Skip navigation
Please use this identifier to cite or link to this item: http://repositorio.unb.br/handle/10482/39652
Files in This Item:
File Description SizeFormat 
ARTIGO_ImputationMethodReduce.pdf945,54 kBAdobe PDFView/Open
Title: Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil
Authors: Oliveira, Silvano Barbosa de
Ganem, Fabiana
Araújo, Wildo Navegantes de
Casabona, Jordi
Sanchez, Mauro Niskier
Croda, Julio
metadata.dc.identifier.orcid: http://orcid.org/0000-0002-6665-6825
Assunto:: Covid-19
Infecções respiratórias
Teste de laboratório
Issue Date: 2020
Publisher: Sociedade Brasileira de Medicina Tropical - SBMT
Citation: OLIVEIRA, Silvano Barbosa de et al. Imputation method to reduce undetected severe acute respiratory infection cases during the coronavirus disease outbreak in Brazil. Revista da Sociedade Brasileira de Medicina Tropical, Uberaba, v. 53, e20200528, 2020. DOI: https://doi.org/10.1590/0037-8682-0528-2020. Disponível em: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822020000100659&lng=en&nrm=iso. Acesso em: 23 nov. 2020. Epub 14-Set-2020.
Abstract: INTRODUCTION: The coronavirus disease (COVD-19) outbreak has overburdened the surveillance of severe acute respiratory infections (SARIs), including the laboratory network. This study was aimed at correcting the absence of laboratory results of reported SARI deaths. METHODS: The imputation method was applied for SARI deaths without laboratory information using clinico-epidemiological characteristics. RESULTS: Of 84,449 SARI deaths, 51% were confirmed with COVID-19 while 3% with other viral respiratory diseases. After the imputation method, 95% of deaths were reclassified as COVID-19 while 5% as other viral respiratory diseases. CONCLUSIONS: The imputation method was a useful and robust solution (sensitivity and positive predictive value of 98%) for missing values through clinical & epidemiological characteristics.
metadata.dc.description.unidade: Faculdade de Ciências da Saúde (FS)
Departamento de Saúde Coletiva (FS DSC)
DOI: https://doi.org/10.1590/0037-8682-0528-2020
Appears in Collections:Artigos publicados em periódicos e afins
UnB - Covid-19

Show full item record " class="statisticsLink btn btn-primary" href="/jspui/handle/10482/39652/statistics">



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.