reducing spread (aka lowering R0 which is the rate of viral spread at t=0 or Rt which is the rate of viral spread at time t>0) and/or
by lowering the risk of death if infected (i.e., they lower the infection fatality rate (IFR) which is typically measured as a change in the case fatality rate (CFR))
We can measure both impacts.
The most definitive measures show the R0 more than doubled, and the CFR was temporarily increased by over 2X post vaccine. There is no reliable evidence of reverse effects AFAIK.
Most importantly, nobody has been able to explain away the evidence I’ll show you below.
My argument
Let’s assume the vaccine saved lives.
Clearly, the greatest benefit of the vaccines will be in early 2021 because after that everyone is “naturally vaccinated” by the virus.
Secondly, vaccine efficacy wanes over time.
Therefore, if there is any benefit to be had, it would be most clearly demonstrable in early 2021.
There are only two ways a vaccine can provide a mortality benefit (and ChatGPT concurs):
reduce the R0 of subsequent variants (or the Rt of the current variant but it’s much less effective since it’s normally too late)
Reduce the IFR of the current or subsequent variants
The COVID vaccines did none of these. It increased both parameters.
The impact on R0 was to raise it, not lower it as promised
Remember “flatten the curve”? Vaccines are supposed to decimate R0 and crush it to be flat. They are NEVER supposed to amplify R0 which is what these vaccines clearly did and the evidence has been in plain sight for over 3 years now and nobody is paying attention.
The shape of the Omicron outbreak in Israel and Denmark is undeniable evidence of an R0 increase. The higher the R0, the steeper and higher the peaks.
Both countries were among the most vaccinated places on earth with strong recent boosters BEFORE Omicron hit. They both had the highest infection rate in the world. Look at this graph comparing the US, Denmark, and Israel for cases. Right before the outbreak both Israel and Denmark had twice the booster coverage as the US. So Israel and Denmark should have the lowest R0 of any nation on earth, not the highest.
So they lied about R0. It amplified R0.
The height of these peaks is consistent with an R0 increase of over 2X.
There are many other studies confirming effects that increase R0 including the Cleveland Clinic (CC) study and the second CC study. There were 7 other studies which found the same effect as the first 2 CC studies: here, here, here, here, here, here, here.the recent confirmation in Japan finding the same thing, and various surveys.
New Japan study confirmed the CC results that more vaccines→more cases: “The odds of contracting COVID-19 increased with the number of vaccine doses: one to two doses (OR: 1.63, 95% CI: 1.08-2.46, p = 0.020), three to four doses (OR: 2.04, 95% CI: 1.35-3.08, p = 0.001), and five to seven doses (OR: 2.21, 95% CI: 1.07-4.56, p = 0.033).” This is consistent with Table 2 in the CC study.
And there are four different surveys showing in the real world, the vaccinated are much more likely to be infected. I couldn’t find any large company where the unvaccinated were out sick more than the vaxxed.
When the vaccine makes you more likely to be infected, R0 and Rt (the R during a wave) go up.
IFR
The most definitive data we have on IFR (infection fatality rate) is from the 15,366 US nursing homes which have reported to CMS on a weekly basis COVID cases and COVID deaths since mid-2020.
There is a reason that they never analyze this data. It’s career suicide for any epidemiologist. Can you guess why? Y
eah, that’s right. It’s because it shows the vaccines more than doubled the CFR (the case fatality rate which is an almost perfect estimate of IFR) shortly after the vaccines were given for a limited period of time (OR 2.1, CI 1.9-2.3).
Nursing home data is dispositive because 80% of the people impacted by COVID were elderly and nursing homes are closed environments where the same people can be followed longitudinally and everyone with symptoms will get tested. There is no place to hide in a nursing home. They are required to report their stats weekly to CMS. And 15,366 is a big number so the Central Limit Theorem applies (i.e., the law of large numbers) which means the data can be noisy and we’ll still find the signal.
I include a list of the 9 positive and negative control conditions that this data meets that confirm the accuracy of the data (the “Pos neg controls” sheet).
There is no better data source for what happened to the elderly in the US after the vaccines rolled out. I don’t know of any data source that is more dispositive on the issue than this one.
As far as confirmation, my earlier article on Santa Clara nursing homes (LTCFs) confirmed the effect (OR 2.6, CI 2.1-3.1) which means the CI’s overlapped. The best estimate (2.1) was inside the overlap of the CIs (2.1-2.3) of the two studies.
One of my favorite takedown articles is this research letter by Vinay Prasad which pointed out that a study showing the vaccinated had lower mortality simply forgot to point out that it happened during non-COVID periods as well.
In one of the most important revelations of the pandemic, Høeg et al. (2024) pointed out that in Arbel, 2021, the non-COVID mortality (NCACM) differences more than completely accounted for the 94.6% lower mortality benefit claimed in the study, i.e., the vaccine didn’t reduce mortality at all; it was all a mirage.
In their reply, Arbel et al. acknowledged the failure, and then tried unsuccessfully to rescue their result with a ridiculous new analysis.
I spoke at length with one of the authors (Ram Duriseti) and he pointed out that a good way to tell it was ridiculous is to look in the table of mortality risks that the authors provided in their reply. The table shows that socioeconomic status has NO effect on death and that obesity is likely helpful to staying alive. And having a transient ischemic attack will improve your odds of living! You do trust the science don’t you?? 🙂
An organization in Israel sued Clalit Health Services to release the data used by Arbel, but they lost. So Arbel’s methods and data remain secret.
The Høeg authors are expecting their reply to be published in a month.
The nail in the coffin
Check out this post by Spiro Pantazatos. R2 is over .71 here and his new model is higher at .75. The positive coefficient means vaccines have increased deaths.
I’m not aware of a multiple regression with a higher R2 showing the opposite.
This is the final nail in the coffin for the people who claim vaccines didn’t increase deaths.
Is there evidence showing both R0 and IFR were lowered?
I’m not aware of any that is of equal or higher quality showing the reverse. Are you?
Summary
The COVID vaccines made things worse. It more than doubled the R0 and IFR (both temporarily before the “benefit” wore off).
If you can find a hole in any of these arguments, or identify data that is opposite and more dispositive, I’m all ears. I’ve got $1M riding on the outcome (we’re halfway through the arguments and will finish in around 3 weeks).
Tonight on VSRF LIVE, we dive deep into the major legal victories that are reshaping the landscape of COVID-19 policies and vaccine accountability across…
