COVID-19 data, mitigation policies and Newcomb–Benford law

We study how reliable are available data on COVID-19 cases and deaths in different countries. Our analysis is based on a modification of the law of anomalous numbers, the Newcomb–Benford law, applied to the daily number of deaths and new cases in each country. We first revisit the Newcomb–Benford law and show how to avoid false negative compliance with the data. We then compare the χ2 statistics deviation from this law to a number of social and economic indices for each country by computing the Spearman rank-order correlation between them and the χ2 deviation. We considered the proportion of excess deaths for those countries with sufficient available data for a good estimate and obtained similar results: less democratic, less transparent, and more corrupt countries tend to have data of lesser quality. We also discussed the limitations of the present approach and which countries the results were significant for.