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Inconsistencies in countries COVID-19 data revealed by Benford's law

机译:COVID-19数据的国家不一致,本福德法律透露

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Reporting of daily new cases and deaths on COVID-19 is one of the main tools to understand and menage the pandemic. However, governments and health authorities worldwide present divergent procedures while registering and reporting their data. Most of the bias in those procedures are influenced by economic and political pressures and may lead to intentional or unintentional data corruption, what can mask crucial information. Benford’s law is a statistical phenomenon, extensively used to detect data corruption in large data sets. Here, we used the Benford’s law to screen and detect inconsistencies in data on daily new cases of COVID-19 reported by 80 countries. Data from 26 countries display severe nonconformity to the Benford’s law (p 0.01), what may suggest data corruption or manipulation.
机译:关于Covid-19日常新病例和死亡的报告是理解和培养大流行的主要工具之一。 但是,全球各国政府和卫生当局在登记和报告其数据时出现不同的程序。 这些程序中的大多数偏见受到经济和政治压力的影响,可能导致故意或无意的数据腐败,什么可以掩盖至关重要的信息。 本福德的法律是一种统计现象,广泛用于检测大数据集中的数据损坏。 在这里,我们利用本公司的法律筛选并检测80个国家报告的日常科迪德 - 19日新案例的数据中的不一致。 来自26个国家的数据对本福德的法律显示出严重的不合格(P <0.01),可能会建议数据损坏或操纵。

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