Statistics

Vex-Caused Deaths In The UK

Anon sends us to the UK’s vex and no vex death data, which in the version I’m using was last updated in May. I’m using Table 2 from that report.

They calculate “Mortality Rate per 100,000 person-years” for various age groups and vex statuses, for all-cause death, coronadoom deaths, and non-doom deaths. They have the absolute death numbers, but they don’t have the absolute denominators (number of people in each group), so we’ll have to trust their person-year rate to make comparisons. They also give uncertainties in these rates, which adds to the confusion about their calculation. But we’re stuck with it.

Here’s the conclusion, which I give up front knowing many will skip the details. I also repeat it below:

The story roughly seems to be this: Old people died of the coronadoom 1,000 times faster than young. The doom pegged many unvexxed folks at the beginning, regardless of age, but the unvexxed survivors did okay after that, and are now doing the best or are close to the best in overall death from any cause, or even death from the doom itself.

The vex had some positive effect, but its power waned quickly, even with boosters. And it sure does look like the vex weakened a lot of people so that they died early. They might not have died of the vex per se, but something happened soon after the shots and people succumbed to a range of causes. At wicked high rates.

Let’s start with doom death rates for various ages and vex statuses.

Red is unvexxed. Greens are one dose, blues two, and yellows three+.

Be careful here. The y-axes changes a ton between age groups: there’s a 1,000 times difference.

There is also a timing artifact, or three. One has to start with no doses before having one dose before having a second, and so on. So the second and third+ dose lines don’t start right away. Recall the big vex push started in the late winter and spring of 2021.

The next artifact is the vex trend, which is related. Some didn’t get their first dose until late, and then, of course, they “graduate out” of the unvexxed group.

The last, slightest, effect is that some people at the top of the age groups age out into the next higher group at 2022.

Which brings us to the survivor effect, which is large and important. Gaze at the 90+ group. Many unvexxed deaths in January and February 2021, and a bit into March. But after that, the unvexxed death rate is not much worse, or even better, then the first or second dose groups.

The boosters came along in October 2021, at which point the death rates for these folks was again lower. But, as you can see, by May 2022, the death rates are converging. The vex is wearing off, the virus is changing, and we must deal with the survivor effect.

Many of the weakest in the 90+ who were unvexxed crapped out right away. Leaving the strongest. Which the doom could not kill, vexxine be damned. Likely often because of acquired natural immunity, which Experts in 2021 suddenly and shockingly said was not important. Then, suddenly again, but not shockingly, they now again admit is import.

Experts are amazing in that way.

Now don’t forget: most in the unvexxed group starting in 2021 had no choice but to be unvexxed. They couldn’t get it, or get it in time. So the initial months of 2021 is not a great time to test for vexxine efficacy.

Once everybody could get it—and this applies to everybody 70+—the vex doesn’t have great stats. Check out that green line for 80-89 year olds in summer and fall 2021. People crapped out from the doom within three weeks of getting their first shot? Interesting!

The 18-39 group is highly variable since the number of deaths are low. More about this group below. Contrast them with the 90+ group: many deaths there, and so lower variability.

Now let’s look at the same picture, but for non-doom deaths:

Notice first the y-axes, and how much (naturally) larger they are than in the first plot. We’ll put them side by side below.

Let’s start in the youngest cohort. The red line is the same: unvexxed. They did better than the vexxed a lot of time, yes? What’s up with that dark green line, the First dose, at least 21 days ago? What was killing them? It wasn’t the doom. And what was killing the folks in the light green line, which is the First does under 21 days?

Any guesses?

Then came the yellow lines, the booster lines. They, too, had higher rates of non-doom deaths than the unvexxed, starting around October 2021.

Well, there is still that higher variability because of low numbers, so we have to be cautious. Let’s look at older groups.

Everywhere at around February and March 2021, the unvexxed had higher death rates of non-doom deaths than the vexxed of any stripe. For those 50+ anyway. Were these extra deaths doom deaths, in the sense the doom contributed to the deaths but wasn’t listed as the primary cause? Was it the non-vex cures of the vex? Such as cramming tubes down the throats of infected people? The unvexxed got the doom, maybe, were sometimes weakened and succumbed to other maladies.

So this appears to be another survivor effect.

The deadliest group were those after three weeks of their first shot, for everybody 40 and older, starting in summer 2021.

It wasn’t the doom killing these people. It must have been something else. What could it be?

Caution is warranted. These sad folks did have a higher death rate, but the numbers still aren’t huge. On the other hand, the number of people in the unvexxed group (alive or dead) started large, and became smaller fairly rapidly, then tailed off to a plateau of those determined to avoid the vex.

It is also fairly clear that the unvexxed are surviving at higher rates as time continues. And that it’s the group to be in for the best rates, often. Until the boosters came along. Then those rates diminished, to tie with unvexxed.

Here are all deaths; i.e., rates of death from all causes, doom or otherwise:

For those 40, or really 50, and up, to be unvexxed initially was riskiest. Then the unvexxed either died, survived the doom or didn’t get it, or became vexxed. Those who remain unvexxed did fine, and appear on the way to be doing best, if they are not already the best.

