Measuring misclassification of Covid-19 as garbage codes: Results of investigating 1,365 deaths and implications for vital statistics in Brazil

PLOS Glob Public Health. 2022 May 5;2(5):e0000199. doi: 10.1371/journal.pgph.0000199. eCollection 2022.

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.

Grants and funding

EBF, LHI, DMXA, RAT, PRLC and TVB were supported by Vital Strategies- GGP-CRVS Brazil Data for Health (23998 n. Fundep). ESJ and MADM were supported financially by Resolve to Save Lives – an initiative of Vital Strategies (RE-NC-CCRV-35-BR). ALB, PS and FM received no specific funding for this work. No author received payment or services from any third party for any aspect of this work. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Funding: Vital Strategies- GGP-CRVS Brazil Data for Health/23998 n. Fundep. This article is, in part, an output of the Bloomberg Philanthropies Data for Health Initiative (www.Bloomberg.org). The views expressed are not necessarily those of the Philanthropies.