Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | preprint |
Idioma: | por |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/1080 |
Resumo: | Objective: Estimate the maximum number of prevalent cases of COVID-19, admitted to intensive care units, and the time of this peak, in Porto Alegre. Methods: A mathematical model of differential equations called SEIHDR (Susceptible, Exposed, Infected, Hospitalized, Dead, Recovered) have been used to analyze the cases of hospitalization for COVID-19 in Porto Alegre and RS, from March 9 to July 25, 2020 in order to extract the parameters to make up an epidemiological curve of the prevalent cases hospitalized in general ward and in intensive care units, as well as how to estimate the prevalence of patients on invasive mechanical ventilation. Finally, we adjusted some parameters of this curve based on the current prevalent cases hospitalized. Results: The mathematical model corrected for the pandemic data until July 25 projected a peak of 1,354 prevalent hospitalized cases: 562 patients admitted to the intensive care unit with 378 under mechanical ventilation on September 12, 2020 (37th epidemiological week). In addition, there would be a peak of 62,514 prevalent cases of infected with COVID-19 at the beginning of the same month (36th epidemiological week. We calculated for the pandemic a basic reproduction number of 1.53 and effective reproduction number of 1.29 to July 25, 2020. Conclusion: As the current number of beds in the intensive care unit would be insufficient to meet this demand, we suggest an increase in the number of critical beds in order to avoid the collapse of the health system in Porto Alegre. |
id |
SCI-1_ad6d058803fb66642427d57b62a8bfd7 |
---|---|
oai_identifier_str |
oai:ops.preprints.scielo.org:preprint/1080 |
network_acronym_str |
SCI-1 |
network_name_str |
SciELO Preprints |
repository_id_str |
|
spelling |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDREstimativa de pacientes hospitalizados por COVID-19 em unidade de terapia intensiva no pico da pandemia em Porto Alegre: Estudo com modelo epidemiológico SEIHDRInfecções por CoronavívusUnidades de Terapia IntensivaHospitalizaçãoCuidados CríticosCoronavirus infectionHospitalizationCritical CareIntensive Care UnitsObjective: Estimate the maximum number of prevalent cases of COVID-19, admitted to intensive care units, and the time of this peak, in Porto Alegre. Methods: A mathematical model of differential equations called SEIHDR (Susceptible, Exposed, Infected, Hospitalized, Dead, Recovered) have been used to analyze the cases of hospitalization for COVID-19 in Porto Alegre and RS, from March 9 to July 25, 2020 in order to extract the parameters to make up an epidemiological curve of the prevalent cases hospitalized in general ward and in intensive care units, as well as how to estimate the prevalence of patients on invasive mechanical ventilation. Finally, we adjusted some parameters of this curve based on the current prevalent cases hospitalized. Results: The mathematical model corrected for the pandemic data until July 25 projected a peak of 1,354 prevalent hospitalized cases: 562 patients admitted to the intensive care unit with 378 under mechanical ventilation on September 12, 2020 (37th epidemiological week). In addition, there would be a peak of 62,514 prevalent cases of infected with COVID-19 at the beginning of the same month (36th epidemiological week. We calculated for the pandemic a basic reproduction number of 1.53 and effective reproduction number of 1.29 to July 25, 2020. Conclusion: As the current number of beds in the intensive care unit would be insufficient to meet this demand, we suggest an increase in the number of critical beds in order to avoid the collapse of the health system in Porto Alegre.Objetivo: Estimar o número máximo de casos prevalentes de COVID-19, internados em unidades de terapia intensiva, e o momento deste pico, em Porto Alegre. Métodos: Empregamos um modelo matemático de equações diferenciais denominado SEIHDR (Suscetível, Exposto, Infectado, Hospitalizado, Morto, Recuperados). Analisamos os casos de hospitalização por COVID-19 em Porto Alegre e RS, desde 9 de março até 25 de julho de 2020 a fim de extrair os parâmetros para construir uma curva epidemiológica do total de casos prevalentes hospitalizados e em unidade de terapia intensiva, assim como estimar a prevalência de pacientes em ventilação mecânica invasiva. Finalmente, ajustamos alguns parâmetros desta curva a partir dos casos reais prevalentes de internados em enfermaria e em unidades de terapia intensiva. Resultados: O modelo matemático corrigido para os dados da pandemia até 25 de julho projetou um pico de 1.354 casos prevalentes hospitalizados: 562 pacientes internados na unidade de terapia intensiva com 378 sob ventilação mecânica no dia 12 de setembro de 2020 (37º semana epidemiológica). Ainda, haveria o pico de 62.514 casos prevalentes de infectados com COVID-19 no início do mesmo mês (36º semana epidemiológica. Calculamos para a pandemia um número de reprodução básico de 1,53 e de reprodução efetiva de 