In what I rather euphemistically refer to as my “spare” time these days, I have been noodling around, out of interest, on Excess Mortality data. The inspiration for this came from a Twitter post shared with me by a friend, from user OutsideAllan, who put together a rather shocking series of heatmaps concerning excess mortality in the United Kingdom.

Intrigued by what I saw, my friend and I decided to try replicating his approach and creating our own heatmaps. It took a little while to figure out what he was doing, but we cracked it eventually.

The results are… horrifying. That is the only way I can describe it. They show a substantial, serious, and relentlessly upward-sloping trend in unexpected deaths among males aged 0-24 in England and Wales, and MUCH higher than expected deaths caused by heart disease, ischaemic heart disease, and cirrhosis of the liver (and other related diseases).

All I can say, looking at the charts and graphs I have put together, is… WTFH is going on?!?!?

Turning Up the Heat

The Twitter user who originally created the heatmaps that sparked my interest, did not provide his methodology for doing it, but it actually was not that hard to replicate. I figured out that, when he talked about “Non-COVID Excess Deaths”, he simply subtracted the deaths with COVID on the death certificate from the overall expected deaths, and then divided that number by the expected deaths to compute the Non-COVID Excess Mortality as a percentage figure.

It turns out he then applied some weights to the data, because it is all in weekly format – to get to monthly and annual series, you have to weight the total number of deaths in a week, by the percentage of the deaths in that particular month or year. Again, not hard to do.

It is not difficult to go from that point, to creating a heatmap. If you know what you are doing in Excel (or LibreOffice Calc), then it is a fairly straightforward exercise.

Because I am kind of a data nerd, that is precisely what I did.

The graphics below all use data from the UK Office of Health Improvement and Disparities, and you can find that exact data set right here – just click on the “Data download” link in the Power BI dashboard they have created. (Incidentally, the OHID has now ceased updating that dataset, as of Feb 20 2024 – I am guessing the Noticers did a little too much noticing, and the BritGov is now shutting down any further line of inquiry here.)

If you want to see how I generated the analytics below, just click on the link below to download the ODS file – you can open it in LibreOffice and Excel. I have made NO changes whatsoever to the core data – if you do not believe me, just download the OHID file linked above, and compare the columns line-by-line.

I make no representations whatsoever for the UK government’s approach to modelling Excess Deaths. They use a highly complex regression-based mathematical approach (see down below) to calculate excess mortality, and I have no view whatsoever on whether it is accurate or not. Nor do I particularly care.

With that out of the way, let us get on to analysing the actual data.

Non-COVID Excess Mortality by Age and Sex

The first heatmap shows you Non-COVID Excess Mortality by Age and Sex in England and Wales, between Mar 27 2020, and Dec 31 2023. As you can see, Ye Olde Phartes died off in droves from the Coof early on, but deaths from all other causes in those age groups were actually quite benign.

But then… as we go past 2021, something very strange, and very sinister, starts to happen.

Young people start dying off at MUCH higher than expected rates, and the Kung Flu simply cannot explain this. And NCEM is high even among the oldies (click on any of these images to biggify).

We see the same trend holding if we switch to an annualised view:

The trend is very clear. Something very strange is happening to young males, between the ages of 0 and 24 years, and also to men in the 50-64 age bracket. Things are not looking that much better for young women, but for men, there is some serious weirdness happening.

Non-COVID Excess Mortality by Cause of Death

It is not possible to get a joint view of excess mortality by age, sex, AND cause of death, from the OHID dataset. The tables just don’t join up that way in the cuts they give us – though I suspect they probably do, within their own databases. But what we DO have, tells us quite a lot.

Take a look at what happens when we apply the exact same methodology to figuring out NCEM by cause of death:

Notice anything weird? Like how deaths from heart failure and cirrhosis/liver disease are OFF THE FREAKIN’ SCALE from 2022 onwards?

And do you notice also how non-COVID cancer deaths are actually fairly benign and stable? Or how most of the “old people diseases”, like Alzheimer’s and Parkinson’s, are generally looking pretty decent? Or how deaths from respiratory diseases (aka pneumonia and flu) are way down nowadays?

Everything we are seeing from the data tell us something very weird is happening with heart failure, circulatory diseases, cirrhosis, and diseases of various vital cardiothoracic organs. The same things hold in the annualised view as well:

Deaths Over Time

We can go well beyond just the heatmaps I have created above. Again, because I am a data nerd who spends FAR too much time around data visualisation software, and I have a serious case of “Rubik’s Complex” (that is to say, I have to solve the problem – comes from being a mathematician by training), I had a go at plugging all of this stuff into a Power BI dashboard.

