WEBVTT

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Looks like Shaggy wants to try it for the eight-man role in the picture.

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Arise!

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But there's Scooby doing the other chair.

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Surprise! It's the Scooby head the eight-man was wearing.

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Now there's real talent.

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We sure fooled him Scooby. We ought to be in the movies.

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Spare!

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Show me who we go!

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Good evening ladies and gentlemen, this is Giga Home Biological.

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It's a high-resistance, low-noise information brief brought to you by a biologist.

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It is Friday the 13th of October, 2023.

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Lots of threes today.

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What to say about that?

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Not the wrong with free.

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Let's go!

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Trying to figure out a way to get Joey in the door.

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You see that? That was nice.

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That was nice.

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Oh, I ran out of music. What happened there?

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It was a little weird.

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I might just...

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Might just do something like this.

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Because it's just funny, I don't know.

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There was no spread in New York.

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Infectious clones are the only real threat.

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Placebo batches were likely distributed and

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in healthy mammals is dumb.

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To put it another way, protocols were murdered, gain of function is a mythology.

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The Scooby-Doo mystery that you are fooled into solving is real.

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And the players are committed to the lies.

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Ladies and gentlemen, this is Giga Home Biological.

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And we are here every night trying to

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excavate ourselves from the cave.

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And so we're keeping our flashlights forward.

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We're keeping our arms straight.

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And we are not surrendering to the fear and confusion and doubt.

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And that's where we are.

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Good evening ladies and gentlemen.

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Welcome to the show coming to you live from Pittsburgh, Pennsylvania, dropping zero frames.

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I assume that my lips and the picture are roughly or the lips of my sound are roughly locked.

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That could be good.

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I paid this out before I get a copyright strike there.

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As usual, you know, not a lot of any different frames or different slides set tonight.

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Just get right to the show.

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Thanks to everybody for supporting the stream for these last three years.

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Thank you very much for sharing it.

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And if you can do so with this one as well, don't take the bait on TV and social media

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because there's a lot of it right now.

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The mystery is still being solved.

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We are still unmasking the bad guys.

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And we keep circling the block all the time, coming back to Berwick and EcoHealth Alliance

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and Tony Fauci and America and lying and USAID and the CIA.

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And we've got to wake up from this.

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We've got to wake up from it, and we're not going to wake up from it

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if you keep listening to the same storytellers.

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We're not going to wake up from it.

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If we keep listening to the same storytellers, it's not going to happen.

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But the same storytellers are telling stories to the other people

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and then the other people and then the other people.

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And this is where we are.

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where we are. And so we've been trying to figure out this map of people you're gonna

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have to apologize, I have to apologize, my hoodies a little magic on the green screen.

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But this illusion of consensus can be broken if we see it, if we can start to show it to

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people that this agreement doesn't make any sense between these people.

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And if we are honest, there aren't that many people that have been very consistent throughout

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the pandemic. But one of them is definitely Nick Hudson. And he just gave a talk a couple

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days ago, which I have been recommended to watch. I'm not, I have not watched it yet.

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My plan is to take notes and stop it as minimally as possible to make this about an eight on

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hour long show. So let's roll the dice and see how long I can keep my mouth shut. By the

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way, intramuscular injection of any combination of substances with the intent of augmenting

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the immune system is likely silly. And for sure, transmission is not immunization. So

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we can stop all of those. We'll talk about that later. This show is about the perception

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of what is true, the lights that are going by your head right now. If I scoot out of the

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way a little bit, those lights that make it seem like that you're going through a tunnel,

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obviously, you know, you're really not going through a tunnel with other side tunnels that

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are lit by other lights. But it looks like you are. And if this goes fast enough, and there's

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enough physical stimulation or or distraction, for example, a lockdown or economic pain or

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TV fear or social media hype, then a pandemic can seem very, very real, just like this tunnel

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can seem really real, especially if the only window to the outside world is a two dimensional

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screen. These people are spectacularly committed to the lies. And Nick Hudson brings his a game

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as he presents the data as we know it. And I think it's going to be a pretty good talk. Although,

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I haven't seen it. It's title actuarial and statistical problems around the COVID phenomenon.

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I have very high hopes. I consider Nick a pandemic friend. I met him through Panda,

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obviously, and I feel like although Panda is an organization full of a variety of individuals,

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I believe Nick to be a man of good faith and a man of seeking the truth. I do really feel like

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he's one of these few. And that's why he's one of those green squares in my current people map.

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So let's get this on. I'll string my head as soon as I hit play.

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Didn't I hit play? Well, come back. We continue now with our 50th annual convention and the 75th

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birthday celebration of the actuarial society of South Africa. If we're just meeting for the first

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time, my name is Inkramila Andrew. I'm going to be your host for the rest of the day.

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So it's been just over three years since the outbreak of the COVID-19 pandemic.

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And so allowing us time to reflect and analyze and review different perspectives, to better

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understand things, and hopefully learn lessons from past events in order to improve for the future.

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In these next two separate presentations that follow, we'll hear from presenters who will

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highlight the importance of actually in such a pandemic event, as well as sharing processes

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and technical research. Can we do the South African accent on 1.5? Is that okay with everybody?

