View Complete Reference

Galvêas, D, Barros, F and Fuzo, CA (2021)

A forensic analysis of SARS-CoV-2 cases and COVID-19 mortality misreporting in the Brazilian population

Public Health.

ISSN/ISBN: Not available at this time. DOI: 10.1016/j.puhe.2021.05.010

Abstract: Objective The study aimed to investigate the misreporting number of positively tested individuals for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) succumbed or not to coronavirus disease 2019 (COVID-19) pandemic in Brazil at the city, state, and national scales using statistical forensic analysis. Study design This is a register-based study over public health data collected, organized, and maintained by the Ministry of Health covering the Brazilian population. Methods We evaluated the Brazilian notifications of positively tested cases for SARS-CoV-2 who have succumbed or not to COVID-19 between February 26th to September 7th of 2020 at the city, state, and national scales for conformity to expected distribution provided by Benford’s law (BL). Results Statistical analyzes demonstrated a significant rejection of SARS-CoV-2 notification cases at the city and the number of deaths by COVID-19 in all regional levels according to the hypothesis of conformity to BL. Conclusion We demonstrated by BL, which has been widely applied to query the quality and reliability of different numerical data sources, the misreporting number of cases and deaths throughout the SARS-CoV-2 pandemic in Brazil. Therefore, we brought to light pieces of evidence that raise questions about the reliability of SARS-CoV-2 data in Brazil. This situation may have led to inconsistencies in public health policy actions, recommendations, and drastic humanitarian, social, and economic consequences such as the intensive unit care overload in some Brazilian regions.

@article{, title = {A forensic analysis of SARS-CoV-2 cases and COVID-19 mortality misreporting in the Brazilian population}, journal = {Public Health}, year = {2021}, doi = { 10.1016/j.puhe.2021.05.010}, url = {}, author = {Daniel Galv{\^e}as and Fernando Barros and Carlos Alessandro Fuzo}, }

Reference Type: Journal Article

Subject Area(s): Medical Sciences