Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020

Detalhes bibliográficos
Autor(a) principal: Ribas, Fábio Vieira
Data de Publicação: 2022
Outros Autores: Custódio, Ana Cristina Dias, Toledo, Luana Vieira, Henriques, Bruno David, Sediyama, Catarina Maria Nogueira de Oliveira, Freitas, Brunnella Alcântara Chagas de
Tipo de documento: preprint
Idioma: por
Título da fonte: SciELO Preprints
Texto Completo: https://preprints.scielo.org/index.php/scielo/preprint/view/3887
Resumo: Objective: To analyze the completeness of notifications of cases of severe acute respiratory illness from the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) during the COVID-19 pandemic, in the national database and in a regional database in the state of Minas Gerais, Brazil, in 2020. Methods: Descriptive study of the completeness of sociodemographic variables and those related to the etiology, clinical condition, evolution and diagnostic criteria of SIVEP-Influenza. Completeness was classified as excellent (greater than 95%), good (90 to 95%), fair (80 to 90%), poor (50 to 80%), and very poor (less than 50%). Results: The percentage of variables with excellent completeness was only 18.1% in the national database and 27.8% in the regional database. Conclusion: Low completeness of both SIVEP-Gripe databases was evidenced, making it necessary to improve the work process and routine training of professionals for the correct completion.
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spelling Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020Completitud de notificaciones de síndrome respiratorio agudo severo a nivel nacional y de salud regional en Minas Gerais, Brasil, durante la pandemia COVID-19, 2020Completude das notificações de síndrome respiratória aguda grave no âmbito nacional e em uma regional de saúde de Minas Gerais, durante a pandemia de COVID-19, 2020Síndrome Respiratória Aguda GraveCOVID-19Sistemas de Informação em SaúdeVigilância em Saúde PúblicaSevere Acute Respiratory SyndromeCOVID-19Health Information SystemsPublic Health SurveillanceSíndrome Respiratorio Agudo SeveroCOVID-19Sistemas de InformaciónVigilancia de la Salud PúblicaObjective: To analyze the completeness of notifications of cases of severe acute respiratory illness from the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) during the COVID-19 pandemic, in the national database and in a regional database in the state of Minas Gerais, Brazil, in 2020. Methods: Descriptive study of the completeness of sociodemographic variables and those related to the etiology, clinical condition, evolution and diagnostic criteria of SIVEP-Influenza. Completeness was classified as excellent (greater than 95%), good (90 to 95%), fair (80 to 90%), poor (50 to 80%), and very poor (less than 50%). Results: The percentage of variables with excellent completeness was only 18.1% in the national database and 27.8% in the regional database. Conclusion: Low completeness of both SIVEP-Gripe databases was evidenced, making it necessary to improve the work process and routine training of professionals for the correct completion.Objetivo: Analizar la completitud de las notificaciones de casos de síndrome respiratorio agudo severo del Sistema de Información de Vigilancia Epidemiológica de Influenza (SIVEP-Gripe) durante la pandemia de COVID-19, en la base de datos nacional y en una base de datos regional de salud en el estado de Minas Gerais, Brasil, en 2020. Métodos: Estudio descriptivo de la completitud de las variables sociodemográficas y las relacionadas con la etiología, cuadro clínico, evolución y criterios diagnósticos del SIVEP-Influenza. La exhaustividad se clasificó como excelente (más grande que 95%), buena (90 a 95%), regular (80 a 90%), mala (50 a 80%) y muy mala (menos que 50%). Resultados: El porcentaje de variables con excelente completitud fue solo del 18,1% en la base de datos nacional y del 27,8% en la base de datos regional. Conclusión: Se evidenció la baja completitud de ambas bases de datos SIVEP-Gripe, siendo necesario mejorar el proceso de trabajo y la rutina de capacitación de los profesionales para el correcto llenado.Objetivo: Analisar a completude das notificações de casos de síndrome respiratória aguda grave no Sistema de Informação de Vigilência Epidemiológica da Gripo (SIVEP Gripe) durante a pandemia de COVID-19, na base de dados nacional e na base da Unidade Regional de Saúde do estado de Minas Gerais, Brasil, em 2020. Métodos: Estudo descritivo da completude das variáveis sociodemográficas e das relativas à etiologia, condição clínica, evolução e critérios diagnósticos do SIVEP-Gripe. O nível de completude foi classificado como excelente (>95%), bom (90 a 95%), regular (80 a 90%), ruim (50 a 80%) ou muito ruim (<50%). Resultados: O percentual de variáveis com completudo excelente foi de apenas 18,1% na base de dados nacional, e de 27,8% na base de dados