本福德定律揭示了各国COVID-19数据的不一致性

Q4 Mathematics

Model Assisted Statistics and Applications Pub Date : 2021-01-01 DOI:10.3233/MAS-210517

Vitor Hugo Moreau

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引用次数: 4

摘要

每日报告COVID-19新发病例和死亡病例是了解和管理大流行的主要工具之一。然而，世界各国政府和卫生当局在登记和报告其数据时采用不同的程序。这些程序中的大多数偏见都受到经济和政治压力的影响，可能导致有意或无意的数据损坏，从而掩盖关键信息。本福德定律是一种统计现象，广泛用于检测大型数据集中的数据损坏。在这里，我们使用本福德定律来筛选和发现80个国家报告的每日新病例数据中的不一致之处。来自26个国家的数据显示严重不符合本福德定律(p< 0.01)，这可能表明数据损坏或操纵。©2021 - IOS出版社。版权所有。

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

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. © 2021 - IOS Press. All rights reserved.

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来源期刊

Model Assisted Statistics and Applications Mathematics-Applied Mathematics

CiteScore

1.00

自引率

0.00%

发文量

期刊介绍： Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.