“We’ve Come to the Conclusion… the Evidence Strongly Supports That There Was No Pandemic”

The historical context: UK mortality 1941 to 2020

Let’s have a look at some data…

This is the data from 1941 to 2020. This is official ONS mortality data… On the left-hand side you’ve got a mortality rate, and then obviously… the years along the horizontal axis. And the bit on the right hand side that circled, that’s the bit… when I met my local Conservative MP, I highlighted the “pandemic” to him and said, “Does that look like a pandemic to you?” And he said, “Of course it does, because it’s going up.”

But when you compare that to previous peaks and troughs in that graph, it doesn’t look that remarkable. Of course there’s lots of human stories wrapped up in that… but in terms of the scale of the event it certainly doesn’t look as obvious as, say, the 1951 pandemic. You’ve got quite a significant bump there for that… so [2020] doesn’t look obviously like a pandemic. And… if you separate out the WHO definition of a pandemic and just think about the everyday person — interpretation of a pandemic from what we’ve read in books and seen on TV — we expect… a very significant mortality event, but we haven’t really seen that. So that might be an open question about… what that means.

Mortality comparison of European regions and countries

Here’s a comparison across Europe from 2015…

And here, if you look up to the year 2020, you get that normal influenza-like illness mortality pattern that rises up in the winter, that falls in the summer. And we’re all used to that. That’s a pattern that’s built into our everyday life and experience. But when you look at what happened in 2019 and 2020 just up to [the red dotted line, i.e. before the introduction of “covid measures”] it doesn’t look any different. And then suddenly we get the declaration of a pandemic from the WHO and the subsequent lockdowns and so on. And it’s only then that you start to see this mortality rise.

The different colours in this graph represent different cities across across Europe. And what you see is that… in many places you get a synchronous increase in mortality which looks a bit odd when you think about the virus spread… you would expect a geographical spread and a time delay as it moves from one place to the next. But we don’t see that… All the peaks of mortality rise up at the same time, just after the declaration of lockdowns and the pandemic… you’ve got a synchronous shift.

So that would suggest that there’s something else going on. And what we see in some some areas, like Bergamo in Northern Italy… [and] New York, although it’s not on the graph… you get a… massive spike… Yet in other places, like in Germany, you don’t see anything. There’s nothing remarkable at all, which doesn’t fit the…message that we were sold about a spreading virus.

Scotland, all location excess deaths in 2020

Let’s turn to Scotland. This is the mortality for all locations… by [which] I mean at home, hospital, care homes. And here, rather than mortality, we’re looking at simply excess deaths, which is the deaths over and above what you might expect from the historical pattern.

And in the initial three week lockdown we were expecting that the curve would be flattened, that we wouldn’t have hospitals overrun etc. That was then extended to nine weeks. And in those nine weeks in Scotland there was an excess death figure of roughly 4,500… But the interesting thing is, if you look before the lockdown… [“Weeks 1-12” on the left-hand side] you actually get fewer excess deaths than expected.

And that’s during the period that you would expect that the virus — if there was a virus — was spreading and infecting people. [But] we’re not getting a mortality signal at all. That only occurs at the point of the lockdowns and the non-pharmaceutical interventions and… all the craziness [that] was introduced.

This is consistent with the ONS figures for England and Wales discussed here:

Then the lockdowns end… 29th of May. And the country opens up again, and things return to normal. You get some variation in the summer. It’s up a bit and down a bit, but you’re not seeing anything different. It’s a natural variation which you wouldn’t expect, maybe, if you were in the middle of a pandemic… which we were told. And then in September the flu vaccines were rolled out and then mortality starts to increase as we all start to adopt these behavioural changes again that were imposed on us.

Scottish care homes, excess deaths in 2020

This is the care home excess deaths. We can see again that we’ve got a negative excess [i.e. fewer people dying than usual, in green] in the early part of 2020, so it looks quite similar to the last graph.

And then the red area obviously, again, is a huge increase in deaths. And obviously this happens straight after lockdowns have been been declared [on 23rd March].

Scottish hospitals, excess deaths in 2020

If you look at hospitals, we were told that hospitals were going to be overrun… That rhetoric was repeated again and again and again. And people were encouraged to change their behaviours in order to not overburden the medical services.

