论文标题
COVID-19报告的数据分析
Digit analysis for Covid-19 reported data
论文作者
论文摘要
2019年12月在武汉出现的冠状病毒已在全球范围内散布，并导致了280,000多人的死亡（截至2020年5月11日）。自2020年2月以来，对中国政府报告的确认案件和死亡人数提出了疑问。在本文中，我们研究了中国在城市和省级提供的数据，并将其与加拿大省数据，美国州数据和法国地区数据进行了比较。我们考虑累积和每天的确认病例和死亡人数，并通过其前两个数字的镜头检查这些数字，特别是我们测量了前两位数字到Newcomb-Benford分布的偏离，通常用于检测欺诈。我们的发现是，没有证据表明所有这些国家的累积和每日已确认案件和死亡都有不同的第一或第二位分布。我们还表明，这些数据无法拒绝Newcomb-Benford分布。
The coronavirus which appeared in December 2019 in Wuhan has spread out worldwide and caused the death of more than 280,000 people (as of May, 11 2020). Since February 2020, doubts were raised about the numbers of confirmed cases and deaths reported by the Chinese government. In this paper, we examine data available from China at the city and provincial levels and we compare them with Canadian provincial data, US state data and French regional data. We consider cumulative and daily numbers of confirmed cases and deaths and examine these numbers through the lens of their first two digits and in particular we measure departures of these first two digits to the Newcomb-Benford distribution, often used to detect frauds. Our finding is that there is no evidence that cumulative and daily numbers of confirmed cases and deaths for all these countries have different first or second digit distributions. We also show that the Newcomb-Benford distribution cannot be rejected for these data.
