Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Archives of Biology and Technology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132023000100304 |
Resumo: | Abstract This paper proposes to analyze how the intervention measures such as lockdown, partial lockdown and no-lockdown help to impede the spread of the severe outbreak of COVID-19 in Brazil. A p-fuzzy model, considering as input variables, the infected population and the intervention measures and as output variable the level of infestation, is proposed. The numerical results show that intervention measures play a crucial role in determining the success of COVID-19 eradication programs, while the population is being vaccinated in stages. Therefore, the model proposed assists government decision making in order to minimize the spread of the pandemic. |
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Brazilian Archives of Biology and Technology |
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Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention MeasuresCOVID-19Fuzzy modelpopulation dynamicsmeasure interventions.Abstract This paper proposes to analyze how the intervention measures such as lockdown, partial lockdown and no-lockdown help to impede the spread of the severe outbreak of COVID-19 in Brazil. A p-fuzzy model, considering as input variables, the infected population and the intervention measures and as output variable the level of infestation, is proposed. The numerical results show that intervention measures play a crucial role in determining the success of COVID-19 eradication programs, while the population is being vaccinated in stages. Therefore, the model proposed assists government decision making in order to minimize the spread of the pandemic.Instituto de Tecnologia do Paraná - Tecpar2023-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132023000100304Brazilian Archives of Biology and Technology v.66 2023reponame:Brazilian Archives of Biology and Technologyinstname:Instituto de Tecnologia do Paraná (Tecpar)instacron:TECPAR10.1590/1678-4324-2023220425info:eu-repo/semantics/openAccessBressan,Glaucia MariaStiegelmeier,Elenice Webereng2022-10-27T00:00:00Zoai:scielo:S1516-89132023000100304Revistahttps://www.scielo.br/j/babt/https://old.scielo.br/oai/scielo-oai.phpbabt@tecpar.br||babt@tecpar.br1678-43241516-8913opendoar:2022-10-27T00:00Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar)false |
dc.title.none.fl_str_mv |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
title |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
spellingShingle |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures Bressan,Glaucia Maria COVID-19 Fuzzy model population dynamics measure interventions. |
title_short |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
title_full |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
title_fullStr |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
title_full_unstemmed |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
title_sort |
Fuzzy Modelling on the Evolution of COVID-19 Epidemic under the Effects of Intervention Measures |
author |
Bressan,Glaucia Maria |
author_facet |
Bressan,Glaucia Maria Stiegelmeier,Elenice Weber |
author_role |
author |
author2 |
Stiegelmeier,Elenice Weber |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Bressan,Glaucia Maria Stiegelmeier,Elenice Weber |
dc.subject.por.fl_str_mv |
COVID-19 Fuzzy model population dynamics measure interventions. |
topic |
COVID-19 Fuzzy model population dynamics measure interventions. |
description |
Abstract This paper proposes to analyze how the intervention measures such as lockdown, partial lockdown and no-lockdown help to impede the spread of the severe outbreak of COVID-19 in Brazil. A p-fuzzy model, considering as input variables, the infected population and the intervention measures and as output variable the level of infestation, is proposed. The numerical results show that intervention measures play a crucial role in determining the success of COVID-19 eradication programs, while the population is being vaccinated in stages. Therefore, the model proposed assists government decision making in order to minimize the spread of the pandemic. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132023000100304 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132023000100304 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-4324-2023220425 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Instituto de Tecnologia do Paraná - Tecpar |
publisher.none.fl_str_mv |
Instituto de Tecnologia do Paraná - Tecpar |
dc.source.none.fl_str_mv |
Brazilian Archives of Biology and Technology v.66 2023 reponame:Brazilian Archives of Biology and Technology instname:Instituto de Tecnologia do Paraná (Tecpar) instacron:TECPAR |
instname_str |
Instituto de Tecnologia do Paraná (Tecpar) |
instacron_str |
TECPAR |
institution |
TECPAR |
reponame_str |
Brazilian Archives of Biology and Technology |
collection |
Brazilian Archives of Biology and Technology |
repository.name.fl_str_mv |
Brazilian Archives of Biology and Technology - Instituto de Tecnologia do Paraná (Tecpar) |
repository.mail.fl_str_mv |
babt@tecpar.br||babt@tecpar.br |
_version_ |
1750318281728720896 |