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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Data-Forensic Determination of the Accuracy of International COVID-19 Reporting: Using Zipf’s Law for Pandemic Investigation

Author 1: Aamo Iorliam
Author 2: Anthony T S Ho
Author 3: Santosh Tirunagari
Author 4: David Windridge
Author 5: Adekunle Adeyelu
Author 6: Samera Otor
Author 7: Beatrice O. Akumba

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120106

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 1, 2021.

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Abstract: Severe outbreaks of infectious disease occur throughout the world with some reaching the level of international pandemic: Coronavirus (COVID-19) is the most recent to do so. In this paper, a mechanism is set out using Zipf’s law to establish the accuracy of international reporting of COVID-19 cases via a determination of whether an individual country’s COVID-19 reporting follows a power-law for confirmed, recovered, and death cases of COVID-19. The probability of Zipf’s law (P-values) for COVID-19 confirmed cases show that Uzbekistan has the highest P-value of 0.940, followed by Belize (0.929), and Qatar (0.897). For COVID-19 recovered cases, Iraq had the highest P-value of 0.901, followed by New Zealand (0.888), and Austria (0.884). Furthermore, for COVID-19 death cases, Bosnia and Herzegovina had the highest P-value of 0.874, followed by Lithuania (0.843), and Morocco (0.825). China, where the COVID-19 pandemic began, is a significant outlier in recording P-values lower than 0.1 for the confirmed, recovered, and death cases. This raises important questions, not only for China, but also any country whose data exhibits P-values below this threshold. The main application of this work is to serve as an early warning for World Health Organization (WHO) and other health regulatory bodies to perform more investigations in countries where COVID-19 datasets deviate significantly from Zipf’s law. To this end, this paper provide a tool for illustrating Zipf’s law P-values on a global map in order to convey the geographic distribution of reporting anomalies.

Keywords: COVID-19; power-law; pandemic; Zipf’s Law; WHO

Aamo Iorliam, Anthony T S Ho, Santosh Tirunagari, David Windridge, Adekunle Adeyelu, Samera Otor and Beatrice O. Akumba, “Data-Forensic Determination of the Accuracy of International COVID-19 Reporting: Using Zipf’s Law for Pandemic Investigation” International Journal of Advanced Computer Science and Applications(IJACSA), 12(1), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120106

@article{Iorliam2021,
title = {Data-Forensic Determination of the Accuracy of International COVID-19 Reporting: Using Zipf’s Law for Pandemic Investigation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120106},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120106},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {1},
author = {Aamo Iorliam and Anthony T S Ho and Santosh Tirunagari and David Windridge and Adekunle Adeyelu and Samera Otor and Beatrice O. Akumba}
}


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