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If you have to, if I have to slow it down one more now, just tell me.

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Findings when analyzing the COVID-19 pandemic. I think it'll be easier.

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You're able to engage with the technical context and research findings of the

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presentations during the Q&A session at the end of each presentation. In this first session,

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we have Nikaxanja to deliver his presentation entitled actuarial and statistical problems

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around the COVID-19 phenomenon. Thank you very much. I'm going to start by claiming

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a first. My sister, who's much more interesting than I am, is on stage next door at the same time

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that I'm on stage here. She's not an actuary. She's a radio presenter, but there you have it.

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How often does that happen at the convention? Family affair, really. Most of us are old enough

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to remember how bad COVID, sorry, bad models were so implicated in the 2008 financial crisis.

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The dawn of the COVID phenomenon was greeted by a plethora of models predicting doom

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of strikingly similar scale. And without exception, I'd be failing to bear even a vague

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resemblance to its reality. Those models generally assumed that there was a deadly virus and that

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lockdowns would slow the spread of it, resulting in less dying. One would call the results

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comical if their impact on society had not been so tragic. When Sweden famously rejected the

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lockdown idea, the models who facilitated the locking down of the world rejected that it would

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experience in a few short weeks a whole year's worth of extra death, translating into a weekly

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mortality rate some six times normal levels. That would leave them at the end of the year

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with twice the level of normal deaths. What actually emerged was that Sweden had a year of

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mortality in line with its tenure average. Now, in our actuarial studies, we learn about a little

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thing called the actuarial control cycle, which amongst others entails testing our models against

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emergent evidence in commercial settings failing to employ the control cycle after a signal as

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loud as this one. I think he's saying too much important to go so fast.

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Just going to slow it down one tick so everybody catches it a little bit. He's a very smart guy.

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He speaks very well. There's nothing to do with him. It has to do with my desire for you to hear

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Nick and what he's got to say. He's going to roll it back. The impact on society had not been so

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tragic. When Sweden famously rejected the lockdown idea, the models who facilitated the locking down

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of the world projected that it would experience in a few short weeks a whole year's worth of

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extra death, translating into a weak immortality rate some six times normal levels. That would leave

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them at the end of the year with twice the level of normal deaths. What actually emerged was that

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Sweden had a year of mortality in line with its tenure average. Now, in our actuarial studies,

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we learn about a little thing called the actuarial control cycle, which amongst others entails testing

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our models against emergent evidence. In commercial settings failing to employ the control cycle

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after a signal as loud as this one would likely result in the responsible actuary

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facing some very difficult questions, if not being fired. Now, the evidence that those models

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called SIR models or susceptible infected recovered models were not merely incorrectly calibrated,

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but wholly inappropriate for application to the COVID phenomenon and that the ensuing policy

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recommendations was wrong, was available abundantly and available decisively within weeks of the

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onset of the COVID hysteria, but it was all ignored. It was as if the actuarial control cycle had never

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been invented. At Panda, the organisation I co-founded along with a group of multidisciplinary

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professionals to push back against the catastrophic hysteria, we could see, for example, that completely

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different places with similar population characteristics experienced completely different mortality

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outcomes, and that these differences could not be explained by viral dynamics, something else was

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at work. This observation led us to adopt an empirical modeling approach capable of subsuming

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all factors, not merely the theory of a novel daily virus. And despite not being perfect,

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that model was very accurate. As the South African coronavirus modding consortium and the

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actuarial society continued to deploy SIR models, we uttered their inaccuracy by making various

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predictions that were strongly validated by emergent evidence. For example, at the time of release of

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SACMA's revised model, we predicted that it would breach the lower bound of its

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comically broad confidence intervals in 10 weeks. We were out by one day. Similarly,

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we predicted that hospital bed demand would be just 5% of what they projected, and again,

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correctly, in the Western Cape, our model predicted peak utilization of hospital beds to the digit.

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In December of 2020, we engaged with the premier of the Western Cape. We asked him what had made

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him spend hundreds of millions building two field hospitals. He said that was what the models

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told them they would need. We described the inaccuracy of the SACMA models to him,

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and he said he wasn't using them. He mistakenly, as it turns out, said that he was using the

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NASA model. He then astonished us by saying that he was investing in a third facility.

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Now, as it turns out, it seems it was not NASA who was advising him, but a consulting firm

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using one of the varied but consistently wrong scenarios from the second iteration of the

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NASA model. I hope that his claim about this will be investigated and that the failure of,

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you know, by whatever consulting firm that was to comply with the normal

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arterial control cycle will have some consequences because the public interest was definitely not

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protected in that scenario. But building pointless facilities was the least of the travesties,

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unleashed upon the public by woefully advised and highly pressurized governments.

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The financial and humanitarian consequences of lockdowns have been quite staggering.

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The established NGO, Action Against Hunger, finds as follows. Before COVID lockdowns,

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the number of people at risk of starvation was 135 million worldwide. By the end of 2021,

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that had increased by another 135 million people, and in 2022, it then increased by a further 67

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million people. The result is that we currently experience about 10 million new deaths a year

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from starvation, three million of them among children. It's a staggering, staggering

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consequence of lockdown. On top of that, about $4 trillion of wealth has been siphoned off

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from the middle classes to the benefit of a coterie of billionaires, the number of whom

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swelled by a quarter over the lockdown period. Now, numbers take time to be updated, but charts

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like this one tell a story of the haves benefiting at the expense of the have-nots.

