One of the things which the authorities frowned upon early on during COVID was comparisons to the flu. The worst recent flu had been the 2017/18 flu season, but CDC went back in time (3 years after that season had ended) and altered the numbers — so that it no longer looks like such a bad flu season.
That’s okay, because there is still a bad flu season from 2014/15 which can be used in order to exemplify what “severe flu” looks like, including how lethal it is.
1) What range of plausible Infection Fatality Rates (IFRs) exist for COVID variants?
The infection fatality rate (IFR) is the total number of deaths divided by the total number of infections. Researchers have a hard time estimating it though, because the total number of infections is hard to pin down precisely.
A natural experiment occurred early during 2020 on the Diamond Princess cruise ship, where the total number of infections was known precisely: 696 total COVID infections according to the evacuation report.
In the time-span in which it remained plausible for the noted COVID deaths to have been linked to infection while aboard, 7 total people died. The strain of COVID was the original Wuhan-1 strain (wild-type).
The IFR was (7/696=) 0.0101, or 1.01% when put into percentage terms — but due to having such a high population age on the cruise, 75% of the COVID infections were in people over age 60. All 7 deaths were elderly passengers (neither young, nor crew).
The age-specific elderly IFR was 1.5%, which made the Wuhan-1 strain of COVID approximately 40% to 50% worse than flu (the elderly flu IFR for 6 recent seasons was 1.1%).
Indeed, a “What if?” analysis on the hypothetical attack of flu aboard the Diamond Princess reveals an expected 5 people would have died — 70% of the death which was seen when COVID attacked the ship:
In column E of the spreadsheet are the total number of infections by age when that total had reached 619 and Japan had released a detailed report. To raise the total up to the final count of 696 infections, numbers were added proportionally (blue shaded cells).
In cell C23, you have the ratio of elderly IFRs (COVID divided by flu). The takeaway message is that COVID is signficantly worse than flu, but at least it is not twice as bad as flu.
For several months, the Diamond Princess data remained the most complete COVID data set on the planet, until the Technical Briefings of the UK rolled out — specifically Technical Briefing No. 5, which precisely estimated the IFR of Alpha variant COVID.
While the UK followed all known COVID infections through time, they only counted deaths up to Day 28, and this cutoff can miss as much as 11% of the total COVID deaths which occur (11% of COVID deaths occur after Day 28, according to a time-to-death analysis cited below).
After adjusting their numbers for the residual/remainder of expected deaths from COVID, I used Bayesian simulation to find out the probability distribution of true IFRs for Alpha variant:
A Bayesian Credible Interval allows for a probability interpretation, unlike what traditional Confidence Intervals allow for. To capture the entire range of plausible values, I ran a 99% Credible Interval on the imputed 117 deaths which came from 52,000 Alpha variant COVID infections in the UK.
The most likely IFR for Alpha variant COVID was 0.226%, which is 60% worse than the severe flu season of 2014/15 in the USA, when the flu IFR was 0.143%. The indication is that Alpha variant was even more deadly than wild-type COVID — though still not twice as deadly as “severe flu.”
The probability that the Alpha variant IFR was below 0.28% was 0.995, which calls into question all published scientific estimations which did not have confidence intervals with lower bounds reaching down below 0.28%.
Those estimates would not be consistent with the data from 52,000 COVID infections, indicating that something besides COVID was causing people to die. While there is a natural lower bound for estimating IFRs of diseases, there is no natural upper bound.
The inherent lethality of the disease itself, even with best medical practices, provides a hard lower bound on estimates. But because poor medical treatments can lead to higher and higher IFRs, there is no natural upper limit on IFR estimation.
The sky is the limit.
This makes the lower estimates “better” in that they are unlikely to be confounded or biased by the implementation of poor medical practices.
From Delta variant to Omicron variant, the IFR of COVID stepped down by about 60% each time, so that Delta variant was approximately 40% as lethal as Alpha, and Omicron only about 40% as lethal as Delta.
That means that Omicron is not even one-fifth as lethal as Alpha variant. This will become interesting below, as the sheer size of excess death rates during Omicron will be considered as to not be scientifically explainable if they are assumed to be the result of acute respiratory infection with COVID.
2) How does each COVID variant compare with severe flu?
