Version 1
: Received: 4 June 2021 / Approved: 7 June 2021 / Online: 7 June 2021 (14:25:44 CEST)
Version 2
: Received: 7 June 2021 / Approved: 8 June 2021 / Online: 8 June 2021 (10:19:38 CEST)
Version 3
: Received: 11 June 2021 / Approved: 11 June 2021 / Online: 11 June 2021 (15:47:44 CEST)
How to cite:
Perez, J. The BFP (Benford-Fibonacci-Perez) Method Validates the Consistency of COVID-19 Epidemiological Data in France and Italy. Preprints.org2021, 2021060187. https://doi.org/10.20944/preprints202106.0187.v2
Perez, J. The BFP (Benford-Fibonacci-Perez) Method Validates the Consistency of COVID-19 Epidemiological Data in France and Italy. Preprints.org 2021, 2021060187. https://doi.org/10.20944/preprints202106.0187.v2
Cite as:
Perez, J. The BFP (Benford-Fibonacci-Perez) Method Validates the Consistency of COVID-19 Epidemiological Data in France and Italy. Preprints.org2021, 2021060187. https://doi.org/10.20944/preprints202106.0187.v2
Perez, J. The BFP (Benford-Fibonacci-Perez) Method Validates the Consistency of COVID-19 Epidemiological Data in France and Italy. Preprints.org 2021, 2021060187. https://doi.org/10.20944/preprints202106.0187.v2
Abstract
The Benford method can be used to detect manipulation of epidemiological or trial data during the validation of new drugs. We extend here the Benford method after having detected particular properties for the Fibonacci values 1, 2, 3, 5 and 8 of the first decimal of 10 runs of official epidemiological data published in France and Italy (positive cases, intensive care, and deaths) for the periods of March 1 to May 30, 2020 and 2021, each with 91 raw data. This new method – called “BFP” for Benford-Fibonacci-Perez - is positive in all 10 cases (i.e. 910 values) with an average of favorable cases close to 80%, which, in our opinion, would validate the reliability of these basic data.
Keywords
SARS-CoV2; Biomathematics; Benford law; trials; Epidemiology; Fibonacci; data analysis; big data
Subject
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Jean-claude Perez
Commenter's Conflict of Interests: Author
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