This work is cited by the following items of the Benford Online Bibliography:

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. | ||||

Balashov, VS, Yan, Y and Zhu, X (2020). Who Manipulates Data During Pandemics? Evidence from Newcomb-Benford Law. Preprint arXiv:2007.14841 [econ.GN]; last accessed March 10, 2021. | ||||

Balashov, VS, Yan, Y and Zhu, X (2021). Using the Newcomb–Benford law to study the association between a country’s COVID-19 reporting accuracy and its development. Scientific Reports 11, pp. 22914. DOI:10.1038/s41598-021-02367-z. | ||||

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. | ||||

Carmo, CRS, Nunes, FC and Caneppele, FdL (2023). The limits of conformity analysis under the Newcomb-Benford law and the COVID-19 pandemic in Brazil . Brazilian Journal of Biometrics 41, pp. 234-248 . DOI:10.28951/bjb.v41i3.626. | ||||

Cerqueti, R and Provenzano, D (2023). Benford's Law for economic data reliability: The case of tourism flows in Sicily. Chaos, Solitons & Fractals 173, p. 113635. DOI:10.1016/j.chaos.2023.113635. | ||||

Dogan, AH, Altuntas, C, Gui, C, Tunalioglu, N and Erdogan, B (2023). Statistical Analysis of Covid-19 Outbreak with Benford’s Law. Journal of Management and Economics Research 21(2), pp. 120-133. DOI:10.11611/yead.1078847 . | ||||

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. | ||||

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. | ||||

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. | ||||

Filho, DF, Silva, L and Medeiros, H (2022). “Won’t get fooled again”: statistical fault detection in COVID-19 Latin American data. Globalization and Health 18, pp.105. DOI:10.1186/s12992-022-00899-1. | ||||

Idrovo, AJ, Manrique-Hernández, EF and Niño, JAF (2021). Report From Bolsonaro’s Brazil: The Consequences of Ignoring Science. International Journal of Health Services 51(1), pp. 31-36. DOI:10.1177/0020731420968446. | ||||

Kennedy, AP and Yam, SCP (2020). On the authenticity of COVID-19 case figures. PLoS ONE 15(12): e0243123. DOI:10.1371/journal.pone.0243123. | ||||

Koesters, N, McMenemy, A and Bélanger, Y (2020). Simulating Epidemics with a SIRD Model and Testing with Benford’s Law. Preprint. | ||||

Ngueilbaye, A, Huang, JZ, Khan, M and Wang, H (2023). Data quality model for assessing public COVID‑19 big datasets. The Journal of Supercomputing. DOI:10.1007/s11227-023-05410-0. | ||||

Pröger, L (2021). Anwendbarkeit des Benford-Gesetzes auf Bewegungsdaten von Wildtieren. Masters Thesis, Institut für Wildbiologie und Jagdwirtschaft, Universität für Bodenkultur Wien. GER | ||||

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. |