This work is cited by the following items of the Benford Online Bibliography:
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. DOI:10.1177/1010539520927265. | ![]() |
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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. | ![]() |
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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. | ![]() |
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Leung, CH, Luo, YB, Lok, TC and Luo, ZC (2021). Analysis and Prediction of COVID-19 Data Quality Based on Benford's Law-- Take Data from 51 Countries and Regions as an Example. Science Innovation 9(2), pp. 53-62. DOI:10.11648/j.si.20210902.14. CHI | ![]() |
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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. | ![]() |
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Moreno-Montoya, J (2020). Benford ́s Law with small sample sizes: A new exact test useful in health sciences during epidemics. Revista de la Universidad Industrial de Santander. Salud UIS vol. 52(2), pp. 161-163. | ![]() |
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