It's amazing nobody noticed. It took just 2.7 seconds for Oracle to run the query that shows this. You can replicate my work yourself on the data I published last year.

Executive summary

If you were age 65-69 and you were one of the 4M people who opted to get one or more jabs in New Zealand, on average, your mortality over a 1 year period from when you got your first shot was elevated by at least 27% from the official baseline mortality rates published by the New Zealand authorities for 2021 as well as 2022.

Every single 5 year age range from 45 to 84 was elevated over baseline. The data was too noisy for lower age ranges (fewer than 59 deaths).

Apparently, Health New Zealand doesn’t care how many people they are killing. They won’t take the 2 seconds to run the query.

As far as I can tell from talking to Barry Young, the former Oracle DBA at Health New Zealand, their epidemiologists have never asked to look at the safety data and have no interest in learning the truth.

That’s their idea of protecting the public.

So the killing will continue.

The SQL query

Simply import the .csv file in the record-level-data directory into Oracle. During import, rename the columns to match the column names to match the query below. Make sure that the DOD field is imported as a DATE. Skip importing the vaccine type.

The query below basically computes how many people between the ages of 65 and 69 got doses 1 - 4 and how many of those people died within 365 days of their shot. It also computes the % died by dividing the two values. It is brain dead simple.

CREATE TABLE analysis_65_69_365_day_obfuscated AS
SELECT dose_number,
       num_vaccinated,
       num_dead,
       ROUND((SELECT num_dead / num_vaccinated * 100 FROM dual), 2) AS percent_died
FROM (
    SELECT dose_number,
           COUNT(*) AS num_vaccinated,
           COUNT(CASE WHEN dod <= vax_date + 365 THEN 1 END) AS num_dead
    FROM obfuscated
    WHERE TRUNC(MONTHS_BETWEEN(vax_date, dob) / 12) BETWEEN 65 AND 69
        AND trunc(vax_date)<'5-oct-2022' -- so that person has time to die before database runs out on oct 7, 2023
    GROUP BY dose_number
    HAVING dose_number BETWEEN 1 AND 4  -- Limit doses to 1 through 4
    );

Results (in just 2.7 seconds)

Results on running the query above on the obfuscated dataset

The results on the original dataset (without the obfuscations) have slightly different counts, but exactly the same percentages which is a great validation that the obfuscation had minimal impact on the statistical integrity.

Mortality rates for 65-69 year olds

The official mortality rates for 65 to 69 year olds is available from Infoshare, using the Group: Death rates DMM selection.

For 2020, the rate was 0.975% per annum.
For 2021, the rate was 0.986% per annum.
For 2022, the rate was 1.055% per annum.

Shot #1 was given in September 2021, suggesting that the baseline mortality rate should be between those two rates. Therefore, a conservative estimate is to use the higher number as baseline mortality expected.

So we have 1.34/1.055 = 1.27 which means our Dose 1 people died at more than 27% above what was expected.

That is a disaster.

But the reasons the rates are higher is presumably due the vaccine so the baseline rate is closer to .975% and even lower than that since healthier people get vaccinated than the overall population so baseline is probably around .9 and we observed 1.34% which is a 48% increase.

The gaslighting attempts

Defenders of the “safe and effective” vaccine will go into overdrive on this.

Their claims will be:

It was a skewed subset of the 65-69 year-olds that opted for the shots; the healthy people avoided getting vaccinated. That’s why the mortality rate is so high.
Look! The vaccine worked!!!! By the time people got the fourth shot, they were able to reduce their all-cause mortality by nearly 40% from baseline! The vaccine is a miracle! Everyone should get it!

My response

Both of these statements are false.

The people who opt to get any vaccine are health seeking and have, in general, lower mortality than the general population. This is known as the “healthy vaccinee effect.”
There is very credible evidence published in JAMA that the vaccine offers no mortality benefit from all-causes or COVID. Dose 4 was lower simply because the cohort itself that opted for shot #4 had a lower baseline mortality since they survived all three shots already and decided to go back for more punishment.
Can I see your correct analysis of the data using the same metrics?

Here’s the Bard explanation of the size of the healthy vaccinee effect which reduces all-cause mortality on those who decide to get vaccinated by 5% to 30% or more.

So our vaccinees should have had lower mortality on Dose 1 than baseline, not 27% higher mortality.

They cannot make their argument work and can’t support it with data.

If the 4M people in NZ who took the shot were unhealthier than average to start with (they would claim since the government mandated it, the healthy vaccinee effect was neutralized), then they cannot explain how their baseline mortality miraculously improved by shot #4 to be 20% below baseline. For more details on this, see the exploration of mortality rate distributions.xlsx spreadsheet in the analysis directory of the repository.

Bottom line is this is like whack-a-mole for epidemiologists. They have to explain both numbers. If they explain one number, they can’t explain how to get to the second number.

Explaining the numbers

The jabs are causing a huge amount of harm. People are seeing it and some of the stories are insane. For example this anecdote is mind blowing:

If the vaccine is saving lives, anecdotes like that one should be impossible to find.

The most likely explanation for the query results are:

The death rates after vaccination diverge from background death rates. If you got the vaccine, your mortality increases over time.
We don’t really know what the baseline mortality rate of the 4M people who opted for the vaccine were, but it’s safe to say that the healthy vaccine effect is still at play and that the cohort getting the vaccine was probably lower than baseline mortality (under 1%) since healthier people opt for vaccination. So the 27% mortality over the year after the shot is problematic especially since it’s compared with the 2022 baseline. To get a 27% differential from baseline is really hard considering 80% of New Zealanders took the first shot. So you can’t argue it was “the sickest.” It was nearly everyone healthy enough to get the shot.

Summary

The NZ data was released almost a year ago on my Substack. It’s record-level data.

How is it that not a single epidemiologist in the world has analyzed the data and reported how it shows the vaccine is beneficial?

How is it that Te Whatu Ora isn’t releasing the correct analysis of the data proving that I am mischaracterizing it?

The answer is obvious: it’s because they can’t.

But it would be a hoot if they tried that. They would be torn to shreds. This is why they don’t do it.

Not even my good buddy Sean Plunket, the New Zealand talk show host that never lets you get a word in edgewise, has proffered his own analysis of the data.

I’d be happy to debate any published epidemiologist with an h-index equal to or greater than my own who claims that the NZ data proves that COVID vaccines reduce mortality.

Any takers?

I didn’t think so.

https://kirschsubstack.com/p/new-zealand-data-leaked-by-barry?publication_id=548354&post_id=141115566&isFreemail=true&r=16ettj&triedRedirect=true