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Koesters, N, McMenemy, A and Bťlanger, Y (2020)

Simulating Epidemics with a SIRD Model and Testing with Benfordís Law

Preprint.

ISSN/ISBN: Not available at this time. DOI: Not available at this time.



Abstract: In this paper, we use Monte Carlo simulations with a SIRD model parameterised from the literature and test with many metrics if Benfordís Law is fulfilled in 4 different scenarios. The results confirm that the NewcombĖBenford law could theoretically be an adequate tool to assess Covid-19 infected data reporting. The challenges in using Benfordís law in epidemics reporting are posed by the counting process in the real world where non malignant errors are introduced by lack of tests. One should as such see Benfordís law not as fraud detection tool, than as a assistive tool to measure reporting effectiveness in the real world.


Bibtex:
@misc{, AUTHOR = {Nils Koesters and Andrena McMenemy and Yohan B{\'e}langer}, TITLE = {Simulating Epidemics with a SIRD Model and Testing with Benfordís Law} YEAR = {2020}, URL = {https://www.researchgate.net/profile/Nils_Koesters/publication/344671690_SIMULATING_EPIDEMICS_WITH_A_SIRD_MODEL_AND_TESTING_WITH_BENFORD'S_LAW_A_PREPRINT/links/5f88558ea6fdccfd7b62bfd9/SIMULATING-EPIDEMICS-WITH-A-SIRD-MODEL-AND-TESTING-WITH-BENFORDS-LAW-A-PREPRINT.pdf}, }


Reference Type: Preprint

Subject Area(s): Medical Sciences