There’s that big peak of deaths after the first dose again. People there died at spectacular rates. Ain’t that curious?

The rate was even more spectacular for those with brand new first doses at age 80 and above, starting in 2022. Did they change the vex type? Or change the vex itself? What killed these people?

These were elderly who waited until 2022 to get their first shot. Then were talked into somehow and…crapped out. Maybe they were on their way out anyway and got the shot at the behest of their doctors? The shot weakened their immune….well, best not to finish the sentence and stay on the bright side of censorship.

Here’s another way to look at the data. This shows just the First dose, at least 21 days ago and the unvexxed, for both non-doom and doom deaths.

The darker colors are non-doom deaths; lighter are doom deaths.

We’re not really looking at vex efficacy here, since this is only one shot. But it’s interesting how small an effect the one shot had. Considering, of course, the survivor effect, too. Again, these are rates and not body counts, so just because the dark green is huge doesn’t mean it always had the highest body count.

But, dude. Dat’s a big-a line.

Here’s the same thing, but for the second dose at 21+ days.

You have the idea by now. And don’t forget we have a survivor effect there, too. If the first shot, uh, was implicated in certain crappings out, then there were fewer weaker people available to crap out from the second shot, and so on.

Last word of caution: there is uncertainty in all these numbers, which we’re waving aside, because these are calculated values. It would be far, far better for the UK, and our Expert-led CDC, to release patient-level data. Which, for some odd reason, they don’t.

The story roughly seems to be this: Old people died of the coronadoom 1,000 times faster than young. The doom pegged many unvexxed folks at the beginning, regardless of age, but the unvexxed survivors did okay after that, and are now doing the best or are close to the best in overall death from any cause, or even death from the doom itself.

The vex had some positive effect, but its power waned quickly, even with boosters. And it sure does look like the vex weakened a lot of people so that they died early. They might not have died of the vex per se, but something happened soon after the shots and people succumbed to a range of causes. At wicked high rates.

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Categories: Statistics

14 replies »

  1. All of this data has an underlying assumption that the deaths were categorized correctly. For example, correctly identifying vexxed, unvexxed and “status uncertain”. And then this same categorization would need to be accurate for the first injection, the second and the booster(s) and the times elapsed. Not a simple task to operate nationally.

    Nonetheless, this assumption has been challenged, certainly in the United States, but also credibly challenged in the UK for data up to at least May 2021. I personally believe that this assumption is not valid – that the signals are being masked by very poor and inadequate data collection practices.

    Then you have persons like Dr McCairn finding no phosphorous in samples of Moderna in Japan under rigorous laboratory analysis; indicating no mRNA is present in the vaccines. So we then have to challenge the data in total if this is true.

    Patient data will never be forthcoming, at least not until it has been “sanitized”.

    Its all about masking adverse event signals, in my view. Even with all these flaws; skewed towards concealment or manipulation of the data, Brigg’s analysis shows the potential of very serious adverse event signals and deserves a big Thank You!

  2. Here in Alberta, 2/3’s of Covid deaths occurred early on in nursing homes (pre-covid vaccine), due to inhumane conditions from staff shortages from fear of dying, inhumane policies by incompetent administrators, and an above average deadly respiratory virus.

    Perhaps 1/4 to 1/5 deaths were called ‘Covid deaths in the unvaccinated’ because they occurred in street derelicts on their way out who had not received Covid vaccines, let alone any healthcare, in decades, and were filling the 2 or 3 ICU beds which would have otherwise remained empty at that time.

    These 2 patient populations dwarfed any other difference in vaccinated vs unvaccinated, preventing any meaningful conclusion from overall population comparisons.

  3. I did a different exercise, some months ago. I added up all vaccinates deaths from Table 2, disregarding doses and <14 days etc. I adjusted the groups as if the had the same size, to make them comparable. I did NOT mix up the age categories, because of the propbels with population sizes.
    Line graphs:
    https://virusvaria.nl/veilig-en-werkzaam-sterfte-per-100-000-naar-leeftijd-en-vaccinatiestatus-in-england-uk/
    Bar graphs:
    https://virusvaria.nl/uk-mortality-in-staafgrafieken-vaccinated-versus-unvaccinated-januari-2021-maart-2022/

  4. @Hagfish: Those types of clots are reportedly a result of amyloids; very unusual and made of the same stuff (prions) that can attack the heart, nervous system and brain. Prionopathies include things like Parkinsons, Alzheimers, CJD, etc if they manage to cross the blood brain barrier. Early signs in the general population will be such things as “impulse control disorders”.

    “Impulse control disorders (ICDs) are a class of psychiatric disorders characterized by difficulties controlling aggressive or antisocial impulses. Because they can involve physical violence, theft, or destruction of property, the disorders often have harmful effects on both the person with the disorder and on others around them.”

    https://www.psychologytoday.com/us/basics/impulse-control-disorders

  5. There’s a complicating factor in UK.

    In the early days of coronadoom, the first jab that became available and was used was the AstroZeneca pseudo-vaccine. This is made from a benign (to humans) coronavirus that is engineered to look like SARS-Cov2. The elderly and those deemed at risk through some pre-existing condition(s) received only this.

