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Lee, K-B, Han, S and Jeong, Y (2020). COVID-19, flattening the curve, and Benford’s law. Physica A: Statistical Mechanics and its Applications 559, 125090.

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Anab, F, Khaliq, A and Younas, I (2021). A Statistical Analysis of Covid-19 Data of Pakistan by Applying Benford’s Law. Journal of Applied Pharmacy 13, pp. 55-60. View Complete Reference No online information available Works that this work references No Bibliography works reference this work
Burgos, A and Santos, A (2021). The Newcomb–Benford law: Scale invariance and a simple Markov process based on it (Previous title: The Newcomb–Benford law: Do physicists use more frequently the key 1 than the key 9?). Preprint arXiv:2101.12068 [physics.pop-ph]; last accessed October 5, 2021. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Carmo, CRS, Caneppele, FdL and Nunes, FC (2021). Analysis of Covid-19 Contamination and Deaths Cases in Brazil According to The Newcomb-Benford Law. Revista Brasileira de Biometria 39(4), pp.522-535. DOI:10.28951/rbb.v39i4.535. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Chatterjee, S, Sarkar, A, Karmakar, M, Chatterjee, S and Paul, R (2020). EIRD model to study the asymptomatic growth during COVID-19 pandemic in India. Indian Journal of Physics. DOI:10.1007/s12648-020-01928-8. View Complete Reference Online information Works that this work references No Bibliography works reference this work
D'Alessandro, A (2020). Benford's law and metabolomics: A tale of numbers and blood. Transfusion and Apheresis Science 59(6), pp. 103019. DOI:10.1016/j.transci.2020.103019. View Complete Reference Online information Works that this work references Works that reference this work
Dissanayake, CK and Daniel, J (2021). Do Pandemic Related Datasets with High Artificial Control Still Follow the Benford’s Law?. Proceedings of the 4th European International Conference on Industrial Engineering and Operations Management, Rome, Italy, August 2-5. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Erfani, A, Zhang, K and Cui, Q (2021). TAB Bid Irregularity: Data-Driven Model and Its Application. Journal of Management in Engineering 37(5), p. 04021055. DOI:10.1061/(ASCE)ME.1943-5479.0000958. View Complete Reference No online information available Works that this work references No Bibliography works reference this work
Farhadi, N (2021). Can we rely on COVID-19 data? An assessment of data from over 200 countries worldwide. Science Progress 104(2). DOI:10.1177/00368504211021232. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2021). Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries. COVID 1, pp. 137–152. DOI:10.3390/covid1010013. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2021). Pandemic Growth and Benfordness: Empirical Evidence from 176 Countries Worldwide. COVID 1(1), pp. 366-383. DOI:10.3390/covid1010031. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2022). Forensic Analysis of COVID-19 Data from 198 Countries Two Years after the Pandemic Outbreak. COVID 2(4), pp. 472-484. DOI:10.3390/covid2040034. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Herteliu, C, Jianu, I, Dragan, IM, Apostu, S and Luchian, I (2021). Testing Benford’s Laws (non)conformity within disclosed companies’ financial statements among hospitality industry in Romania. Physica A: Statistical Mechanics and its Applications 582, p. 126221. DOI:10.1016/j.physa.2021.126221. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Ileanu, B-V (2021). Time Lag Evidence of Anti-Abortion Decree and Perturbation of Births Distribution. A Benford Law Approach. Preprint arXiv:2106.15520 [physics.soc-ph]; last accessed July 30, 2021. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Jošić, H and Žmuk, B (2021). Assessing the Quality of COVID-19 Data: Evidence from Newcomb-Benford Law. Facta Universitatis, in press. DOI:10.22190/FUEO210326008J. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Kilani, A (2021). Authoritarian regimes' propensity to manipulate Covid-19 data: a statistical analysis using Benford's Law. Commonwealth & Comparative Politics . DOI:10.1080/14662043.2021.1916207. View Complete Reference Online information Works that this work references Works that reference this work
Koesters, N, McMenemy, A and Bélanger, Y (2020). Simulating Epidemics with a SIRD Model and Testing with Benford’s Law. Preprint. View Complete Reference Online information Works that this work references Works that reference this work
Malvar, S and Meneghini, JR (2022). Machine learning approaches for localized lockdown during COVID-19: a case study analysis. Preprint arXiv:2201.00715 [cs.LG]; last accessed January 9, 2022. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Morillas-Jurado, FG, Caballer-Tarazona, M and Caballer-Tarazona, V (2022). Applying Benford’s Law to Monitor Death Registration Data: A Management Tool for the COVID-19 Pandemic. Mathematics 10(1), 46. DOI:10.3390/math10010046. View Complete Reference Online information Works that this work references Works that reference this work
Us, D (2021). Benford's Law: An Empirical Analysis of Reported Covid-19 Cases and Institutional Structures Around the Globe . Undergraduate Thesis, Università commerciale Luigi Bocconi, Milan. DOI:10.13140/RG.2.2.28839.88488. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Wei, A and Vellwock, AE (2020). Is COVID-19 data reliable? A statistical analysis with Benford's Law. Preprint, posted September. DOI:10.13140/RG.2.2.31321.75365/1. View Complete Reference Online information Works that this work references Works that reference this work
Wong, WK, Juwono, FH, Loh, WN and Ngu, IY (2020). Newcomb-Benford Law Analysis on COVID-19 Daily Infection Cases and Deaths in Indonesia and Malaysia. Research Square preprint. DOI:10.21203/rs.3.rs-131072/v1. View Complete Reference Online information Works that this work references Works that reference this work