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And this is precisely the kind of outcome that Panda had warned of in our first paper,

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which stirred up so much breastfeeding range and anxiety amid people swept up by the false

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narrative of the COVID phenomenon. If you're not,

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May 2020, Panda's contention that the COVID policy response would trigger 30 times as much

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loss of life as COVID stood stood to was a dramatic underestimate.

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May 2020. That's that's some impressive, impressive stuff.

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Convinced that such people were engaged in acts of immense folly, we have an interesting tidbit

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for you. Let's, for a moment, suspend judgment on that whole suite of SIR models. Let's assume

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for a minute that they were actually appropriate. And we ask the question, what happens when you

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deploy such models reflecting one of the clearest and earliest available empirical results under

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the COVID phenomenon, namely that COVID exhibited intense age-graduated mortality with deaths,

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among even vaguely healthy under-70s being negligible? What happens if you incorporate

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differential mobility for the at-risk elderly? Now, at this website, we have a model you can

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play with showing that reducing the mobility of the non-vulnerable by locking down causes her

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immunity to be attained with higher prevalence among the vulnerable. Let that sink in for a minute.

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What it means is that in terms of the very logic of SIR models themselves,

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lockdowns can clearly be predicted to shift disease burden onto the people most likely to die,

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causing total deaths to increase. This is a stunning reality and I invite you to look at

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this website and verify it for yourself. Okay, having argued that the application of SIR models

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is invalid. I think what's important to note here, I'm not sure if this is the model,

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it would have been one of the models, but there are a couple old guys in Panda that are old

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ecologists. Believe it or not, ecologists are really good at making models. A lot of their stuff

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is based on, you know, you make a sample across an ecosystem and then you make a sample across

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an ecosystem and then you make a sample across an ecosystem and then you make a model of what's

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happening based on those repeated samples over seasons. And so making a model of people getting

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infected and it's spreading and so that's easy for them. Maybe they can do that and it's the same

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kind of map, it's the same programming. And so Panda's website had a number of these models

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at one point that you could play with, which I think is pretty extraordinary. It's not something

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that the American or the Dutch or the your any European CDC had where scroll up and down on the

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R knot. So you can see what it does or scroll up and down on our predictions. So you can see what

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they do. So you can see how absurd our predictions are. Or you can see what our predictions will look

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like over years and why these models aren't right because they don't really. And you can play around

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with this, the idea of changing the age dependency of the of the potential for lethality

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and changing the way that that affects, you know, there are ways to do it. And there are ways that

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they could have brought us to understand these models better. But if they would have done that,

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they wouldn't have been able to make the claims that they wanted to make. We would understand the

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limits of their model. And the whole charade would have been over. We would have seen the two-dimensional

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scenery trees for what they were, because we would have turned them on their side like this and go

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wait, that's not a real tree. And that's what these models are. From the front, they're painted

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beautiful and they look like a great thing like, wow, we really understand this biology. Look,

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we can even adjust some parameters and the biology responds. Ooh. But even Nick will admit

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that this is a model that is dumb because it's still just these real basic epidemiology models

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based on infection and immunity and blah, blah, blah, like three variables. But if they're going to

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use it, then at least we might as well show them how they're not using it very well. Because if you

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add one more variable like age dependence, your model makes some pretty dark predictions.

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It's gorgeous, Nick. Congratulations, keep going. We need to get back to some reliable findings.

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We now have hundreds of studies validating this one from Panda's paper in mid 2020.

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This will be familiar to a great number of you who have ever done numerical and technical work,

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which I imagine will be quite a few. Lockdown students, he was entirely uncorrelated with

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official mortality data. On the x-axis, we have lockdown, stringency, on the y-axis,

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official COVID mortality. And that, ladies and gentlemen, is a pain splat. No correlation.

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Now, we can return to the point I mentioned earlier, that one of our first and earliest

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conclusions was that something else was going on other than viral spread and that it had to do

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with where you were. Before exploring what that something is, let's explore the theoretical

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framework for this. A syndemic is the aggregation of two epidemics that exacerbate disease burden,

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where two processes are present, statistical methods can be used to assess which is the

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more important and how much it contributes. And one of those methods is a type of Bayesian analysis.

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You look at which of these two factors elicits a differentiation in the objective population.

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And we get some very clear and for some people quite startling findings when we do that.

