On the authenticity of COVID-19 case figures
In this article, we study the applicability of Benford's law and Zipf's law to national COVID-19 case figures with the aim of establishing guidelines upon which methods of fraud detection in epidemiology, based on formal statistical analysis, can be developed. Moreover, these approaches ma...
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| Veröffentlicht in: | PloS one 2020-12, Vol.15 (12), p.e0243123-e0243123 |
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| creator | Kennedy, Adrian Patrick Yam, Sheung Chi Phillip |
| description | In this article, we study the applicability of Benford's law and Zipf's law to national COVID-19 case figures with the aim of establishing guidelines upon which methods of fraud detection in epidemiology, based on formal statistical analysis, can be developed. Moreover, these approaches may also be used in evaluating the performance of public health surveillance systems. We provide theoretical arguments for why the empirical laws should hold in the early stages of an epidemic, along with preliminary empirical evidence in support of these claims. Based on data published by the World Health Organization and various national governments, we find empirical evidence that suggests that both Benford's law and Zipf's law largely hold across countries, and deviations can be readily explained. To the best of our knowledge, this paper is among the first to present a practical application of Zipf's law to fraud detection. |
| doi_str_mv | 10.1371/journal.pone.0243123 |
| format | Article |
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To the best of our knowledge, this paper is among the first to present a practical application of Zipf's law to fraud detection.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0243123</identifier><identifier>PMID: 33290420</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Coronaviruses ; COVID-19 ; COVID-19 - epidemiology ; Dengue fever ; Economic development ; Empirical analysis ; Epidemics ; Epidemiology ; False information (Law) ; Federal government ; Fraud ; Fraud investigation ; Health surveillance ; Hong Kong ; Humans ; Legislation ; Medicine and Health Sciences ; Methods ; Models, Theoretical ; Pandemics ; Pandemics - statistics & numerical data ; People and Places ; Public health ; Regions ; Reproducibility of Results ; SARS-CoV-2 - pathogenicity ; Severe acute respiratory syndrome coronavirus 2 ; Social Sciences ; Statistical analysis ; Statistics ; Surveillance systems</subject><ispartof>PloS one, 2020-12, Vol.15 (12), p.e0243123-e0243123</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Kennedy, Yam. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kennedy, Adrian Patrick</au><au>Yam, Sheung Chi Phillip</au><au>Verdonck, Kristien</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>On the authenticity of COVID-19 case figures</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-12-08</date><risdate>2020</risdate><volume>15</volume><issue>12</issue><spage>e0243123</spage><epage>e0243123</epage><pages>e0243123-e0243123</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In this article, we study the applicability of Benford's law and Zipf's law to national COVID-19 case figures with the aim of establishing guidelines upon which methods of fraud detection in epidemiology, based on formal statistical analysis, can be developed. Moreover, these approaches may also be used in evaluating the performance of public health surveillance systems. We provide theoretical arguments for why the empirical laws should hold in the early stages of an epidemic, along with preliminary empirical evidence in support of these claims. Based on data published by the World Health Organization and various national governments, we find empirical evidence that suggests that both Benford's law and Zipf's law largely hold across countries, and deviations can be readily explained. To the best of our knowledge, this paper is among the first to present a practical application of Zipf's law to fraud detection.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>33290420</pmid><doi>10.1371/journal.pone.0243123</doi><tpages>e0243123</tpages><orcidid>https://orcid.org/0000-0002-4380-0919</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Coronaviruses COVID-19 COVID-19 - epidemiology Dengue fever Economic development Empirical analysis Epidemics Epidemiology False information (Law) Federal government Fraud Fraud investigation Health surveillance Hong Kong Humans Legislation Medicine and Health Sciences Methods Models, Theoretical Pandemics Pandemics - statistics & numerical data People and Places Public health Regions Reproducibility of Results SARS-CoV-2 - pathogenicity Severe acute respiratory syndrome coronavirus 2 Social Sciences Statistical analysis Statistics Surveillance systems |
| title | On the authenticity of COVID-19 case figures |
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