regional. Conclusão: Evidenciou-se baixa completude de ambas bases dados do SIVEP-Gripe, tornando-se necessários aperfeiçoamentos no processo de trabalho e capacitações rotineiras dos profissionais para o correto preenchimento.SciELO PreprintsSciELO PreprintsSciELO Preprints2022-04-04info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/388710.1590/S1679-49742022000200004porhttps://preprints.scielo.org/index.php/scielo/article/view/3887/7254Copyright (c) 2022 Fábio Vieira Ribas, Ana Cristina Dias Custódio, Luana Vieira Toledo, Bruno David Henriques, Catarina Maria Nogueira de Oliveira Sediyama, Brunnella Alcântara Chagas de Freitashttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessRibas, Fábio VieiraCustódio, Ana Cristina DiasToledo, Luana VieiraHenriques, Bruno DavidSediyama, Catarina Maria Nogueira de OliveiraFreitas, Brunnella Alcântara Chagas dereponame:SciELO Preprintsinstname:SciELOinstacron:SCI2022-04-04T11:54:30Zoai:ops.preprints.scielo.org:preprint/3887Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2022-04-04T11:54:30SciELO Preprints - SciELOfalse
dc.title.none.fl_str_mv Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
Completitud de notificaciones de síndrome respiratorio agudo severo a nivel nacional y de salud regional en Minas Gerais, Brasil, durante la pandemia COVID-19, 2020
Completude das notificações de síndrome respiratória aguda grave no âmbito nacional e em uma regional de saúde de Minas Gerais, durante a pandemia de COVID-19, 2020
title Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
spellingShingle Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
Ribas, Fábio Vieira
Síndrome Respiratória Aguda Grave
COVID-19
Sistemas de Informação em Saúde
Vigilância em Saúde Pública
Severe Acute Respiratory Syndrome
COVID-19
Health Information Systems
Public Health Surveillance
Síndrome Respiratorio Agudo Severo
COVID-19
Sistemas de Información
Vigilancia de la Salud Pública
title_short Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
title_full Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
title_fullStr Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
title_full_unstemmed Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
title_sort Completeness of notifications of severe acute respiratory syndrome nationally and of a regional health in Minas Gerais, Brazil, during the COVID-19 pandemic, 2020
author Ribas, Fábio Vieira
author_facet Ribas, Fábio Vieira
Custódio, Ana Cristina Dias
Toledo, Luana Vieira
Henriques, Bruno David
Sediyama, Catarina Maria Nogueira de Oliveira
Freitas, Brunnella Alcântara Chagas de
author_role author
author2 Custódio, Ana Cristina Dias
Toledo, Luana Vieira
Henriques, Bruno David
Sediyama, Catarina Maria Nogueira de Oliveira
Freitas, Brunnella Alcântara Chagas de
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Ribas, Fábio Vieira
Custódio, Ana Cristina Dias
Toledo, Luana Vieira
Henriques, Bruno David
Sediyama, Catarina Maria Nogueira de Oliveira
Freitas, Brunnella Alcântara Chagas de
dc.subject.por.fl_str_mv Síndrome Respiratória Aguda Grave
COVID-19
Sistemas de Informação em Saúde
Vigilância em Saúde Pública
Severe Acute Respiratory Syndrome
COVID-19
Health Information Systems
Public Health Surveillance
Síndrome Respiratorio Agudo Severo
COVID-19
Sistemas de Información
Vigilancia de la Salud Pública
topic Síndrome Respiratória Aguda Grave
COVID-19
Sistemas de Informação em Saúde
Vigilância em Saúde Pública
Severe Acute Respiratory Syndrome
COVID-19
Health Information Systems
Public Health Surveillance
Síndrome Respiratorio Agudo Severo
COVID-19
Sistemas de Información
Vigilancia de la Salud Pública
description Objective: To analyze the completeness of notifications of cases of severe acute respiratory illness from the Influenza Epidemiological Surveillance Information System (SIVEP-Gripe) during the COVID-19 pandemic, in the national database and in a regional database in the state of Minas Gerais, Brazil, in 2020. Methods: Descriptive study of the completeness of sociodemographic variables and those related to the etiology, clinical condition, evolution and diagnostic criteria of SIVEP-Influenza. Completeness was classified as excellent (greater than 95%), good (90 to 95%), fair (80 to 90%), poor (50 to 80%), and very poor (less than 50%). Results: The percentage of variables with excellent completeness was only 18.1% in the national database and 27.8% in the regional database. Conclusion: Low completeness of both SIVEP-Gripe databases was evidenced, making it necessary to improve the work process and routine training of professionals for the correct completion.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-04
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10.1590/S1679-49742022000200004
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identifier_str_mv 10.1590/S1679-49742022000200004
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