Applying Benford's law to COVID-19 data: the case of the European Union.

ABSTRACT

BACKGROUND: Previous studies have used Benford's distribution to assess the accuracy of COVID-19 data. Data inaccuracies provide false information to the media, undermine global response and hinder the preventive measures taken by authorities. METHODS: Daily new cases and deaths from all the countries of the European Union were analyzed and the conformance to Benford's distribution was estimated. Two statistical tests and two measures of deviation were calculated to determine whether the reported statistics comply with the expected distribution. Four country-level developmental indexes were included, the GDP per capita, health expenditures, the Universal Health Coverage (UHC) Index and the full vaccination rate. Regression analysis was implemented to examine whether the deviation from Benford's distribution is affected by the aforementioned indexes. RESULTS: The findings indicate that Bulgaria, Croatia, Lithuania and Romania were in line with Benford's distribution. Regarding daily cases, Denmark, Ireland and Greece, showed the greatest deviation from Benford's distribution. Furthermore, it was found that the vaccination rate is positively associated with deviation from Benford's distribution. CONCLUSIONS: The findings suggest that overall, official data provided by authorities are not confirming Benford's law, yet this approach acts as a preliminary tool for data verification. More extensive studies should be made with a more thorough investigation of countries that showed the greatest deviation.