I cannot publish it, because I only have a free desktop download and not a full-banana license, but anyone who wants the actual PBIX file is welcome to shoot me an email, and I will be happy to send it over.

Take a look at the screenshot of time series data for men, aged 0-24, in England and Wales, using the same government data:

And now take a look at the same time-series data for heart failure ONLY:

To resort to my favourite Americanisms – this is queer as a three-dollar bill and more f***ed-up than a football bat.

Some Perspective

If you look at the UK Excess Mortality data, you will see that 10,320 MORE people died in 2023 of causes that have nothing to do with the Coof.

The official death toll from 9/11 stands at 2,977 (not including the 19 supposed hijackers).

So what we see in the data tell us that England and Wales, with a combined population of around 60 million or so, as of 2023, absorbed 3.47 9/11 attacks in the space of a single year.

Worse, in 2023 alone, 388 more males between 0 and 24 years of age died than expected. That is MORE than the total death toll of both Boeing 737 MAX 8 crashes (346 people in two crashes over 9 months).

Again, this is just England and Wales. I have no idea what the numbers are for the rest of the world – I have not put any effort into figuring it out. But I suspect that, if anyone did it, the numbers would be HORRIFIC.

A Very British Cop-Out

It is worth noting the British government has now significantly changed its excess deaths calculation methodology, because reasons, and the data reporting have therefore changed. They no longer maintain the old dataset, and now have new excess deaths data for 2023 onward. You can access their own Power BI dashboard using the link above.

All I can say to this is: sack up, bitches. You people forced the entire country into multiple lockdowns, the impacts of which no one really fully understands yet, but which we can conclusively agree did NOT work to prevent the spread of the Coof. And now you are ducking and diving responsibility for deaths well above historical norms, by redefining what “excess death” is, in the most convoluted and mathematical way possible.

Seriously, I have a background in fairly serious numerological nitwittery, and I find it difficult to understand what the hell they are doing with all those regressions. (OK, I exaggerate somewhat – at the simplest level, it is basically a quasi-Poisson generalised regression model that you could run yourself in R, if you had the raw data. But still, it is difficult to explain this in plain English.)

None of that changes the fact that weird shit is happening, which we simply cannot explain.

The Not-Vaxx as a Possible Cause

So, again, i ask:

WHAT THE HELL IS GOING ON WITH THESE DEATHS?!?!?!

I am not a doctor, so I am at a complete loss to explain any of this. My own theory – and it is of course only a theory – is that the not-vaxx is heavily involved in all of this. We cannot know for sure, because no one (to my knowledge) has done a serious, rigorous, proper longitudinal study that looks at people with at least one jab, versus purebloods (like me, and like most of you), and tracked their health over time.

That being said… we do have the results now of the world’s largest ever study on vaccinated people, across 99 million people and 10 countries, looking at the mRNA jabs as well as the adenovirus variants. The medical journal, Vaccine, published that study on Feb 12 2024.

If you try to read the abstract to that study, you will have absolutely no idea what the hell it says, because it is written in the most impenetrable medical gobbledegook imaginable. The authors of that study argue the jabs are quite safe, based on what they saw.

Of course, as Steve Kirsch notes, there is a lot about this study they are NOT telling you:

1. They looked at the medical records of 99,068,901 vaccinated individuals.
2. They compared observed vs. expected (“OE”) rates of “13 selected adverse events of special interest (AESI) across neurological, haematological, and cardiac outcomes.”
3. They only looked for 42 days after the shots since everyone knows you can’t get adverse events after 42 days (I’m being sarcastic).
4. They didn’t evaluate mortality due to the shot since everyone knows the vaccines are safe and didn’t kill anyone (I’m being sarcastic).
5. They found clearly increased risk of the various AESI, but the end conclusion is that the risks after COVID infection are far higher, so people should take the shots. This is unbelievable. I don’t know a single cardiologist whose business dropped after the COVID vaccines rolled out. Do you?
6. As usual, they aren’t allowed to share the data so you have to take their word for it.

It is also an observational study – the weakest kind of study of longitudinal data, because it relies so much on self-reporting and medical records.

And, as Dr. John Campbell explains, there are serious issues with the adverse events reporting systems in the West:

In spite of all those problems, this study is very revealing.

