In Part 1 of this series, it was discovered that there is a Fauci/Ferguson Narrative which makes COVID look like it might be a possible cause of the million excess deaths in the US, as well as millions upon millions of excess deaths elsewhere in the world.
Key points were that the Imperial College London model headed up by Neil Ferguson was essentially a farce, and that Anthony Fauci’s claim that COVID is 10x worse than flu is also looking to be demonstrated to be a farce.
Exhibit A (from Part 1)
“Exhibit A” in part 1 had included deep analysis on the 7 elderly deaths seen from an estimated 457 COVID infections among passengers on the Diamond Princess cruise ship in early February of 2020.
If Fauci’s claim that COVID is 10x worse than flu were true, then 41 elderly deaths would have been expected from the 457 infections in elderly on that cruise ship (the elderly IFR for flu is about 0.9%).
Because only 7 deaths were seen, the probability of COVID being 10x worse than flu is less than the annual probability of a random person being struck by lightning.
Because there is an annual lightning-strike death for every 12 million people in the US, and because about 10% of lightning strikes cause a death, the annual rate of lightning strikes is one strike per 1.2 million people.
That probability is pretty low, but it is not as low as the probability that Fauci was correct.
But using just 457 COVID infections in order to prove someone wrong may be considered unseemly, so let’s expand the count of followed COVID infections to 117,000 of them in order to get more precise about the true lethality of COVID.
Exhibit B
In UK technical briefing #5, it was reported that 117,000 infected people had been followed through time for 28 days, in order to see if they died or not. In 65,000 of these people were infections with wild-type COVID, and in another 52,000 of them were infections with the deadliest variant of COVID ever seen: Alpha variant.
Investigations which extend past the middle of January 2021 are all tainted by the fact that vaccine exposure could affect the results, so these early data are a veritable gold mine when it comes to discovering the true IFR on wild-type COVID and the deadliest-ever variant of COVID: Alpha variant.
Using a time-to-death analysis by Linton et. al., it is estimated that only about 89% of all COVID deaths are seen by Day 28 after symptom onset, so the recorded deaths above were adjusted accordingly. Here is an analysis on the kinds of wild-type COVID IFR values which can produce the expected total of 73 deaths from 65,000 infections:
You may notice that the IFR from the most-severe recent flu season is added to the graph at right for perspective. You may also notice that wild-type COVID, by only killing 73 out of 65,000 people infected, was no worse than severe flu. Unlike the Diamond Princess data, this analysis shows the probabilities associated with an overall IFR.
But Alpha variant infections were more fatal, so let’s also analyze the different probabilities which are associated with each different value for an Alpha variant IFR:
Notice how Alpha variant COVID was almost twice as bad as the severe flu of 2014/15 — when the flu IFR was 0.143% and 1 person out of every 700 people infected with flu ended up dying. That flu IFR is marked off in the graph at right.
As you can see at right, the estimated lethality of COVID which comes out of the Fauci/Ferguson narrative has such a little chance of being true that it is more likely that you’ll be hit by lightning:
The two competing narratives are the Fauci/Ferguson Narrative versus the Evidence-Based Narrative, where Bayesian inference is utilized on known death data in order to circumscribe the outer limits on the plausibility of what can be true of the world, given known data.
If government officials make statements which have less than one chance in a million of being true — because of known death data — then it is imperative to discover the truth.
The points scorecard now is
Fauci/Ferguson Narrative: 0 points
Evidence-Based Narrative: 2 points
Stay tuned for Exhibit C and Exhibit D, and any more which may follow, and we can keep track of the plausibility scorecard throughout.
Reference
[Past seasons CDC reports of symptomatic flu infections and flu deaths by age] — CDC. https://www.cdc.gov/flu/about/burden/index.html
[16% of all flu infections remain asymptomatic; 84% of them progress to symptoms] — Leung NH, Xu C, Ip DK, Cowling BJ. Review Article: The Fraction of Influenza Virus Infections That Are Asymptomatic: A Systematic Review and Meta-analysis. Epidemiology. 2015 Nov;26(6):862-72. doi: 10.1097/EDE.0000000000000340. PMID: 26133025; PMCID: PMC4586318. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586318/
[As of 19 Jan 2021, from 52,000 COVID infections with Alpha (SGTF) variant, there were 104 deaths by Day 28, 1 death per 500 Alpha infections (IFR=0.20%)] — Page 3. Epidemiological findings. UK Technical Briefing #5 (PDF file). General page: https://www.gov.uk/government/publications/investigation-of-novel-sars-cov-2-variant-variant-of-concern-20201201
"On 19/01/2021, ... 104 deaths among SGTF cases (0.2%), within 28 days of specimen date."
[“Time-to-death” probability for COVID; using the 95% upper bound of both the mean and the SD of the lognormal model which had 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/
Image Attribution (lightning):
Page URL: https://commons.wikimedia.org/wiki/File:Lightning_Pritzerbe_01_(MK).jpg
Attribution: Mathias Krumbholz, CC BY-SA 3.0 <https://creativecommons.org/licenses/by-sa/3.0>, via Wikimedia Commons