How limitations in data of health surveillance impact decision making in the Covid-19 pandemic

Detalhes bibliográficos
Autor(a) principal: Villela,Daniel Antunes Maciel
Data de Publicação: 2020
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Saude em Debate
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-11042020000800206
Resumo: ABSTRACT The Covid-19 pandemic signaled an alert to all countries about controlling transmission of SARS-CoV-2 to have fewer infected individuals, causing less stress to all health systems, and saving lives. As a result, multiple governments, including national and local levels of government, went through several degrees of social distancing measures. The decision process regarding the flexibilization of social distancing measures requires evidence of incidence decrease, available capacity in the health systems to absorb eventual epidemic waves, and serological prevalence studies designed to estimate the proportion of individuals with antibody protection. The trend criterium usually given by the effective reproduction number might be misguided if there are significant delays for reporting cases. For instance, the reproduction number for Niterói, in the state of Rio de Janeiro, went down from a value of approximately 3 to little more than 1. Even with all measures, the reproduction number did not get below R<1, which would demonstrate a more controlled scenario. Finally, a prediction method permits adjusting the notification delay and analyzing the current status of the epidemics.
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spelling How limitations in data of health surveillance impact decision making in the Covid-19 pandemicCoronavirus infections2019 novel coronavirus pandemicModels, theoreticalPublic health surveillanceABSTRACT The Covid-19 pandemic signaled an alert to all countries about controlling transmission of SARS-CoV-2 to have fewer infected individuals, causing less stress to all health systems, and saving lives. As a result, multiple governments, including national and local levels of government, went through several degrees of social distancing measures. The decision process regarding the flexibilization of social distancing measures requires evidence of incidence decrease, available capacity in the health systems to absorb eventual epidemic waves, and serological prevalence studies designed to estimate the proportion of individuals with antibody protection. The trend criterium usually given by the effective reproduction number might be misguided if there are significant delays for reporting cases. For instance, the reproduction number for Niterói, in the state of Rio de Janeiro, went down from a value of approximately 3 to little more than 1. Even with all measures, the reproduction number did not get below R<1, which would demonstrate a more controlled scenario. Finally, a prediction method permits adjusting the notification delay and analyzing the current status of the epidemics.Centro Brasileiro de Estudos de Saúde2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-11042020000800206Saúde em Debate v.44 n.spe4 2020reponame:Saude em Debateinstname:Centro Brasileiro de Estudos de Saudeinstacron:CBES10.1590/0103-11042020e413info:eu-repo/semantics/openAccessVillela,Daniel Antunes Macieleng2021-08-19T00:00:00Zoai:scielo:S0103-11042020000800206Revistahttp://www.scielo.br/scielo.php?script=sci_serial&pid=0103-1104&lng=en&nrm=isohttps://old.scielo.br/oai/scielo-oai.phprevista@saudeemdebate.org.br2358-28980103-1104opendoar:2021-08-19T00:00Saude em Debate - Centro Brasileiro de Estudos de Saudefalse
dc.title.none.fl_str_mv How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
title How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
spellingShingle How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
Villela,Daniel Antunes Maciel
Coronavirus infections
2019 novel coronavirus pandemic
Models, theoretical
Public health surveillance
title_short How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
title_full How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
title_fullStr How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
title_full_unstemmed How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
title_sort How limitations in data of health surveillance impact decision making in the Covid-19 pandemic
author Villela,Daniel Antunes Maciel
author_facet Villela,Daniel Antunes Maciel
author_role author
dc.contributor.author.fl_str_mv Villela,Daniel Antunes Maciel
dc.subject.por.fl_str_mv Coronavirus infections
2019 novel coronavirus pandemic
Models, theoretical
Public health surveillance
topic Coronavirus infections
2019 novel coronavirus pandemic
Models, theoretical
Public health surveillance
description ABSTRACT The Covid-19 pandemic signaled an alert to all countries about controlling transmission of SARS-CoV-2 to have fewer infected individuals, causing less stress to all health systems, and saving lives. As a result, multiple governments, including national and local levels of government, went through several degrees of social distancing measures. The decision process regarding the flexibilization of social distancing measures requires evidence of incidence decrease, available capacity in the health systems to absorb eventual epidemic waves, and serological prevalence studies designed to estimate the proportion of individuals with antibody protection. The trend criterium usually given by the effective reproduction number might be misguided if there are significant delays for reporting cases. For instance, the reproduction number for Niterói, in the state of Rio de Janeiro, went down from a value of approximately 3 to little more than 1. Even with all measures, the reproduction number did not get below R<1, which would demonstrate a more controlled scenario. Finally, a prediction method permits adjusting the notification delay and analyzing the current status of the epidemics.
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
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-11042020000800206
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0103-11042020e413
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Centro Brasileiro de Estudos de Saúde
publisher.none.fl_str_mv Centro Brasileiro de Estudos de Saúde
dc.source.none.fl_str_mv Saúde em Debate v.44 n.spe4 2020
reponame:Saude em Debate
instname:Centro Brasileiro de Estudos de Saude
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instname_str Centro Brasileiro de Estudos de Saude
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reponame_str Saude em Debate
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repository.name.fl_str_mv Saude em Debate - Centro Brasileiro de Estudos de Saude
repository.mail.fl_str_mv revista@saudeemdebate.org.br
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