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Measuring misclassification of Covid-19 as garbage codes: Results of investigating 1,365 deaths and implications for vital statistics in Brazil.
França, Elisabeth B; Ishitani, Lenice H; de Abreu, Daisy Maria Xavier; Teixeira, Renato Azeredo; Corrêa, Paulo Roberto Lopes; de Jesus, Eliene Dos Santos; Marinho, Maria Antonieta Delgado; Bahia, Tauá Vieira; Bierrenbach, Ana Luiza; Setel, Philip; Marinho, Fatima.
  • França EB; Graduate Program in Public Health, School of Medicine, Federal University of Minas Gerais - Belo Horizonte, Minas Gerais, Brazil.
  • Ishitani LH; Research Group on Epidemiology and Health Evaluation, Federal University of Minas Gerais - Belo Horizonte, Minas Gerais, Brazil.
  • de Abreu DMX; Research Group on Epidemiology and Health Evaluation, Federal University of Minas Gerais - Belo Horizonte, Minas Gerais, Brazil.
  • Teixeira RA; Research Group on Epidemiology and Health Evaluation, Federal University of Minas Gerais - Belo Horizonte, Minas Gerais, Brazil.
  • Corrêa PRL; Research Group on Epidemiology and Health Evaluation, Federal University of Minas Gerais - Belo Horizonte, Minas Gerais, Brazil.
  • de Jesus EDS; Municipal Health Department of Belo Horizonte, Belo Horizonte, Minas Gerais, Brazil.
  • Marinho MAD; Municipal Health Department of Salvador, Salvador, Bahia, Brazil.
  • Bahia TV; National Health Foundation, Ministry of Health, Natal, Rio Grande do Norte, Brazil.
  • Bierrenbach AL; Prefeitura Municipal de Salvador, Salvador, Bahia, Brazil.
  • Setel P; Vital Strategies, São Paulo, Brazil.
  • Marinho F; Vital Strategies, New York, New York, United States of America.
PLOS Glob Public Health ; 2(5): e0000199, 2022.
Article in English | MEDLINE | ID: covidwho-1854952
ABSTRACT
The purpose of this article is to quantify the amount of misclassification of the Coronavirus Disease-2019 (COVID-19) mortality occurring in hospitals and other health facilities in selected cities in Brazil, discuss potential factors contributing to this misclassification, and consider the implications for vital statistics. Hospital deaths assigned to causes classified as garbage code (GC) COVID-related cases (severe acute respiratory syndrome, pneumonia unspecified, sepsis, respiratory failure and ill-defined causes) were selected in three Brazilian state capitals. Data from medical charts and forensic reports were extracted from standard forms and analyzed by study physicians who re-assigned the underlying cause based on standardized criteria. Descriptive statistical analysis was performed and the potential impact in vital statistics in the country was also evaluated. Among 1,365 investigated deaths due to GC-COVID-related causes, COVID-19 was detected in 17.3% in the age group 0-59 years and 25.5% deaths in 60 years and over. These GCs rose substantially in 2020 in the country and were responsible for 211,611 registered deaths. Applying observed proportions by age, location and specific GC-COVID-related cause to national data, there would be an increase of 37,163 cases in the total of COVID-19 deaths, higher in the elderly. In conclusion, important undercount of deaths from COVID-19 among GC-COVID-related causes was detected in three selected capitals of Brazil. After extrapolating the study results for national GC-COVID-related deaths we infer that the burden of COVID-19 disease in Brazil in official vital statistics was probably under estimated by at least 18% in the country in 2020.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Country/Region as subject: South America / Brazil Language: English Journal: PLOS Glob Public Health Year: 2022 Document Type: Article Affiliation country: Journal.pgph.0000199

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies Country/Region as subject: South America / Brazil Language: English Journal: PLOS Glob Public Health Year: 2022 Document Type: Article Affiliation country: Journal.pgph.0000199