A Mathematical Interpretation of the Pattern of COVID-19 Post-Vaccination Mortality and Excess Mortality
DOI:
https://doi.org/10.51094/jxiv.352Keywords:
Pattern of COVID-19 Post-Vaccination Mortality, Erlang distribution, Excess MortalityAbstract
Reference [1] presents a histogram with the number of days from COVID-19 vaccination to death on the horizontal axis and the number of deaths on the vertical axis, based on a report from the Ministry of Health, Labour and Welfare (MHLW). This article gives a mathematical interpretation of the histogram and discusses excess mortality based on this interpretation.
Conflicts of Interest Disclosure
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References
Masanori Fukushima, Yuriko Hirai, Eiji Nakatani and Tsutomu Nishimura, Overview of COVID-19 postvaccination mortality and pharmacoepidemiological evaluation: nation-wide view and a proposal, Clinical Evaluation. 2022;49(3):499-517.
Masanori Fukushima, Takayuki Kikuchi and Yuriko Hirai, Warnings and Requests to Coronavirus Vaccine Recipients and All Healthcare Providers -Based on the case of a healthy 28-year-old man who died suddenly of myocardial rhabdomyolysis 5 days after vaccination with the novel coronavirus vaccine, Clinical Evaluation. 2023;50(4):507-542.
Kiyoshi Ito, [Probability theory and I], Kakuritsuron to watashi (in Japanese), Iwanami Shoten, Publishers, (2010/9/15) ISBN 9784000052085.
Wikipedia, Erlang distribution, https://en.wikipedia.org/wiki/Erlang_distribution
Wikipedia, Exponential distribution, https://en.wikipedia.org/wiki/Exponential_distribution
Wikipedia, Stirling's approximation, https://en.wikipedia.org/wiki/Stirling's_approximation
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Submitted: 2023-04-05 05:03:56 UTC
Published: 2023-04-06 02:49:10 UTC — Updated on 2023-04-12 04:54:26 UTC
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- 2023-11-20 00:21:09 UTC (9)
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- 2023-09-15 08:56:15 UTC (7)
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- 2023-06-13 09:35:08 UTC (4)
- 2023-05-19 08:52:56 UTC (3)
- 2023-04-12 04:54:26 UTC (2)
- 2023-04-06 02:49:10 UTC (1)
Reason(s) for revision
Some equations and sentences are changed in the first half of Section 2. Stirling’s formula is added in Section 3.License
Copyright (c) 2023
Takashi Nakamura
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