1,29 para 25 de julho de 2020. Conclusão: Como o número atual de leitos de unidade de terapia intensiva seria insuficiente para atender a esta demanda, sugerimos um aumento no número de leitos críticos a fim de evitar o colapso do sistema de saúde em Porto Alegre.SciELO PreprintsSciELO PreprintsSciELO Preprints2020-08-10info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/108010.1590/SciELOPreprints.1080porhttps://preprints.scielo.org/index.php/scielo/article/view/1080/1586Copyright (c) 2020 Mauricio Guidi Saueressig, Cristiano Lima Hackmann, Carlos Eduardo Schonerwald da Silva, Jair Ferreirahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSaueressig, Mauricio GuidiHackmann, Cristiano LimaSilva, Carlos Eduardo Schonerwald daFerreira, Jairreponame:SciELO Preprintsinstname:SciELOinstacron:SCI2020-08-08T21:48:02Zoai:ops.preprints.scielo.org:preprint/1080Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2020-08-08T21:48:02SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR Estimativa de pacientes hospitalizados por COVID-19 em unidade de terapia intensiva no pico da pandemia em Porto Alegre: Estudo com modelo epidemiológico SEIHDR |
title |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
spellingShingle |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR Saueressig, Mauricio Guidi Infecções por Coronavívus Unidades de Terapia Intensiva Hospitalização Cuidados Críticos Coronavirus infection Hospitalization Critical Care Intensive Care Units |
title_short |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
title_full |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
title_fullStr |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
title_full_unstemmed |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
title_sort |
Estimation of patients hospitalized for COVID-19 in an intensive care unit at the peak of the pandemic in Porto Alegre: Study with epidemiological model SEIHDR |
author |
Saueressig, Mauricio Guidi |
author_facet |
Saueressig, Mauricio Guidi Hackmann, Cristiano Lima Silva, Carlos Eduardo Schonerwald da Ferreira, Jair |
author_role |
author |
author2 |
Hackmann, Cristiano Lima Silva, Carlos Eduardo Schonerwald da Ferreira, Jair |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Saueressig, Mauricio Guidi Hackmann, Cristiano Lima Silva, Carlos Eduardo Schonerwald da Ferreira, Jair |
dc.subject.por.fl_str_mv |
Infecções por Coronavívus Unidades de Terapia Intensiva Hospitalização Cuidados Críticos Coronavirus infection Hospitalization Critical Care Intensive Care Units |
topic |
Infecções por Coronavívus Unidades de Terapia Intensiva Hospitalização Cuidados Críticos Coronavirus infection Hospitalization Critical Care Intensive Care Units |
description |
Objective: Estimate the maximum number of prevalent cases of COVID-19, admitted to intensive care units, and the time of this peak, in Porto Alegre. Methods: A mathematical model of differential equations called SEIHDR (Susceptible, Exposed, Infected, Hospitalized, Dead, Recovered) have been used to analyze the cases of hospitalization for COVID-19 in Porto Alegre and RS, from March 9 to July 25, 2020 in order to extract the parameters to make up an epidemiological curve of the prevalent cases hospitalized in general ward and in intensive care units, as well as how to estimate the prevalence of patients on invasive mechanical ventilation. Finally, we adjusted some parameters of this curve based on the current prevalent cases hospitalized. Results: The mathematical model corrected for the pandemic data until July 25 projected a peak of 1,354 prevalent hospitalized cases: 562 patients admitted to the intensive care unit with 378 under mechanical ventilation on September 12, 2020 (37th epidemiological week). In addition, there would be a peak of 62,514 prevalent cases of infected with COVID-19 at the beginning of the same month (36th epidemiological week. We calculated for the pandemic a basic reproduction number of 1.53 and effective reproduction number of 1.29 to July 25, 2020. Conclusion: As the current number of beds in the intensive care unit would be insufficient to meet this demand, we suggest an increase in the number of critical beds in order to avoid the collapse of the health system in Porto Alegre. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/1080 10.1590/SciELOPreprints.1080 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/1080 |
identifier_str_mv |
10.1590/SciELOPreprints.1080 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/1080/1586 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://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 |
SciELO Preprints SciELO Preprints SciELO Preprints |
publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
dc.source.none.fl_str_mv |
reponame:SciELO Preprints instname:SciELO instacron:SCI |
instname_str |
SciELO |
instacron_str |
SCI |
institution |
SCI |
reponame_str |
SciELO Preprints |
collection |
SciELO Preprints |
repository.name.fl_str_mv |
SciELO Preprints - SciELO |
repository.mail.fl_str_mv |
scielo.submission@scielo.org |
_version_ |
1797047819893211136 |