Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista da Sociedade Brasileira de Medicina Tropical |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822020000100368 |
Resumo: | Abstract INTRODUCTION: This work aims to develop a biomathematical transmission model of COVID-19, in the State of Sergipe, Brazil, to estimate the distribution of cases over time and project the impact on the spread of the epidemic outbreak due to interventions and control measures over the local population. METHODS: This is an epidemiological mathematical modeling study conducted to analyze the dynamics of the accumulated cases of COVID-19, which used a logistic growth model that adds a term of withdrawal of individuals as a control measure. Three possible COVID-19 propagation scenarios were simulated based on three different rates of withdrawal of individuals. They were adjusted with real data of the infected and measures of control over the population. RESULTS: The lockdown would be the best scenario, with a lower incidence of infected people, when compared to the other measures. The number of infected people would grow slowly over the months, and the number of symptomatic individuals in this scenario would be 40,265 cases. We noticed that the State of Sergipe is still in the initial stage of the disease in the scenarios. It was possible to observe that the peak of cases and the equilibrium, in the current situation of social isolation, will occur when reaching the new support capacity, at the end of August in approximately 1,171,353 infected individuals. CONCLUSIONS: We established that lockdown is the intervention with the highest ability to mitigate the spread of the virus among the population. |
id |
SBMT-1_b8132d59b6a622f9d220e5b0809222c3 |
---|---|
oai_identifier_str |
oai:scielo:S0037-86822020000100368 |
network_acronym_str |
SBMT-1 |
network_name_str |
Revista da Sociedade Brasileira de Medicina Tropical |
repository_id_str |
|
spelling |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling studyCOVID-19Coronavirus infectionSocial isolationEpidemiologyAbstract INTRODUCTION: This work aims to develop a biomathematical transmission model of COVID-19, in the State of Sergipe, Brazil, to estimate the distribution of cases over time and project the impact on the spread of the epidemic outbreak due to interventions and control measures over the local population. METHODS: This is an epidemiological mathematical modeling study conducted to analyze the dynamics of the accumulated cases of COVID-19, which used a logistic growth model that adds a term of withdrawal of individuals as a control measure. Three possible COVID-19 propagation scenarios were simulated based on three different rates of withdrawal of individuals. They were adjusted with real data of the infected and measures of control over the population. RESULTS: The lockdown would be the best scenario, with a lower incidence of infected people, when compared to the other measures. The number of infected people would grow slowly over the months, and the number of symptomatic individuals in this scenario would be 40,265 cases. We noticed that the State of Sergipe is still in the initial stage of the disease in the scenarios. It was possible to observe that the peak of cases and the equilibrium, in the current situation of social isolation, will occur when reaching the new support capacity, at the end of August in approximately 1,171,353 infected individuals. CONCLUSIONS: We established that lockdown is the intervention with the highest ability to mitigate the spread of the virus among the population.Sociedade Brasileira de Medicina Tropical - SBMT2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822020000100368Revista da Sociedade Brasileira de Medicina Tropical v.53 2020reponame:Revista da Sociedade Brasileira de Medicina Tropicalinstname:Sociedade Brasileira de Medicina Tropical (SBMT)instacron:SBMT10.1590/0037-8682-0417-2020info:eu-repo/semantics/openAccessGóis,Aédson NascimentoLaureano,Estevão EsmiSantos,David da SilvaSánchez,Daniel EduardoSouza,Luiz FernandoVieira,Rita de Cássia AlmeidaOliveira,Jussiely CunhaSantana-Santos,Eduesleyeng2020-10-19T00:00:00Zoai:scielo:S0037-86822020000100368Revistahttps://www.sbmt.org.br/portal/revista/ONGhttps://old.scielo.br/oai/scielo-oai.php||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br1678-98490037-8682opendoar:2020-10-19T00:00Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT)false |
dc.title.none.fl_str_mv |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
title |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
spellingShingle |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study Góis,Aédson Nascimento COVID-19 Coronavirus infection Social isolation Epidemiology |
title_short |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
title_full |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
title_fullStr |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
title_full_unstemmed |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
title_sort |
Lockdown as an Intervention Measure to Mitigate the Spread of COVID-19: a modeling study |
author |
Góis,Aédson Nascimento |
author_facet |
Góis,Aédson Nascimento Laureano,Estevão Esmi Santos,David da Silva Sánchez,Daniel Eduardo Souza,Luiz Fernando Vieira,Rita de Cássia Almeida Oliveira,Jussiely Cunha Santana-Santos,Eduesley |
author_role |
author |
author2 |
Laureano,Estevão Esmi Santos,David da Silva Sánchez,Daniel Eduardo Souza,Luiz Fernando Vieira,Rita de Cássia Almeida Oliveira,Jussiely Cunha Santana-Santos,Eduesley |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Góis,Aédson Nascimento Laureano,Estevão Esmi Santos,David da Silva Sánchez,Daniel Eduardo Souza,Luiz Fernando Vieira,Rita de Cássia Almeida Oliveira,Jussiely Cunha Santana-Santos,Eduesley |
dc.subject.por.fl_str_mv |
COVID-19 Coronavirus infection Social isolation Epidemiology |
topic |
COVID-19 Coronavirus infection Social isolation Epidemiology |
description |
Abstract INTRODUCTION: This work aims to develop a biomathematical transmission model of COVID-19, in the State of Sergipe, Brazil, to estimate the distribution of cases over time and project the impact on the spread of the epidemic outbreak due to interventions and control measures over the local population. METHODS: This is an epidemiological mathematical modeling study conducted to analyze the dynamics of the accumulated cases of COVID-19, which used a logistic growth model that adds a term of withdrawal of individuals as a control measure. Three possible COVID-19 propagation scenarios were simulated based on three different rates of withdrawal of individuals. They were adjusted with real data of the infected and measures of control over the population. RESULTS: The lockdown would be the best scenario, with a lower incidence of infected people, when compared to the other measures. The number of infected people would grow slowly over the months, and the number of symptomatic individuals in this scenario would be 40,265 cases. We noticed that the State of Sergipe is still in the initial stage of the disease in the scenarios. It was possible to observe that the peak of cases and the equilibrium, in the current situation of social isolation, will occur when reaching the new support capacity, at the end of August in approximately 1,171,353 infected individuals. CONCLUSIONS: We established that lockdown is the intervention with the highest ability to mitigate the spread of the virus among the population. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
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=S0037-86822020000100368 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822020000100368 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0037-8682-0417-2020 |
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 |
Sociedade Brasileira de Medicina Tropical - SBMT |
publisher.none.fl_str_mv |
Sociedade Brasileira de Medicina Tropical - SBMT |
dc.source.none.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical v.53 2020 reponame:Revista da Sociedade Brasileira de Medicina Tropical instname:Sociedade Brasileira de Medicina Tropical (SBMT) instacron:SBMT |
instname_str |
Sociedade Brasileira de Medicina Tropical (SBMT) |
instacron_str |
SBMT |
institution |
SBMT |
reponame_str |
Revista da Sociedade Brasileira de Medicina Tropical |
collection |
Revista da Sociedade Brasileira de Medicina Tropical |
repository.name.fl_str_mv |
Revista da Sociedade Brasileira de Medicina Tropical - Sociedade Brasileira de Medicina Tropical (SBMT) |
repository.mail.fl_str_mv |
||dalmo@rsbmt.uftm.edu.br|| rsbmt@rsbmt.uftm.edu.br |
_version_ |
1752122162418810880 |