Cross Reference Up

Idrovo, AJ and Manrique-Hernández, EF (2020). Data Quality of Chinese Surveillance of COVID-19: Objective Analysis Based on WHO’s Situation Reports. Asia Pacific Journal of Public Health.

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

Note that this list may be incomplete, and is currently being updated. Please check again at a later date.

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 Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that 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 Works that reference this work
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. View Complete Reference Online information Works that this work references No Bibliography works reference this work
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. View Complete Reference Online information Works that this work references No Bibliography works reference this work
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 . View Complete Reference Online information Works that this work references No Bibliography works 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 Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
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. View Complete Reference Online information Works that this work references Works that reference this work
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. 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
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. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Pröger, L (2021). Anwendbarkeit des Benford-Gesetzes auf Bewegungsdaten von Wildtieren. Masters Thesis, Institut für Wildbiologie und Jagdwirtschaft, Universität für Bodenkultur Wien. GER View Complete Reference Online information Works that this work references Works that 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