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Article

Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries

1
School of Business and Management, IU International University of Applied Sciences, 10247 Berlin, Germany
2
Sydney Medical School, Nepean Clinical School, University of Sydney, Sydney, NSW 2747, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Guglielmo Campus
COVID 2021, 1(1), 137-152; https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010013 (registering DOI)
Received: 17 June 2021 / Revised: 3 July 2021 / Accepted: 7 July 2021 / Published: 16 July 2021
When it comes to COVID-19, access to reliable data is vital. It is crucial for the scientific community to use data reported by independent territories worldwide. This study evaluates the reliability of the pandemic data disclosed by 182 countries worldwide. We collected and assessed conformity of COVID-19 daily infections, deaths, tests, and vaccinations with Benford’s law since the beginning of the coronavirus pandemic. It is commonly accepted that the frequency of leading digits of the pandemic data shall conform to Benford’s law. Our analysis of Benfordness elicits that most countries partially distributed reliable data over the past eighteen months. Notably, the UK, Australia, Spain, Israel, and Germany, followed by 22 different nations, provided the most reliable COVID-19 data within the same period. In contrast, twenty-six nations, including Tajikistan, Belarus, Bangladesh, and Myanmar, published less reliable data on the coronavirus spread. In this context, over 31% of countries worldwide seem to have improved reliability. Our measurement of Benfordness moderately correlates with Johns Hopkin’s Global Health Security Index, suggesting that the quality of data may depend on national healthcare policies and systems. We conclude that economically or politically distressed societies have declined in conformity to the law over time. Our results are particularly relevant for policymakers worldwide. View Full-Text
Keywords: COVID-19; data analytics; forensic; Benford’s law; organizational learning COVID-19; data analytics; forensic; Benford’s law; organizational learning
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MDPI and ACS Style

Farhadi, N.; Lahooti, H. Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries. COVID 2021, 1, 137-152. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010013

AMA Style

Farhadi N, Lahooti H. Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries. COVID. 2021; 1(1):137-152. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010013

Chicago/Turabian Style

Farhadi, Noah, and Hooshang Lahooti. 2021. "Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries" COVID 1, no. 1: 137-152. https://0-doi-org.brum.beds.ac.uk/10.3390/covid1010013

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