If the COVID vaccine benefit was so large, why can't we detect it in the Czech record level data?

The % rise in all-cause mortality for vaccinated vs unvaccinated during COVID waves were comparable. In other words, the vaccines didn't work.

Executive summary

In a fixed-cohort analysis anchored to ISO week 2021-24 (baseline window 2021-24 to 2021-40), vaccinated all-cause mortality rose from 23.297 to 31.190 deaths per 100,000 person-weeks (RR 1.3388, +33.9%), while unvaccinated mortality rose from 13.017 to 17.625 (RR 1.3541, +35.4%). The unvaccinated-to-vaccinated ratio of rate ratios was 1.011 (95% interval 0.985 to 1.039), with male (1.003) and female (1.021) values also close to parity. The two groups did not have equal baseline risk: in many birth-year bands, unvaccinated baseline ACM rates were more than twice vaccinated rates. Nonetheless, the wave-period rise, expressed relative to each cohort’s own baseline, remained near parity, so a stable vaccinated all-cause mortality advantage is not observed in this fixed-cohort specification. This is an observational comparison and should not be interpreted as a causal effect estimate.

In other words, it didn’t work.

Background

Reliable observational studies comparing vaccinated to unvaccinated are hard to do for a myriad of reasons including:

1. massive health difference between people who opt to get the vaccine vs. those who don’t

2. large differences in testing requirements (required vs. optional)

3. suppression of symptoms by those who opted for the vaccine leading to under diagnosis.

If you look at COVID mortality, it looks like being vaccinated was hugely beneficial. But was that due to these biases?

If we want to know the truth about what happened (instead of feeding our own belief systems), it’s important to look at measurements, such as relative all-cause mortality increases during COVID waves, that aren’t subject to these biases. Other good measurements are following a population (vaccinated AND unvaccinated) longitudinally over time to see what happens (that neutralizes selection biases).

When we do that, we find there wasn’t a clear all-cause mortality benefit at all from those who opted for the vaccine.

In short, we have a vaccine where the best pieces of evidence we have available show significant harm and little to no benefit.

Here are a few examples:

1. No COVID death benefit: The Medicare US Nursing home data shows the case fatality rate (CFR) remained flat during alpha, even though nursing homes were the first to get the shots. This was literally the “poster child” case study and the CFR didn’t budge directionally. The Arbel study done in Israel claiming the boosters had a 90% reduction in death was later found to be caused by the healthy vaccine effect which nullified the finding (Hoeg).

2. Increased risk of all-cause death: The Florida brand comparison study by Levi and Ladapo showed even when you closely matched both Pfizer and Moderna groups, those with a Pfizer vaccine had 37% higher non-COVID all cause mortality which is highly suggestive of huge vaccine harm.

3. Increased risk of cases: Multiple Cleveland Clinic studies pointed out more vaccines—>greater risk of infection. And Israel is the stunning example of that with the highest cases of Delta and Omicron in the world, over 10x higher than their alpha infections which was confirmed by careful wastewater measurements.

4. No effect worldwide of the vaccine: No “knee” in the cumulative COVID death curve as the vaccine rolled out worldwide.

   

5. And in highly vaccinated Japan, instead of COVID cumulative death curves “flatlining”, they did the opposite and got steeper over time! Whoops! How can THAT happen?!?

   

6. And the Mostert study showed excess deaths kept rising worldwide instead of turning around

   

7. And now the Czech data shows no benefit as well!

   Czech Republic record level data

   This table reports the Czech 2021-24 fixed-cohort all-cause mortality check used above. Rates are all-cause deaths per 100,000 person-weeks. The baseline window is ISO weeks 2021-24 to 2021-40; the wave window is 2021-41 to 2022-17. RoRR is (wave / baseline in unvaccinated) / (wave / baseline in vaccinated). A RoRR above 1.0 means the unvaccinated cohort had the larger wave-to-baseline mortality increase; here, the headline intervals include 1.0, so this is not a precise causal effect estimate. This is a Czech record-level stress check, not a U.S. national causal estimator.

The all-sex birth-year rows below show why the headline result is not simply an aggregate-composition artifact. Unvaccinated baseline mortality is often much higher than vaccinated baseline mortality within the same birth-year band, but the wave-versus-baseline rate-ratio contrast remains mixed rather than showing a stable vaccinated advantage. Birth-year intervals are omitted below for readability; sparse younger cells should be treated as descriptive and high-variance.

Summary

The Czech Republic record level data is a stunning confirmation of “no effect” for the COVID shots. All you had to do is ignore the “label” of a COVID death and simply look at mortality during non-COVID period vs. COVID periods for the vaccinated vs. unvaccinated.

I’m not aware of any other publicly available record level dataset that can be used for this test. So it remains the only and the best. I’m not aware of any dataset that would be more dispositive showing a different result.

If the COVID vaccine was so beneficial, why do the authorities need to keep the data hidden from view? Baffling isn’t it???

The bottom line is this: the best quality datasets for answering questions of benefit vs. harm all say the same thing for the COVID vaccines: harms >> benefits.