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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.

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Agyemang, EF, Mensah, JA and Nyarko, E (2023). How dependable is World Continental COVID-19 data? Disclosure of Inconsistencies in Daily Reportage Confirmed Cases, Recovered and Deaths During First Wave. Preprint – submitted to Heliyon. DOI:10.2139/ssrn.4516032. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Atakan, S and Orman, G (2023). On the usage of Benford’s Law on coronavirus data statistics. Proceedings of 2023 IEEE International Conference on Big Data (BigData), pp. 4848-4853. DOI:10.1109/BigData59044.2023.10386606. View Complete Reference Online information Works that this work references No Bibliography works 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
Filho, TMR, Mendes, JFF, Lucio, ML and Moret, MA (2022). Reliability of COVID-19 data and government policies. Preprint arXiv:2208.11226 [physics.soc-ph]; last accessed August 31, 2022. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Filho, TMR, Mendes, JFF, Lucio, ML and Moret, MA (2023). COVID-19 data, mitigation policies and Newcomb–Benford law. Chaos, Solitons and Fractals 174 p. 113814. DOI:10.1016/j.chaos.2023.113814. View Complete Reference Online information Works that this work references Works that reference this work
Hulme, PE, Ahmed, DA, Haubrock, PJ, Kaiser, BA, Kourantidou, M, Leroy, B and McDermott, SM (2023). Widespread imprecision in estimates of the economic costs of invasive alien species worldwide. Science of the Total Environment, pp. 167997. DOI:10.1016/j.scitotenv.2023.167997. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Jiang, C, Zhang, X and Hu, B (2024). Government reporting credibility as immunity: Evidence from a public health event. Journal of Multinational Financial Management 73. DOI:10.1016/j.mulfin.2024.100847. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Kolias, P (2022). Applying Benford’s law to COVID-19 data: the case of the European Union. Journal of Public Health 44(2), pp. e221-e226. DOI:10.1093/pubmed/fdac005. View Complete Reference Online information Works that this work references Works that reference this work
Parreño, SJE (2023). Analyzing crop production statistics of the Philippines using the newcomb-benford law. Multidisciplinary Science Journal. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Silva, LEdO and Figueiredo, D (2024). A novel approach to evaluate data integrity: evidence from COVID-19 in China. Brazilian Journal of Biometrics 42(1), pp. 78-87. DOI:10.28951/bjb.v42i1.659. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Sinaga, ES and Sudharma, NI (2024). Benford’s law analysis to evaluate the quality data of COVID-19 epidemiological surveillance in Indonesia. International Journal of Public Health Science (IJPHS) vol. 13 (1), pp. 7-13. View Complete Reference Online information Works that this work references No Bibliography works reference this work