But what we see here in reality [from the actual data] in Scotland [is] that the burden in hospitals in terms of excess deaths… we get a bump, obviously [in the red area], but what the green areas represent is that people you would expect to be dying in hospital aren’t dying in hospital. They’re dying somewhere else. The hospitals aren’t dealing with patients you would normally expect to die. So what’s going on there? Why is that happening?

Now if you look at that [chart] overall, the statistic is that roughly over 1,000 deaths did not occur compared to the 5-year average over that period. And then we have a spike starting later on in the winter [of 2020/2021]. We’re getting more excess deaths… than you might expect.

Scottish excess deaths at home in 2020

Turning to excess deaths at home… The interesting part here is the blue area of that histogram. The blue area represents those whose deaths are attributed to covid. These are people dying at home in excess of what you might expect… in red. And what we’re seeing is that there’s a huge increase — just over 5,000 people died at home — compared to what you would expect.

Normally… typically, they would die elsewhere, say in care homes or in hospital, but they’re dying at home. So why is that happening? Why are people people dying at home, when really they should be attended to, and cared for in their final phase of their life?

So we’ve got 5,000 excess deaths in Scotland — 32% more than average. In England it’s just over 50,000. It’s roughly proportionate to the population sizes… 10x more in England than Scotland.

Urgent care activity (NHS England)

So what’s been happening with urgent care? This is from England. I couldn’t get the data for Scotland, but it’s quite similar for Scotland given what we’ve seen in the past.

Here you’ve got, for urgent care, the A&E attendances in March/April 2020. They basically fall off a cliff. People aren’t being rushed to hospital… exactly during that period. We were told we would expect a massive surge… the “sombrero effect” that had to be pushed down, as Boris Johnson said. But here we’ve got a massive gap… a huge drop-off in A&E attendances… So that doesn’t make any sense. Why would that… be happening when we’re in the middle of a pandemic? How do we explain that?

We can see that there’s a huge spike in NHS 111 calls — so people are generally phoning up for advice. They might be frightened. They might have healthcare concerns. They might not be getting relief elsewhere. So the only recourse they have is to turn to NHS 111 and phone them up. And in fact many GP services were saying that’s what you had to do. There was nothing else available to you. “Stay home until you go blue” was more or less the advice.

So we’ve got these massive gaps in expectations between what we expect in a so-called pandemic and what we actually saw. So how do we explain that? That’s been the driving motivation for us. How do we explain that?

Cause of death: attribution and certification

Well, one of the big changes is cause of death… attribution… changes to death certification.

Everybody’s familiar with death within 28 days of a positive covid test. But of course it wasn’t just a positive covid test, it was suspected or probable covid. So the doctor just has to have a mere suspicion… that suspicion could be that you probably died of covid because there’s a lot of it going around, and we’re in the middle of a pandemic. Nothing more than that is needed. And that’s also true for flu by the way. It’s not just for covid.

So we had these wholesale changes to the law in order to support these changes to death certification. It’s never been done before. And the other major change is that deaths could be certified remotely by telephone call, or maybe not even that… could be emailed in… So you have massive collapse in the infrastructure that we [had] there for verifying causes of death.

This graph is simply showing that the typical normal causes of death that you expect like dementia, cancer etc. were being transferred over to covid. So you get a reattribution and a pushing of… the co-morbidities that people would typically die of are being reclassified as covid. So covid deaths look to be increased, but there’s other underlying factors that are actually causing people to die, and they’re being classified as covid deaths. So that’s another driver of covid.

Modelling: an exponential growth in exaggerations

Of course we were told by the epidemiological modellers, by people like Neil Ferguson, that we would expect exponential growth in cases… this virus would spread through society in a deadly, persistent way. And… if you compare what actually happened — this is data from… the Autumn/Winter period 2020…

What you found [was] that the actual cases that were being reported… and recorded… even with all the cheating going on… they just didn’t have enough to meet the exponentiation requirements. So what they had to do was make changes to how they did the testing again, in order to create the cases. If the facts don’t fit the model, the facts have to change. So that’s what basically changed.