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When the presence of COVID or a PCR test, for example, is used as a flag, what we find is that

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the characteristics of COVID deaths are identical to the characteristics of non-COVID deaths among

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multiple dimensions. So age, gender, income, and comorbidity prevalence. And this strongly

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suggests, very strongly suggests that COVID is not a cause of age. See what I mean by starting

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outcome. But if you flag people for where they were, when they died, the proportion of deaths

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varies spectacularly by that flag. The virus would seem to obey political borders at a very

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granular level, which is, of course, impossible. Death attributed to COVID emerged to be very

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heavily determined by political boundaries at multiple levels of granularity. The combination

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of those two results, the failure of COVID to divide deaths into differential populations

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and the very strong tendency of geographic flags to divide them very strongly suggests that

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variation in clinical and public health practices is a major culprit where excess mortality is

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involved. So does everybody understand that? If it was a disease, it should, it should separate

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on age, it should separate on the same morbidity, prevalences,

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sorry, and it doesn't. So in other words, it's not sorting by what you would expect it to sort

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if it was a respiratory disease with a certain set of of vulnerabilities in a certain vulnerable

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population. Instead, instead, as Denny has told us a couple days in a row now and even told Kim

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Iverson, it respects municipalities, it respects hospital regions, and it, it respects the protocols

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that were present. And so if the deaths don't cross borders, then they have something to do

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with what the people are doing inside of those borders rather than the biology, which, of course,

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crosses borders, and the biology that affects certain people more than other people,

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certain vulnerable people more than certain healthy people. But we actually didn't see that,

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which is really in some ways pretty striking. I think we should listen to him say it again

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because he says it better himself. Two results, the failure of COVID to divide deaths into

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differential populations and the very strong tendency of geographic flags to divide them very

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strongly suggests that variation in clinical and public health practices is a major culprit

27:00.320 --> 27:08.720
where excess mortality is involved. A second syndemic phenomenon was indeed operating in the

27:08.720 --> 27:14.640
background beyond the reach of media attention. Now, if this strikes you as something that's

27:14.640 --> 27:20.560
difficult to digest, I invite you to indulge in something of a thought experiment. Imagine that

27:20.560 --> 27:26.080
one day when no particular virus or bacterium or fungus was in circulation, you woke up to find

27:26.160 --> 27:30.720
that your local hospital administrator was announcing on television that certain changes

27:30.720 --> 27:36.720
would be made to his hospital's policies. Henceforth, patients with flu-like symptoms

27:38.240 --> 27:43.360
would be isolated. They would receive massively reduced attendance by healthcare workers.

27:43.360 --> 27:47.360
They would no longer receive antibiotics to suppress secondary infections.

27:47.360 --> 27:51.760
Crucial patient advocacy provided by the hospital visitation system would be terminated.

27:52.320 --> 27:56.960
The hospital's would administer a new drug called remdesivir, a drug of no demonstrated

27:56.960 --> 28:01.200
efficacy and associated with multiple organ failure. The patients would be put on ventilators.

28:01.760 --> 28:06.160
Even when they had no kinetic difficulty breathing, party to prevent the suspected

28:06.160 --> 28:10.320
aerosolization of viral particles that might endanger hospital staff and even though the

28:10.320 --> 28:17.360
ventilator mortality rate was running at well above 90%. Now, I put it to you that if that

28:17.440 --> 28:22.000
announcement happened under normal circumstances, there would be an immediate public outcry.

28:22.960 --> 28:28.480
And everybody would be abundantly, it would be abundantly clear to everybody

28:28.480 --> 28:35.120
that such moves would result in countless deaths. And there is your syndemic because that is exactly

28:35.120 --> 28:39.360
what transpired under COVID. There you go. In a nutshell,

28:39.360 --> 28:47.840
I want to hear it again because it's just so damn good. I'm going to turn it up.

28:48.960 --> 28:54.960
That was impressive. That's impressive. This is the thought experiment that I tried to get Peter

28:54.960 --> 29:05.920
to do that actually, actually, I think Danny Rancor helped me make Peter do this thought experiment

29:06.000 --> 29:12.720
in his hand. Listen to the thought experiment that Nick describes this, this, this syndemic,

29:12.720 --> 29:21.440
it's a systemic epidemic of behavior. And if you changed all the behavior and across the board,

29:21.440 --> 29:27.920
the policy change of how we're going to treat respiratory disease and the changes weren't good.

29:28.720 --> 29:31.200
That's what happens.

29:38.400 --> 29:43.280
Now, if this strikes you as something that's difficult to digest, I invite you to indulge

29:43.280 --> 29:48.160
in something of a thought experiment. Imagine that one day when no particular virus or

29:48.160 --> 29:53.280
bacteria or fungus was in circulation, you woke up to find that your local hospital

29:53.280 --> 29:58.240
administrator was announcing on television that certain changes would be made to his hospital's

29:58.240 --> 30:06.720
policies. Henceforth, patients with flu-like symptoms would be isolated. They would receive

30:06.720 --> 30:11.120
massively reduced attendance by healthcare workers. They would no longer receive antibiotics to

30:11.120 --> 30:16.560
suppress secondary infections. Crucial patient advocacy provided by the hospital visitation

30:16.560 --> 30:21.760
system would be terminated. The hospital's would administer a new drug called Remdesivir,

30:21.760 --> 30:24.800
a drug of no demonstrated efficacy, and associated with multiple organ failure.

30:25.440 --> 30:29.680
The patients would be put on ventilators. Even when they had no kinetic difficulty breathing,

30:30.240 --> 30:34.880
partly to prevent the suspected aerosolization of viral particles that might endanger hospital

30:34.880 --> 30:38.880
staff, and even though the ventilator mortality rate was running at well above 90%.

