What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil

Detalhes bibliográficos
Autor(a) principal: Santos, Cleber
Data de Publicação: 2022
Outros Autores: Ferreira, Vanessa Melo, Cavalcante, João Roberto, Ribeiro, Patricia Canto, Castro, Hermano Albuquerque de, Gutierrez, Adriana Coser, Pereira, Ingrid D’avilla Freire, Nehab, Marcio Fernandes, Moura, Maria Martha Duque de, Perissé, André Reynaldo Santos
Tipo de documento: preprint
Idioma: por
Título da fonte: SciELO Preprints
Texto Completo: https://preprints.scielo.org/index.php/scielo/preprint/view/3560
Resumo: Objective: To describe the completeness of the profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil between 2020 and 2021 Methods:  the absolute and relative frequencies of the completeness of the variable occupation were calculated for each state for the between 2020 and 2021. Results: For the study period, there was 94.83% incompleteness for notifications of Flu-like syndrome, 97.73% for notified cases of SARS and 17.06% for deaths from all causes. Conclusions: We recommend an articulation between the Ministry of Health, Ministry of Labor and Welfare and workers' representations, such as councils and unions, to solve the problem of lack of data on occupation/profession in public databases.
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spelling What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil¿Qué podemos aprender con los datos que no tenemos? El caso de la variable profesión /ocupación sobre base de datos de la síndrome gripal, síndrome respiratorio agudo severo y de mortalidad en BrasilO que aprendemos diante dos dados que não temos? O caso da variável profissão/ocupação nos bancos de síndrome gripal, síndrome respiratória aguda grave e mortalidade no BrasilDados faltantesVigilânciaSaúde do trabalhadorPandemiaMissing dataSurveillancePandemicWorker’s healthObjective: To describe the completeness of the profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil between 2020 and 2021 Methods:  the absolute and relative frequencies of the completeness of the variable occupation were calculated for each state for the between 2020 and 2021. Results: For the study period, there was 94.83% incompleteness for notifications of Flu-like syndrome, 97.73% for notified cases of SARS and 17.06% for deaths from all causes. Conclusions: We recommend an articulation between the Ministry of Health, Ministry of Labor and Welfare and workers' representations, such as councils and unions, to solve the problem of lack of data on occupation/profession in public databases.Objetivo: descrever o preenchimento da variável profissão/ocupação nos bancos de dados do Sistema de Informação de Mortalidade (SIM), de Síndrome Respiratória Aguda Grave (SRAG) e Síndrome Gripal (SG) entre 2020 e 2021 no Brasil. Métodos: foram calculadas as frequências absolutas e relativas do preenchimento da variável profissão/ocupação por Unidade da Federação para cada base de dados durante o período de estudo. Resultados: Para o período de estudo, verificou-se 94,83% de incompletude para as notificações de SG, 97,73% para casos notificados de SRAG e 17,06% para óbitos por todas as causas. Conclusões: Recomendamos uma articulação entre o Ministério da Saúde, Ministério do Trabalho e Previdência e representações de trabalhadores, como conselhos e sindicatos para formulação de estratégias para contornar o problema da falta de dados de ocupação/profissão nos bancos de dados públicos.SciELO PreprintsSciELO PreprintsSciELO Preprints2022-02-09info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/356010.1590/SciELOPreprints.3560porhttps://preprints.scielo.org/index.php/scielo/article/view/3560/6562Copyright (c) 2022 Cleber Santos, Vanessa Melo Ferreira, João Roberto Cavalcante, Patricia Canto Ribeiro, Hermano Albuquerque de Castro, Adriana Coser Gutierrez, Ingrid D’avilla Freire Pereira, Marcio Fernandes Nehab, Maria Martha Duque de Moura, André Reynaldo Santos Perisséhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSantos, CleberFerreira, Vanessa MeloCavalcante, João RobertoRibeiro, Patricia CantoCastro, Hermano Albuquerque deGutierrez, Adriana CoserPereira, Ingrid D’avilla FreireNehab, Marcio FernandesMoura, Maria Martha Duque dePerissé, André Reynaldo Santosreponame:SciELO Preprintsinstname:SciELOinstacron:SCI2022-02-03T18:52:58Zoai:ops.preprints.scielo.org:preprint/3560Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2022-02-03T18:52:58SciELO Preprints - SciELOfalse
dc.title.none.fl_str_mv What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
¿Qué podemos aprender con los datos que no tenemos? El caso de la variable profesión /ocupación sobre base de datos de la síndrome gripal, síndrome respiratorio agudo severo y de mortalidad en Brasil
O que aprendemos diante dos dados que não temos? O caso da variável profissão/ocupação nos bancos de síndrome gripal, síndrome respiratória aguda grave e mortalidade no Brasil
title What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
spellingShingle What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
Santos, Cleber
Dados faltantes
Vigilância
Saúde do trabalhador
Pandemia
Missing data
Surveillance
Pandemic
Worker’s health
title_short What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
title_full What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
title_fullStr What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
title_full_unstemmed What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
title_sort What can we learn with the data we didn’t have? The case of the variable profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil
author Santos, Cleber
author_facet Santos, Cleber
Ferreira, Vanessa Melo
Cavalcante, João Roberto
Ribeiro, Patricia Canto
Castro, Hermano Albuquerque de
Gutierrez, Adriana Coser
Pereira, Ingrid D’avilla Freire
Nehab, Marcio Fernandes
Moura, Maria Martha Duque de
Perissé, André Reynaldo Santos
author_role author
author2 Ferreira, Vanessa Melo
Cavalcante, João Roberto
Ribeiro, Patricia Canto
Castro, Hermano Albuquerque de
Gutierrez, Adriana Coser
Pereira, Ingrid D’avilla Freire
Nehab, Marcio Fernandes
Moura, Maria Martha Duque de
Perissé, André Reynaldo Santos
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Santos, Cleber
Ferreira, Vanessa Melo
Cavalcante, João Roberto
Ribeiro, Patricia Canto
Castro, Hermano Albuquerque de
Gutierrez, Adriana Coser
Pereira, Ingrid D’avilla Freire
Nehab, Marcio Fernandes
Moura, Maria Martha Duque de
Perissé, André Reynaldo Santos
dc.subject.por.fl_str_mv Dados faltantes
Vigilância
Saúde do trabalhador
Pandemia
Missing data
Surveillance
Pandemic
Worker’s health
topic Dados faltantes
Vigilância
Saúde do trabalhador
Pandemia
Missing data
Surveillance
Pandemic
Worker’s health
description Objective: To describe the completeness of the profession/ occupation on flu-like syndrome, severe acute respiratory syndrome and mortality databases in Brazil between 2020 and 2021 Methods:  the absolute and relative frequencies of the completeness of the variable occupation were calculated for each state for the between 2020 and 2021. Results: For the study period, there was 94.83% incompleteness for notifications of Flu-like syndrome, 97.73% for notified cases of SARS and 17.06% for deaths from all causes. Conclusions: We recommend an articulation between the Ministry of Health, Ministry of Labor and Welfare and workers' representations, such as councils and unions, to solve the problem of lack of data on occupation/profession in public databases.
publishDate 2022
dc.date.none.fl_str_mv 2022-02-09
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/3560
10.1590/SciELOPreprints.3560
url https://preprints.scielo.org/index.php/scielo/preprint/view/3560
identifier_str_mv 10.1590/SciELOPreprints.3560
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://preprints.scielo.org/index.php/scielo/article/view/3560/6562
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
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