Let the Numbers Speak

None of you need to know where I personally stand on this stuff – as far as I am concerned, it is the single most dangerous, unethical, and evil medical experiment ever done in history, and I want no part of it.

But I am not the one who needs to speak here. The data need to speak for themselves.

So let us take a look at what the evidence actually says. You can find every single image I have shown below, in the original study, right here. I repeat, I am NOT making any of this up. It is straight from the study itself, and I have made no alterations whatsoever to the original images.

Not-Vaxx Neurological Complications

Here is a heatmap taken straight from within that study, which looks at the Observed-to-Expected incidence ratio of a particular Adverse Event of Special Interest (AESI), in the column headers, based on the number of doses (1st column) of one of three not-vaxxes (row labels). The not-vaxxes are the AstraZeneca/Oxford adenovirus-based jab, the Pfizer/BioNTech mRNA jab, and the Moderna mRNA jab.

In plain English, this table shows us much higher than expected rates of Guillain-Barre Syndrome from one dose of the AZO jab, and much higher than expected acute disseminated encephalomyelitis from one of the Moderna jab.

tl;dr version: your chances of getting a serious neurological disease spike significantly after your first dose of any of these not-vaxxes, but then seems to become fairly benign.

Not-Vaxx Impacts on Veins and Arteries

Let us now turn to adverse events resulting in thrombosis and embolisms – in plain English, the terms translate to “blood clots that could potentially kill you”.

The heatmap below – again, from the exact same study – shows statistically significant safety signals all over the place for blood clots, resulting from the adenovirus-based jab. The more of those jabs you get, the worse the risk gets of having a blood clot that could off you.

Again, keep in mind, this study has some serious limitations. Yet it paints a picture of danger that government authorities simply do not want to admit.

Not-Vaxx Impacts on the Heart

Here we get to the really juicy stuff. If we look at the risks of myocarditis and pericarditis – that is to say, inflammation of the heart muscle or the fibrous sac surrounding the heart, respectively – then they are just… shocking.

The Real Kicker

It is easier to look at all of that data in one single graphic, which is what Steve Kirsch did in his post on the subject, linked above. Take a look below:

Yeah. There you go. The risk of myocarditis, resulting in a potentially fatal heart attack, spiked up dramatically after 2 doses of the Moderna not-vaxx.

The risk of pericarditis, resulting in severe and sharp chest pain, and possibly an eventual heart attack, go up nearly SEVEN TIMES above what you would expect to see in healthy people after 3 doses of the AZO adenovirus-based shot.

As Mr. Kirsch points out, if the not-vaxxes were genuinely safe, they would be largely indistinguishable from a placebo. You would not expect to see such substantial probabilities of adverse events, resulting in so many different complications, from a truly safe and effective medical product.

Conclusion – We Need Answers

The data I have shown above, are ONLY for the UK. If you really want to get deep in the weeds, there is an OECD dataset floating around out there, which shows excess mortality across all OECD nations. The problem is, it is not possible to perform the analysis I have done above at quite the same level, because the various countries report deaths differently. The US, for instance, reports Coof deaths only by age, not broken down by sex. Other countries report only aggregate Coof deaths, not broken down at all by age and sex.

And I have not found a consolidated dataset that looks at cause of death both with and without the Coof.

None of that changes the fact that excess mortality is high and persistent around the world, and particularly so in some countries with high rates of “Coofaccination”, as it were.

The world needs answers. Every single person who took these jabs is potentially at risk of a life-threatening adverse event – and given the BILLIONS of doses of this poison the governments forced us all to take, we have no idea just how bad the problem could be.

More than that – every individual who died from complications brought on by the not-vaxx had a family. They had parents, children, boyfriends, girlfriends, and dear friends who are now bereft of their company and warmth.

I do not want to watch any more videos or see any more pictures like these – regardless of whether they died from the not-vaxx:

These people – or at least their loved ones – deserve answers. Something is happening here which we cannot explain, because no one has joined up the various dots in a comprehensive and systematic fashion. I am well aware of a number of excellent points made by the likes of Dr. Peter McCullough, Dr. Pierre Kory, Dr. Robert Malone, and of course Steve Kirsch, to bring attention to what is happening, but we have seen no serious longitudinal medical study that really looks at the link between not-vaxxes and deaths in young people.

All we can say, based on the data, is that there is clearly a serious signal buried in a lot of noise. We need to amplify that signal and find out what is causing it – and then PUT A STOP TO IT.

Too many have died. Too many more WILL die. Enough is enough.