30:40.400 --> 30:46.320
Now, I'd put it to you that if that announcement happened under normal circumstances, there would

30:46.400 --> 30:54.160
be an immediate public outcry. And everybody would be abundantly clear to everybody

30:54.160 --> 31:00.880
that such moves would result in countless deaths. And there is your syndemic because that is exactly

31:00.880 --> 31:06.240
what transpired under COVID. Such practices were taken up more enthusiastically in certain hospitals

31:06.240 --> 31:10.800
than in others and in certain districts than in others, explaining the stock geospatial

31:10.800 --> 31:16.800
differentials among other deaths. And that also why it correlated with the lockdowns,

31:16.800 --> 31:23.440
because essentially either you had a top down administration from the governor to the state

31:23.440 --> 31:29.520
health administrator or whatever the hell they're called in your state down to the school boards

31:29.520 --> 31:35.360
and the county and whatever. In Pennsylvania, that's the way it was. You just had somebody at

31:35.360 --> 31:40.640
the top saying we're going to follow all the rules. And once that person says that, it's all the way

31:40.640 --> 31:46.000
down the chain. And if you have that, then you also have more likely hospital administrators

31:46.000 --> 31:52.400
that are just going to say no holds barred, follow the protocols. And there were other places

31:52.400 --> 31:56.320
where they just weren't that strict. And when you weren't that strict, then doctors did what

31:56.320 --> 32:01.440
they should have done done and just treated like they treat all the time the symptoms said they

32:01.440 --> 32:10.400
see in front of them. And that's why there was no spread of the deaths. The mortality didn't

32:10.400 --> 32:17.280
spread. It respected borders. And that's why it respected borders because it was human behavior.

32:19.040 --> 32:26.480
Top down orchestrated human behavior. Just like this thought experiment that Nick just described,

32:26.480 --> 32:33.920
Nick is killing it. We're going to have to come up with a good name for him. If Mike Eden is

32:34.000 --> 32:40.160
Mr. Sparkle, then who's this? Can we call him Mr. Clean? Because I don't want to,

32:40.160 --> 32:43.520
it could be Mr. Clean, but Mr. Clean's bald, so I don't want to say that.

32:45.200 --> 32:48.880
In terms of the hypothesis known as the healthcare fragility hypothesis, which has

32:48.880 --> 32:53.360
a rapidly increasing number of adherence due to the multiple data points supporting it,

32:53.360 --> 32:58.880
the COVID phenomenon is best viewed as a mass casualty event rather than as a viral pandemic.

32:59.280 --> 33:06.720
Right. So far, the contents of this presentation have been quite bland and controversial.

33:07.360 --> 33:11.760
He's a little bit like a Sean Connery from South Africa, though. What would that, what could we

33:11.760 --> 33:16.560
call him then? Is there a, if you use Sean Connery, is that a clue for a new nickname?

33:18.480 --> 33:23.440
So before I turn to the hot button of the injections, I'd like to have an opportunity to

33:23.520 --> 33:29.360
loosen you up with some salient facts. The following statements are all true and presented

33:29.360 --> 33:35.520
in approximately temporal order. Number one, governance signed draconian contracts,

33:35.520 --> 33:39.920
committing them to acquiring billions of injection doses prior to the dissemination of any evidence

33:39.920 --> 33:46.000
regarding their safety and efficacy. Number two, the results of randomized trials run by

33:46.000 --> 33:50.560
the manufacturers of those injections were released. These trials were underpowered,

33:50.560 --> 33:55.200
were not double blinded, and groups vulnerable to severe COVID outcomes were underrepresented.

33:56.320 --> 34:01.920
Analysis of those trials demonstrated using the trial data that the intervention arm of the study

34:01.920 --> 34:07.280
exhibited worse all cause experience and that all relevant clinical outcomes.

34:08.880 --> 34:13.760
Worse all cause experience under all relevant clinical outcomes than the placebo arm.

34:15.120 --> 34:19.920
The intervention arm suffered higher all cause deaths, higher all cause hospitalization rates,

34:20.720 --> 34:28.320
more serious adverse events, and higher all cause severe morbidity, and many people are

34:28.320 --> 34:35.600
astonished to find out. Even higher occurrence of COVID symptoms as defined by the study itself.

34:38.880 --> 34:45.200
Media claims of 95% efficacy for these products were premised on one non-clinical finding from

34:45.200 --> 34:50.560
the study that of higher incidence of COVID symptoms in conjunction with a positive PCR test.

34:50.560 --> 34:56.080
It's a non-clinical finding. It's of no use to man or beast. Analysts found that the propensity to

34:56.080 --> 35:00.960
apply PCR tests to those with COVID symptoms in the placebo arm was multiple higher than the

35:00.960 --> 35:05.280
similar propensity for the intervention arm suggesting profound crossing of the blind and

35:05.280 --> 35:14.240
invalidating that sole non-clinical result. So start. Number three, a legal case was brought

35:14.240 --> 35:20.240
by a whistleblower from a company called Ventavia citing multiple serious irregularities at labs

35:20.240 --> 35:25.440
to whom administration of the Pfizer trial had been outsourced. Quite astonishingly Pfizer's

35:25.440 --> 35:29.760
defense in that case was not that no fraud had been committed but essentially that it had served

35:29.760 --> 35:36.160
up the fraud demanded of it by the US military. The Fifth Circuit judge did not accept this

35:36.160 --> 35:41.040
defense but ruled that while those irregularities were problematic they were not evidence of commercial

35:41.120 --> 35:45.200
fraud because the contracts had been signed prior to commission of the scientific fraud

35:46.160 --> 35:49.440
and that the fact that the FDA hadn't done its job in that it authorized rather than

35:49.440 --> 35:55.440
approved the vaccines left the matter out of the court's hands. Number four and perhaps most

35:55.440 --> 36:00.320
significantly of all Pfizer then performed a bait and switch. It distributed to the world a

36:00.320 --> 36:05.200
product fundamentally different from the one that had fraudulently tested in crucial regards.