The CDC data on past flu seasons reveals that the 2014/2015 season was severe:
The symptomatic “case fatality rate” for that season was 0.17% (30 million symptomatics and 51,000 deaths), but because about 16% of flu infections remain asymptomatic, adjustments bring the IFR down to about 0.14%.
As was noted above in the Bayesian analysis regarding the plausible range of COVID IFRs, Alpha variant COVID was still 60% higher than that (though not quite twice as bad as severe flu).
Note how that puts Delta variant on the same approximate level of severe flu, and more likely at a lower IFR than the flu IFR found in 2014/15. As for Omicron variant, not only is it not even close to severe flu, but it does not even approach the average of recent seasonal flu.
It is much safer to get an infection with Omicron than to get one with flu.
3) By how much can nations differ, regarding excess death from acute respiratory infections?
International differences in population age structure, as well as differences in the level and quality of medical care, among other things, will tend to lead to differences in the amount of excess death which is seen whenever there is an epidemic of acute respiratory infections.
When dozens of nations are examined and the average excess death rate due to influenza is recorded, you find that the maximal difference in excess deaths between any two nations can reach as high as 15-fold:
This 15-fold difference in excess death is the result of all of the differences between nations which exist — age structure, quality of medical care, etc. — so it can be considered to be “intrinsic.”
Death differences larger than 15-fold between nations would not be considered to be consistent with reality, given that international differences between nations were already “baked into” the maximal 15-fold difference found when dozens of nations were studied.
But between-nation death differences due to COVID are disturbingly as high as a thousand-fold. Here is an example of a more-than-500-fold difference in COVID death rates (Yemen vs. Singapore):
Because differences of up to 15-fold are explainable due to underlying differences between nations, differences beyond 15-fold would always require special explanation.
How come it took 2000 COVID cases to produce a single COVID death in Singapore on 19 Nov 2020 — while in Yemen, at the same time, there was AT LEAST one COVID death for every 4 COVID cases?
Were doctors in Singapore 500 times better at treating COVID than those in Yemen?
Applying the 15-fold natural difference between nations, COVID cases in Yemen were STILL 39 times more likely to die than those in Singapore. That’s a 39-fold difference AFTER accounting for the differences in death rates between nations.
Many nations have reduced their case fatality rates tremendously, but the frequency of testing can artificially reduce it if you find more cases. Actually, the reverse is true: the earlier lack of testing everyone (not finding enough of the cases which DO exist) was what it was that led to abnormally high case fatality rates in the first place.
Here are 25 examples of case fatality rates for Omicron:
Notice how most of the nations in the graph have case fatality rates that are lower than that found in the severe flu season of 2014/15.
This brings up a final “hard question” …
4) If COVID at its worst was never even twice as bad as severe flu, and is currently not even a fifth as bad as it was during Alpha variant (is now currently even safer to get than the flu), then where have all of the excess deaths been coming from?
There are only a few times in recorded history when excess deaths were as high as they were for 2020 into 2021 (and into the beginning of 2022). Here is a stylized graph of the accumulation of excess deaths over the first 19 months of COVID, as compared to the average accumulation of excess death during World War I and also during a most severe recent flu season:
Because of the inherent fatality of COVID — i.e., something that used to be worse than flu, but never twice as bad as severe flu — the excess death rate is not scientifically explainable by way of assuming that COVID is behind the bulk of the excess death.
COVID was never inherently lethal enough to cause the bulk of these deaths, so another explanation for them is required. A prime suspect which is capable of being an explanation for the bulk of these deaths is the COVID “vaccine.”
As an example, in Uruguay, excess deaths were not a problem until the COVID vaccine became available:
The excess death rate in many nations in the past few years, especially during Omicron, is not scientifically explainable if it is continued to be assumed that the bulk of the excess death has come from COVID.
The likely culprit here is the COVID “vaccine.”
