VA Data Shows Covid Boosters Increased Risk of Hospitalization and Flu Shots Don’t Work

Executive summary

In my earlier article, VA study published in JAMA shows that COVID *and* flu shots don’t reduce your risk of hospitalization, I showed how you could analyze the VA hospitalization data for COVID vs. flu, and by using each disease as a control for the other disease, show that neither vaccine worked. It uses a very simple principle: if a vaccine works, the vaccinated should be hospitalized at a lower rate than the rate they’d be hospitalized for an unrelated respiratory virus.

Today, I did a Fisher exact test on the propensity-score adjusted data in the Xie paper and the results were revealing:

If you got just one COVID shot, there was a 10% reduction in hospitalization
If you got 2 COVID shots, there was no additional benefit
If you got the booster, your benefit diminished to just a 3% reduction in hospitalization risk so it reversed the benefit you got earlier!
If you got a flu shot, there was basically no benefit whatsoever in terms of hospitalization reduction (a 1.8% benefit)
None of the above results were statistically significant.

Bottom line: The first shot might have had a narrow benefit, but the second and third shots can’t be justified at all. We shouldn’t be giving these shots unless the benefits outweigh the risks. Previous articles have pointed out that the shots increased infection risk and increased the case fatality rate, and that’s before we even consider the vaccine-caused increase in non-COVID all-cause mortality.

So this new information doesn’t change anything: you shouldn’t get the shots at all.

Here are the calculations

These calculations use the numbers in the Xie paper in the Table (propensity matched columns):

Statistics for dose 1 only = 421 103 8575 2300 8996 2403 11399
One-sided p-value 0.2237717093928315
Two-sided p-value 0.44280492830474005
Max likelihood estimate of the Odds ratio= 1.0963145028647212
Traditional OR= 1.0963231339692603
95% Confidence Interval(low=0.8772108708050249, high=1.3803252322420094)

Statistics for primary series benefit = 1985 492 7011 1911 8996 2403 11399
One-sided p-value 0.04870272401590869
Two-sided p-value 0.09486104178727314
Max likelihood estimate of the Odds ratio= 1.0996957927882844
Traditional OR= 1.0997048192561514
95% Confidence Interval(low=0.9832366472918711, high=1.2313456876988418)

Statistics for BOOSTER benefit = 4986 1311 4010 1092 8996 2403 11399
One-sided p-value 0.23051618753054964
Two-sided p-value 0.459976483563565
Max likelihood estimate of the Odds ratio= 1.0356821969194545
Traditional OR= 1.0356853860771413
95% Confidence Interval(low=0.9450890735997887, high=1.1348349873690617)

Statistics for INFLUENZA vaccine = 5743 1524 3253 879 8996 2403 11399
One-sided p-value 0.3607081043412625
Two-sided p-value 0.7024320102170791
Max likelihood estimate of the Odds ratio= 1.0182583278503825
Traditional OR= 1.0182599466028934
95% Confidence Interval(low=0.9261636742375395, high=1.1191195195638168)

Summary

I’ve been doing this for more than 3 years now, and a slightly reduced hospitalization risk after the first shot is the first and only benefit from vaccination that I’ve seen that might be credible. However, part of the benefit may be due to selection bias because if you got the first shots and didn’t die from it, you are less likely to be hospitalized from COVID because you have a stronger immune system.

The VA data shows additional COVID shots are not beneficial.

The data again confirms that the influenza vaccine doesn’t work at all.

Finally, even if the small hospitalization benefit of the first COVID shot was statistically significant, the effect size is too small to be meaningful, especially in light of the fact that the COVID CFR which didn’t drop after the vaccine rolled out and that one in 6 people reported COVID vaccine adverse events in a recent public poll in Germany.

Bottom line: The data keeps telling us that the COVID shots are nonsensical and should be immediately halted, but health authorities aren’t paying attention to the data.

Reprinted with permission from Steve Kirsch’s newsletter.

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