M. L. Lucio | Searcharxiv

arXiv2022

COVID-19 denialism in Brazil: a multifactor study

We discuss the relationships between the outcome of the COVID-19 pandemic in Brazil at the municipal level and different health, social, demographic, and economic indices. We obtain significant correlations between the data gathered for each municipalitiy and the proportion of cases and deaths by COVID-19 and the results by municipality of the 2018 Brazilian presidential election. We obtain different estimates for the number of deaths caused by central government denialism of scientific facts and measures for mitigation of the pandemic and its the historical, economic, and social roots.

physics.soc-ph↗

arXiv2022

Reliability of COVID-19 data and government policies

We study how available data on COVID-19 cases and deaths in different countries are reliable. 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 of the data. We then compared deviation from this law, to a number of social and economic indices for each country by computing the Spearman rank order correlation between each index and the \c{hi}2 deviation of COVID- 19 data to the modified NB law. A similar analysis for excess deaths for the same countries with sufficient available data was performed. We conclude that in general less democratic, less transparent and more corrupt countries tend to have data of lesser quality. We also discuss the limitations of the present approach.

physics.soc-ph↗