url http://repositorio.ufla.br/jspui/handle/1/42190
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz
publisher.none.fl_str_mv Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz
dc.source.none.fl_str_mv Cadernos de Saúde Pública
reponame:Repositório Institucional da UFLA
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institution UFLA
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