36:06.000 --> 36:12.240
Number five, it's this list is long. Pfizer and the FDA went to court in an attempt to prevent

36:12.240 --> 36:19.200
the exchange of data between them from becoming public for 75 years. Now it's important to note

36:19.200 --> 36:22.560
that Pfizer never responded to the allegations regarding the clinical findings of the trials

36:22.560 --> 36:26.960
even though a central and early voice and primary author in the whole fracar was a respected and

36:26.960 --> 36:31.760
long-serving editor of the British medical journal itself. This is stunning because the

36:31.840 --> 36:37.440
implication is that anyone who has ever recommended that anybody be vaccinated with the Pfizer

36:37.440 --> 36:42.320
product is wittingly or unwittingly arguing that even though the product is expected to make you

36:42.320 --> 36:46.320
more likely to become sick, to experience severe illness, to be hospitalized or to die,

36:47.280 --> 36:54.480
you should take it so that we can have fewer positive PCOS and that quite clearly is a ridiculous

36:54.560 --> 37:01.440
proposition. With these facts in mind, that was all preamble, I invite you to put aside

37:01.440 --> 37:07.920
your judgments to forget about what the man on the TV may have told you and to consider some data

37:07.920 --> 37:14.800
about these injections. Much of the evidence presented in favor of the injections outside of

37:14.800 --> 37:21.920
the fraudulent Pfizer Phase 3 trials is classed as observational, as distinct from arising from

37:21.920 --> 37:27.200
a randomized control trial. Now this is sketchy at best because of the very large difficulty in

37:27.200 --> 37:32.080
designing observational studies so as to eliminate confounding factors and because of the extremely

37:32.080 --> 37:38.320
low fatality rate of COVID. The single most relied upon analysis regarding these injections is

37:38.320 --> 37:44.400
arguably that emanating from the UK's ONS or Office for National Statistics. Based on aggregate data,

37:44.400 --> 37:50.160
it claimed that the vaccines had high efficacy going even beyond the all-cause result arising

37:50.160 --> 37:56.480
from the Pfizer trial. After much, much foot dragging, the underlying data was released,

37:56.480 --> 38:01.040
this took for your requests and constant harassment and badgering and researchers immediately

38:01.040 --> 38:05.520
demonstrated significant problems visible in the underlying data. For example, if you look at this

38:05.520 --> 38:13.120
chart, this analysis of age classified non-COVID mortality comes from that data. The gray line

38:13.120 --> 38:18.640
superimposes injection uptake on this rather strange non-COVID mortality line for the unvaccinated,

38:18.640 --> 38:24.000
which is depicted in orange. And once you've seen that, all credibility you may ever took to

38:24.000 --> 38:32.080
that study should evaporate immediately. Absent a coherent explanation for how the act of injecting

38:32.080 --> 38:39.120
grandpa over here causes a grandpa over there to drop dead. It's actually unfortunate that this

38:40.160 --> 38:44.960
graph is in a little better because this gray line telling you how many doses were taken up,

38:45.600 --> 38:53.600
it's on a scale from 0 to 100%. Now, if it was a numbers and you have deaths per thousand,

38:53.600 --> 38:58.800
you might even get a better idea of how related they are. I understand that this still shows you

38:58.800 --> 39:04.320
something temporally, but it would be interesting to know at what scale we're at because it looks to

39:04.320 --> 39:10.160
me, you know, you'd hope that it would happen within two weeks and then that would be the two

39:10.240 --> 39:15.840
week shift, right? Because everybody's unvaccinated for two weeks. And so if it just shifted all the

39:15.840 --> 39:22.160
people that were taking the shot to a more likely attesting positive and getting whatever,

39:23.280 --> 39:28.960
then this rise here should be related to these shots, but then it'll be farther in time.

39:31.040 --> 39:36.000
And then they would have been vaccinated. So it's interesting. It's interesting to think that

39:36.000 --> 39:39.840
maybe that these people that were vaccinated are giving it to the unvaccinated people,

39:39.840 --> 39:43.920
but I don't, I'm not saying that. I'm just, I wonder what Nick will say.

39:44.480 --> 39:52.000
So spend all credibility to this analysis. It's, there's clearly something going

39:52.000 --> 39:56.720
deeply wrong with the methodology of the study. This is just one of multiple problems from the

39:56.720 --> 40:02.640
study. And it's a distinct issue, for example, from the canard of categorizing people as unvaccinated

40:02.720 --> 40:06.480
for the first however many weeks after their vaccination. Now, no act, you should have any

40:06.480 --> 40:11.600
problem spotting the immediate problem with that canard because, and it's very easy to demonstrate

40:11.600 --> 40:16.720
this, this will mathematically artificially induce almost arbitrarily high efficacy signals,

40:17.360 --> 40:22.560
even if an observational study is unwittingly structured to compare one placebo with another.