Covid-19 is not a High Consequence Infectious Disease

But of course the experts knew that this new virus — if there was one indeed… it could have just been an endemic background virus perhaps — was never going to cause a high-consequence infectious disease.

Back in March, the High Consequence Infectious Disease group, of which Neil Ferguson is a member, sat and looked at the classification of covid-19 and came to the conclusion that it was not… So it wasn’t an Ebola. It wasn’t some serious malady.

[Ferguson] was on the committee… and they ruled that [covid] wasn’t a High Consequence Infectious Disease [HCID]. And that’s still on the website. You can go and look… It’s a huge red flag sitting there, that the experts have declared that this wasn’t something to worry about, yet we were all told to worry about it. It was a bizarre contradiction. I almost had a nervous breakdown when I saw that, and… was showing people it and saying, “Look, they’re admitting it doesn’t mean anything. There’s nothing here.” [And they replied] “Well, surely it can’t mean that…?”

The Iatrogenesis Hypothesis

So ultimately we’re left with the hypothesis… how do we explain all this data? And we call this iatrogenesis [iatrogenic means induced unintentionally in a patient by a doctor].

It’s… the alternative explanation for the death patterns… the mortality patterns… The elevated patterns of death could either be attributed to a new virus or disease. Or it could be due to our interventions… the reactions that were taken… the changes in medical procedures, protocols, routines… even changes in basic routines can cause death in old people. So was the excess mortality caused by changes in public health and medical policy?

One of the major guiding changes was NG163, which I’m sure many of you will be familiar with. NG163 was brought in to manage covid respiratory symptoms in people suffering from what might be a genuine respiratory distress issue. And that was rolled out nationally, and it was accompanied by DNRs [“Do Not Resuscitate” orders] which we’ve heard about… also withdrawal of antibiotics.

So… the traditional means by which you would manage a respiratory disease… just discarded. And you need that for untreated bacterial infections, obviously. So it might not be the virus that’s much of a worry, but it’s all the sepsis, bacterial infections. And ultimately those who were suffering respiratory diseases… I would say a fair proportion of them would have been bacterial in nature, and not having antibiotics quickly enough may have been a compounding factor.

And this was obvious to experts… palliative care experts wrote letters to the BMJ [British Medical Journal] making clear that these kinds of changes represented by that particular change in NG163 would lead to suppression of people’s breathing ability, and death. These are palliative care opioid drugs… midazolam… And the [palliative care experts] were right. That’s exactly what happened. They forecast it, and it happened. They were ignored. The letter is still there in the BMJ. You can go off and read it. So the experts warned them, but… they ignored it.

The striking correlation between the use of midazolam and excess deaths

So just to corroborate the correlation between the use of midazolam and the changing pattern with the change in excess deaths…

This is for the UK. At the top there you see the spikes. In March/April 2020 we get a huge spike in excess death, and, if you look at the pattern of changes in midazolam prescribing, you see a huge increase at the same time.

Now you could say, “Well, you would expect that during influenza season, because people are going to have respiratory distress, and they might need to go on ventilators, and they might need midazolam.” But you don’t see commensurate spikes in the previous years. You just don’t see it. So it’s a unique spike. You see this also in New York, where they use fentanyl rather than the midazolam. That was the drug of choice in the States.

Re New York, the evidence presented here is worth considering:

I found this chart particularly striking:

Fraudulent PCR testing

Last one… so PCR testing was rolled out, and even if you were asymptomatic you could have covid-19 if the PCR test comes up positive. So we’re all familiar with that. What people aren’t familiar with is the real scandal of PCR testing…

A significant proportion of the PCR tests — maybe more in 2020 than maybe later — were picking up or designed to pick up other competing influenza-like illness viruses… coronaviruses, influenzas etc. So there was a huge drop-off… remember the flu disappeared? Well, it never really disappeared… but changing the test meant that these causative viruses were essentially reclassified as as SARS-CoV-2.

Now that doesn’t mean to say that SARS-CoV-2 doesn’t… exist… it’s largely irrelevant, that question. The question is: “What was killing people, and how did PCR influence that?”

