In this prior piece on comments from the public figure, Sam Harris, it is clear that perceptions of very high COVID death persist among those who could be characterized as the Glitterati (highly-popular talking-heads who parrot official narratives and enjoy lush lives). But none of it squares with a UK technical briefing:
[click to enlarge]
The above screenshot shows a computer simulation using the UK COVID deaths recorded in UK Technical Briefing No. 5, with an upward adjustment of those deaths to bring them in line with expectations beyond Day 28. One hundred and fifty million random “infection fatality rate” (IFR) values were first created and then put to the test:
Which ones were capable of reproducing the UK COVID death record?
Only 1,253 of those random IFR values were capable of reproducing known death data. At right is a histogram showing how frequently an IFR value was able to reproduce the death data. Notice the steep drop in probability of producing the known death data at IFR values above 0.0016 (0.16%).
Because it is a rough guide for the “proof” of something, a 99.99% Bayesian Credible Interval was formed and the boundaries are the vertical dashed lines. The chance of seeing an IFR value above the right-most dashed line is only 1 in 20,000, and that chance drops very quickly with each additional 0.01%. That line sits at .00196 (0.196%).
At far-right, the IFR required by the Imperial College London model which was used in order to justify UK (and even US) lockdowns was 0.009 (0.9%). This extensive simulation reveals that that IFR doesn’t have a snowball’s chance in hell of being true. But the true IFR has got be compatible with the evidence, so it must be much lower.
Reference
[The level of evidence required to make it appropriate to begin to talk about something as being “proven” — at least for practical purposes] — Veselinović I. [Microsatellite DNA analysis as a tool for forensic paternity testing (DNA paternity testing)]. Med Pregl. 2006 May-Jun;59(5-6):241-3. Serbian. doi: 10.2298/mpns0606241v. PMID: 17039906. https://pubmed.ncbi.nlm.nih.gov/17039906/
The probability of paternity of 99.99% or higher corresponds to the paternity "practically proven", indicating that the alleged father is the biological father.
[As of 19 Jan 2021, from 65,000 wild-type COVID infections, there were 65 deaths by Day 28; and from 52,000 Alpha (SGTF) variant COVID infections, there were 104 deaths by Day 28; 169 total deaths from 117,000 total infections] — Page 3. Epidemiological findings. UK Technical Briefing #5. https://www.gov.uk/government/publications/investigation-of-novel-sars-cov-2-variant-variant-of-concern-20201201
[“Time-to-death” model for COVID; using the 95% UB of both the mean and SD of the log-normal model that fit the actual deaths best] — Linton NM, Kobayashi T, Yang Y, et al. Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data. Journal of Clinical Medicine. 2020 Feb;9(2). DOI: 10.3390/jcm9020538. PMID: 32079150; PMCID: PMC7074197. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074197/
[Imperial College model using an evidence-contradicting IFR of 0.9%] — Imperial College COVID-19 Response Team. Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
[recent COVID model, likely alluded to by Sam Harris, which requires an IFR of at least 0.9% again, just like the Imperial College one did] — Two Years of U.S. COVID-19 Vaccines Have Prevented Millions of Hospitalizations and Deaths. https://doi.org/10.26099/whsf-fp90