40:23.120 --> 40:29.440
Doesn't require a live medication. Just a placebo versus placebo study with that methodology will

40:29.440 --> 40:34.160
give a false, obviously a false efficacy signal. This is what it looks like.

40:35.200 --> 40:40.320
On a, obviously if there's exactly the same methodology for the two arms, no, no exclusion

40:40.320 --> 40:42.720
period in either of the arms, then the results are going to be the same because we've got a

40:42.720 --> 40:48.000
placebo versus a placebo. But if you introduce just a two week exclusion period, you get an

40:48.000 --> 40:53.920
artificial efficacy for placebo versus placebo of 60%. And if you extend it to three weeks,

40:54.800 --> 40:58.320
that boosts the signal to around 80%. Remember, this is entirely of the artificial structure,

40:58.320 --> 41:03.200
manufactured example. And they were studies that have gone as far as seven weeks of exclusion.

41:05.120 --> 41:10.240
It's fraud. It's scientific fraud. And of course, the other thing that happens here is after so many

41:10.240 --> 41:15.520
weeks, 10, 12 weeks, whatever, what happens? Trials terminated before this effect can disappear.

41:16.880 --> 41:21.040
And yet this scam, because that's what it is, is an almost uniform feature of investigations

41:21.040 --> 41:23.200
into injection consequences. Pointing out that.

41:24.000 --> 41:27.760
So you want me to explain this one, Ali Maria or the one before this?

41:33.760 --> 41:35.840
Otherwise, I'll just keep going the one before it.

41:42.400 --> 41:47.840
So this is unvaccinated mortality. This is vaccinated mortality. He's saying that it's not

41:48.400 --> 42:00.480
it's not consistent with the idea that this dose uptake here. And this rise in unvaccinated

42:00.480 --> 42:08.480
mortality shouldn't be so temporarily related to one another. Vaccinated should be higher or equal,

42:08.480 --> 42:13.920
but this plot is consistently below life table rate. So I think he's here talking about

42:14.480 --> 42:21.200
these people aren't even dying at the normal rate that their age group should die. So that's

42:21.200 --> 42:26.960
also weird. There's a number of things that he's pointing out here. I'm going to go forward a

42:26.960 --> 42:31.360
little bit. So this one is just showing you that when you use that two week exclusion for a brief

42:31.360 --> 42:38.640
window of six or eight weeks, it's really an amazing false impression that you have efficacy.

42:39.600 --> 42:44.960
And Crawford actually showed those two on three months. It's very easy to think about it.

42:44.960 --> 42:48.560
It's very easy to think about it just from the perspective of measuring the number of days.

42:49.280 --> 42:53.440
So if you just do the imaginary study where

43:00.000 --> 43:07.680
the stuff that I spray on my feet keeps my keeps me from getting from getting bug bites on my feet.

43:08.320 --> 43:15.440
But it's only effective after 14 days of use. So before I've used it for 14 days, I still have

43:15.440 --> 43:22.800
unsprayed feet. So if you compare my sprayed feet to a bunch of people that don't spray their feet

43:22.800 --> 43:29.200
for 28 days, and actually there's only 14 days of that 28 days where you're going to be looking at

43:29.200 --> 43:34.640
me and whether I get my bug bites, because before that, I'm actually contributing to the other group.

43:35.600 --> 43:40.800
And if anybody gets bit in the first 14 days of their before the 14th day of their spraying,

43:41.760 --> 43:47.520
then you're going to move them to the unvaccinated group. That's what they did in all these studies.

43:49.600 --> 43:56.160
And so by the end of the study, when you've moved anybody in the first 14 days that got bit

43:56.160 --> 44:00.160
by a bug over to the other side, and then you said, see the people that sprayed their feet

44:01.040 --> 44:05.440
didn't get bit. It's very deceptive because you've actually

44:06.320 --> 44:10.960
excluded half of the time period of the 28 days and put it in the other group.

44:12.720 --> 44:18.720
And even though they extended this out, if you think of the vulnerability as being an exponentially

44:18.720 --> 44:22.960
decreasing curve, then they're shifting a lot of things over to the other group.

44:23.040 --> 44:31.200
And then you get this slight but solid signal of effectiveness that they could parade around

44:31.200 --> 44:40.240
with relative risk. It's extraordinary. It's fraud. It's scientific fraud. It's fraud.

44:41.200 --> 44:44.960
And of course, the other thing that happens here is after so many weeks, 10, 12 weeks, whatever,

44:44.960 --> 44:48.160
what happens? Trials terminated before this effect can disappear.