[The] graph [above] on the right-hand side shows how they the pockled [cheated with] PCR. And you can see [the graph] shows the percentage in different regions of the UK…where the percentage of PCR tests that were being tracked nationally that were being called as positive… on one single gene rather than two of the three genes that may be used in the test… it’s rather technical, but essentially they were cheating on the tests. And these would be genes that might have an overlap. They might look similar to the genes that you might get in other viruses. In Scotland… March 2021, it was above 50%. And this is on the ONS website. You can go off and see the data. Many people don’t look, but it’s all there in plain sight.

So the PCR test — we use this phrase “casedemic”… it creates a persistent psychological impression that people have got illnesses, even if they don’t have any symptoms. So you were “pre-covid” or asymptomatic… suffering with no symptoms would mean you still had covid.

For further context re PCR testing, see e.g. this post on Kary Mullis, winner of the 1993 Nobel Prize in Chemistry “for his invention of the polymerase chain reaction (PCR) method”, who died in 2019:

Conclusions

So the conclusion that we’ve come to, somewhat reluctantly, because it’s quite dramatic, is that there’s no real evidence in our minds that there’s a lethal spreading virus. We just don’t see that pattern. It left large parts of Europe unscathed, and large parts of the world unscathed — Africa and so on. Lots of the harms and deaths are caused by policy changes — the reaction to it… if you want to view it as a reaction.

Evidence suggests that subtle changes to death certification — well, not so subtle actually… obvious changes to death certification and attribution, which were not resisted by the medical profession that just adopted this stuff — that would be enough to change the statistics. Just changing the labels on the death certificates gives the impression that there’s more [covid] death.

So you’ve got statistical manipulation… death certificate manipulation. You’ve got testing manipulation. And the reaction to it in terms of the policy changes, the iatrogenesis changes, the change in how people were treated… it’s that that caused the increased mortality that we witnessed, not maybe a spread of virus. So we’ve come to the conclusion… the evidence strongly supports that there was no pandemic.

I am reminded of this article from Denis Rancourt, formerly Professor of Physics at the University of Ottawa, who has independently reached a similar conclusion to that of Martin Neil (and others):

I found this section particularly striking (emphasis added):

All-cause mortality by time (day, week, month, year, period), by jurisdiction (country, state, province, county), and by individual characteristics of the deceased (age, sex, race, living accomodations) is the most reliable data for detecting and epidemiologically characterizing events causing death, and for gauging the population-level impact of any surge or collapse in deaths from any cause.

Such data is not susceptible to reporting bias or to any bias in attributing causes of death. We have used it to detect and characterize seasonality, heat waves, earthquakes, economic collapses, wars, population aging, long-term societal development, and societal assaults such as those occurring in the COVID period, in many countries around the world, and over recent history, 1900-present.

Interestingly, none of the post-second-world-war Centers-for-Disease-Control-and-Prevention-promoted (CDC‑promoted) viral respiratory disease pandemics (1957-58, “H2N2”; 1968, “H3N2”; 2009, “H1N1 again”) can be detected in the all‑cause mortality of any country. Unlike all the other causes of death that are known to affect mortality, these so‑called pandemics did not cause any detectable increase in mortality, anywhere.

The large 1918 mortality event, which was recruited to be a textbook viral respiratory disease pandemic (“H1N1”), occurred prior to the inventions of antibiotics and the electron microscope, under horrific post-war public-sanitation and economic-stress conditions. The 1918 deaths have been proven by histopathology of preserved lung tissue to have been caused by bacterial pneumonia. This is shown in several independent and non-contested published studies.

Here is the pattern of the use of the word “pandemic” from 1900 up until the covid era (NB the y-axis is a percentage):

And here is how Rancourt summarises his findings…

Here are my conclusions, from our detailed studies of all-cause mortality in the COVID period, in combination with socio-economic and vaccine-rollout data:

1. If there had been no pandemic propaganda or coercion, and governments and the medical establishment had simply gone on with business as usual, then there would not have been any excess mortality
2. There was no pandemic causing excess mortality
3. Measures caused excess mortality
4. COVID-19 vaccination caused excess mortality

This article ([SPCI-7] “We’ve come to the conclusion… the evidence strongly supports that there was no pandemic”) was created and published by Some Thinking Allowed and is republished here under “Fair Use”