论文标题
COVID-19数据和政府政策的可靠性
Reliability of COVID-19 data and government policies
论文作者
论文摘要
我们研究不同国家的COVID-19案件和死亡的可用数据是如何可靠的。我们的分析基于对异常数字定律的修改，《纽科姆·奔驰法》适用于每个国家的每日死亡人数和新案件。我们首先重新审视Newcomb-Benford法律，并展示如何避免数据对数据的虚假负面依从性。然后，我们通过计算每个索引与\ c {hi}之间的Spearman等级顺序相关性来比较每个国家 /地区的许多社会和经济指数。对具有足够可用数据的同一国家的过剩死亡进行了类似的分析。我们得出的结论是，总的来说，民主党不那么民主，透明和腐败的国家往往具有质量较低的数据。我们还讨论了当前方法的局限性。
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.
