Using Benford’s law to assess the quality of COVID-19 register data in Brazil | Zendy

Lucas Silva | Zendy; Dalson Britto Figueiredo Filho | Zendy

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Using Benford’s law to assess the quality of COVID-19 register data in Brazil

Author(s) -

Lucas Silva,

Dalson Britto Figueiredo Filho

Publication year - 2020

Publication title -

journal of public health

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.916

H-Index - 82

eISSN - 1741-3850

pISSN - 1741-3842

DOI - 10.1093/pubmed/fdaa193

Subject(s) - benford's law , covid-19 , statistics , goodness of fit , reliability (semiconductor) , econometrics , standard deviation , data quality , register (sociolinguistics) , actuarial science , mathematics , medicine , economics , virology , metric (unit) , power (physics) , physics , operations management , disease , pathology , quantum mechanics , outbreak , infectious disease (medical specialty) , linguistics , philosophy

We employ Newcomb-Benford law (NBL) to evaluate the reliability of COVID-19 figures in Brazil. Using official data from February 25 to September 15, we apply a first digit test for a national aggregate dataset of total cases and cumulative deaths. We find strong evidence that Brazilian reports do not conform to the NBL theoretical expectations. These results are robust to different goodness of fit (chi-square, mean absolute deviation and distortion factor) and data sources (John Hopkins University and Our World in Data). Despite the growing appreciation for evidence-based-policymaking, which requires valid and reliable data, we show that the Brazilian epidemiological surveillance system fails to provide trustful data under the NBL assumption on the COVID-19 epidemic.

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