    As more of the population became vexxed, jabs were switched to the experimental mRNA drugs. The younger cohorts received only these latter vexxines. Only the mRNA Jabs have been used on everybody for quite some time now.
    I’m *almost* certain that everybody’s booster jabs were exclusively mRNA. (I’m old and accepted the AZ jab. I was thus amongst the first to be offered mRNA boosters which I refused.)

    Not sure of exactly when AZ went out of use, or what the age cutoff that marked ‘younger’ was.

  6. There’s a great blog by a UK NHS data scientist about these topics, but I lost the link when I got a new work computer 🙁

    If I recall correctly, he thinks there is a issue when comparing the cohorts (unvaccinated vice vaccinated); a simpson’s paradox where the differences in outcomes go away when you control for fitness, past health issues, smoking, etc… Basically, the vaccinated group is the healthiest cohort (and least likely to need extra protection from Covid); whereas the unvaccinated is the most vulnerable group with risk associated with taking any kind of vaccination that may affect their immune system.

    If this is the case, then doesn’t the slight protection in the vaccinated group go away…?

    I’ve read something similar years ago about these kinds of differences in cohorts and the flu shots.

  7. @Solent: Again the AZ vaccine variability was huge, in terms of composition.

    In just three batches tested in Germany the human protein (from kidney cell lines) varied from 45 to 71 pct and the nCOV-19 (active agent) varied from 29 to 55 pct.

    https://www.chemistryworld.com/news/protein-impurities-found-in-astrazenecas-covid-19-vaccine-stir-debate/4013844.article

    The statistical inference being, from these very limited data points, that the expected range of the true population would likely be much larger. Compositional variation between batches by a factor of 2 is a reasonable expectation, in my view. Meaning, on the extreme, it is theoretically possible for one cohort to have gotten 4 times as much nCOV-19 than another. In practice, it would not be unreasonable to find a factor of 3 or more in the extreme.

    So, even accepting the premise that the nCOV-19 ingredient is highly effective, by the time mass manufacturing variability is considered, it becomes a bit of a “crap shoot” (in gambling terminology) at the individual, clinical level, simply due to manufacturing variability.

    Additionally, there is emerging evidence that certain mRNA vaccine manufacturers are producing batches that do not contain phosphorus and therefore do not contain mRNA. Why this is happening is another matter.

    Then as you wrote, the AZ vaccines were discontinued in the UK and boosters on offer are either Pfizer or Moderna – further confusing any signals in the UK.

    Combined with the above variables are woeful data collection and classification practices in both the UK and the USA, from the outset to today. Allegedly the CDC is currently manipulating data with respect to cancer deaths, for example:

    https://threadreaderapp.com/thread/1554936515544973314.html

    Where does this lead us? The efficacy and adverse event data is extremely noisy, unreliable and dirty and in my opinion, manipulated. Essentially useless. Any expert who claims, from the data, that this “has been a great success”, or that “so many more would have died without” is simply not credible (to put it mildly).

    All that can be done now, as Prof Briggs has clearly illustrated, is monitor the excess deaths with time.

  8. The shrill, childish name-calling is what you do when you want to drive off any readers with the willingness or the intellectual capacity to question anything you say.

    If you can’t figure out the implications for yourself, there’s no sense in explaining. You might get it. But how many of your readers will?

  9. @briggs: The following paper, which uses data that seems to have good statistical power, concludes that the flue vaccines are useless, ie, have no benefit.

    https://www.acpjournals.org/doi/10.7326/M19-3075
    ———————
    The Effect of Influenza Vaccination for the Elderly on Hospitalization and Mortality
    An Observational Study With a Regression Discontinuity Design

    Results:
    The data included 170 million episodes of care and 7.6 million deaths. Turning 65 was associated with a statistically and clinically significant increase in rate of seasonal influenza vaccination. However, no evidence indicated that vaccination reduced hospitalizations or mortality among elderly persons. The estimates were precise enough to rule out results from many previous studies.
    —————

    What is your take?

  10. Dr. John Campbell, a UK doctor, recently discussed the excess death problem. He pointed out how with excess COVID-19 deaths, the death rate average has risen and the excess deaths we are seeing now should be much lower due to that. He isn’t saying exactly what he thinks is causing it (as YouTube might ban him), but is clearly saying that the authorities should be looking into the cause. Too many young people dying these days.

    https://youtu.be/5wLu98NygrA

  11. The link between cigarette smoking and cancer is pretty shaky from a truly objective scientific perspective, the man who invented the statistical techniques relied on by epidemiology said so himself (RA Fisher). Ultimately all “scientific” decisions and paradigms are political or at the very best subjective. There is no such thing as scientific certainty. In the fundamental analysis science is a description that tells us nothing about meaning. Once government gave up on religion they had to appropriate science as the source of authority, which means science as practiced nowadays is inherently corrupt. You will not be able to “prove” anything using science or science adjacent methods that ruling authorities don’t want you to prove. The battle is spiritual not material in a very real sense.

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