Reference
[Diamond Princess breakdown of cases by age] — National Institute of Infectious Diseases in Japan. Available from: https://www.niid.go.jp/niid/en/2019-ncov-e/9417-covid-dp-fe-02.html
[Diamond Princess final evacuation report] — Anan H, Kondo H, Takeuchi I, Nakamori T, Ikeda Y, Akasaka O, Koido Y. Medical Transport for 769 COVID-19 Patients on a Cruise Ship by Japan Disaster Medical Assistance Team. Disaster Med Public Health Prep. 2020 Dec;14(6):e47-e50. doi: 10.1017/dmp.2020.187. Epub 2020 Jun 5. PMID: 32498735; PMCID: PMC7298096. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298096/
[“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/
[WHO COVID-19 Situation Report #72 on 1 Apr 2020 showing 7 Diamond Princess deaths (46 days after all passenger infections had occurred)] — WHO. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200401-sitrep-72-covid-19.pdf
[Past seasons CDC reports of flu infections and flu deaths] — CDC. https://www.cdc.gov/flu/about/burden/index.html
[Mortality Risk (case fatality rate) for COVID over time] — OWID. https://ourworldindata.org/mortality-risk-covid
[Daily share of the population receiving COVID-19 vaccine] — OWID. https://ourworldindata.org/covid-vaccinations
[Estimated Daily and Cumulative Excess Death during COVID] — The Economist data. OWID. https://ourworldindata.org/excess-mortality-covid
[USA lost 117,465 lives in 19 months of fighting in WWI] — https://www.census.gov/history/pdf/reperes112018.pdf
[84% fraction of flu infections with symptoms (16% asymptomatic)] — 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, 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."
[In almost 700,000 cases confirmed by sequencing, Delta was only 42% as lethal as Alpha (IFR ~ 0.09%)] — Table 3. Number of confirmed and probable cases by variant as of 11 October 2021. UK Technical Briefing #25. General page: https://www.gov.uk/government/publications/investigation-of-sars-cov-2-variants-technical-briefings
Specific page: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1025827/Technical_Briefing_25.pdf
[From 1.5 million confirmed cases, Omicron is 31% as lethal as Delta (IFR ~ 0.03%), making Omicron much safer than the seasonal flu] — Nyberg T, Ferguson NM, Nash SG, Webster HH, Flaxman S, Andrews N, Hinsley W, Bernal JL, Kall M, Bhatt S, Blomquist P, Zaidi A, Volz E, Aziz NA, Harman K, Funk S, Abbott S; COVID-19 Genomics UK (COG-UK) consortium, Hope R, Charlett A, Chand M, Ghani AC, Seaman SR, Dabrera G, De Angelis D, Presanis AM, Thelwall S. Comparative analysis of the risks of hospitalisation and death associated with SARS-CoV-2 omicron (B.1.1.529) and delta (B.1.617.2) variants in England: a cohort study. Lancet. 2022 Mar 16:S0140-6736(22)00462-7. doi: 10.1016/S0140-6736(22)00462-7. Epub ahead of print. PMID: 35305296; PMCID: PMC8926413. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8926413/
[For the 65 to 74 age group, the top 16 nations had mean acute respiratory disease death rates 4.8 times higher than the mean of the bottom 16 nations] — Iuliano AD, Roguski KM, Chang HH, Muscatello DJ, Palekar R, Tempia S, Cohen C, Gran JM, Schanzer D, Cowling BJ, Wu P, Kyncl J, Ang LW, Park M, Redlberger-Fritz M, Yu H, Espenhain L, Krishnan A, Emukule G, van Asten L, Pereira da Silva S, Aungkulanon S, Buchholz U, Widdowson MA, Bresee JS; Global Seasonal Influenza-associated Mortality Collaborator Network. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. Lancet. 2018 Mar 31;391(10127):1285-1300. doi: 10.1016/S0140-6736(17)33293-2. Epub 2017 Dec 14. Erratum in: Lancet. 2018 Jan 19;: PMID: 29248255; PMCID: PMC5935243. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5935243/
[Average daily excess death during 2018 in the Netherlands was 1.5 per million; peak daily death was 9.9 per million] -- van Asten L, Harmsen CN, Stoeldraijer L, Klinkenberg D, Teirlinck AC, de Lange MMA, Meijer A, van de Kassteele J, van Gageldonk-Lafeber AB, van den Hof S, van der Hoek W. Excess Deaths during Influenza and Coronavirus Disease and Infection-Fatality Rate for Severe Acute Respiratory Syndrome Coronavirus 2, the Netherlands. Emerg Infect Dis. 2021 Feb;27(2):411-420. doi: 10.3201/eid2702.202999. Epub 2021 Jan 4. PMID: 33395381; PMCID: PMC7853586. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853586/