44:49.040 --> 44:53.680
And yet, this scam, because that's what it is, is an almost uniform feature of investigations

44:53.680 --> 44:58.320
into injection consequences, pointing out that creator scare hospital was deploying it,

44:58.320 --> 45:01.920
elicited what was perhaps the greatest and most coordinated media smear campaign that

45:01.920 --> 45:06.560
I faced since I started speaking out against the madness. All of it, of course, based on complete

45:06.560 --> 45:12.560
fabrications. Now, as a rule of thumb, categorical studies relying on accurate placement and

45:12.640 --> 45:16.880
control for all material confounding variables are as scarce as hence teeth.

45:17.520 --> 45:20.160
And you have to ask the question, what can we do about that?

45:22.000 --> 45:28.320
For our money, the most reliable form of investigation plausible is to conduct

45:28.320 --> 45:32.320
temporal correlation assessments for causality of all cause mortality.

45:33.280 --> 45:36.640
It's not something we study in the actual syllabus, the Bradford Hill criteria for assessing

45:36.640 --> 45:41.360
temporal causation are well known in public else. Lots of people now need to utilize them.

45:41.440 --> 45:43.920
They're not, they're well within the capacity of most actors to understand.

45:45.680 --> 45:49.040
And you can apply it to data like this. This is data from the Netherlands.

45:49.600 --> 45:54.320
And that data is crucially important because, and uniquely valuable, because that country

45:54.320 --> 45:58.800
conducted its vaccine rollout in a strictly age-based fashion. Each and every age group

45:58.800 --> 46:06.800
produces a chart like this. Now, just, I just want, oh, sorry, skip the page, there we go.

46:06.800 --> 46:10.080
I just want to, you know, maybe just make sure you're reading the lines correctly.

46:10.080 --> 46:13.840
The blue is the summer and spring vaccination program, number of doses.

46:13.840 --> 46:17.920
And the gray on the right there that's, that hump is the autumn vaccination process.

46:18.480 --> 46:21.040
Red is excess mortality for this age group.

46:22.640 --> 46:26.080
Yeah, no challenge. Bradford Hill, tick, tick, tick, all the way to the bank.

46:26.960 --> 46:32.400
The vaccinologist, doctor, Theo, Theo Chittis, who did this work,

46:32.480 --> 46:37.520
infers from this work, an accrued vaccine dose fatality rate of about 2,000 per million doses,

46:38.160 --> 46:42.640
making it even more fatal than the purported fatality rate of SARS-CoV-2.

46:43.440 --> 46:46.720
It's very serious stuff and very hard to look at without scratching your head.

46:48.960 --> 46:52.960
Other analyses are beginning to emerge. This one I have not time had time to study.

46:52.960 --> 46:56.720
It was the degree of rigor I'd like. I know the author, he's a reliable guy.

46:57.680 --> 47:04.160
And he deploys a methodologically sophisticated approach to test for what's going on.

47:06.320 --> 47:09.200
This is Danny Rancor's work. You can see his name right there.

47:12.560 --> 47:18.000
For temporal regime change and to assess data from near tropical countries where mortality

47:18.000 --> 47:21.680
exhibits very weak seasonality, so it doesn't produce a big noisy effect in your data.

47:21.680 --> 47:28.800
It estimates a crude vaccine dose fatality rate of 1,260 per million doses, so a little bit low,

47:28.800 --> 47:33.040
but pretty much in line from an order of magnitude perspective with Theo Chittis' work.

47:34.000 --> 47:36.160
Notably, in this analysis, South Africa produces...

47:36.160 --> 47:38.960
Theo Skitters is what he should be saying.

47:38.960 --> 47:44.080
Theo Skitters, he's saying it a bit funny because he's South African and they speak Dutch too.

47:44.080 --> 47:47.840
The worst estimate I've come, so perhaps we should be grateful that the vast majority

47:47.840 --> 47:50.160
of our population declined the opportunity to be vaccinated.

47:51.040 --> 47:56.160
Despite the fact that attempts to coerce them, we're in clear violations of multiple

47:56.160 --> 48:02.480
codes of public health and human rights. An important note with regards to both these investigations is

48:02.480 --> 48:09.840
that... That's a nice way of saying it in violation of multiple codes of human rights.

48:11.920 --> 48:17.600
That's a pretty good way of saying it. Vaccine dose fatality rate exhibits a very strong

48:17.600 --> 48:22.640
age graduation, so it's a feature which ought to be explored for the same reasons I outlined

48:22.640 --> 48:27.040
earlier with respect to COVID mortality in the discussion on syndemicity.

48:28.880 --> 48:32.560
Now, it takes a while for research like this to come to light, not least of all,

48:32.560 --> 48:36.800
because it's clearly funded and because we often have to undertake the costly step of deploying

48:36.800 --> 48:40.800
freedom of information requests to obtain data that should never have been out of the public domain

48:40.800 --> 48:45.680
in the first place. But there were early warning systems in place and they had been,

48:45.680 --> 48:48.880
for a couple of years, sounding an unprecedented alarm. Look at this.

48:49.520 --> 48:53.360
This is the VAERS system in the US. It's a signaling system for adverse events,

48:53.360 --> 48:59.360
which the FDA is justly very proud of, not to mention legally obliged to maintain

48:59.360 --> 49:04.000
a good working order, and in respect of which it is a felony to input false records.

49:04.640 --> 49:09.920
And that VAERS system, vaccine adverse event reporting system, was signing out a signal orders

49:09.920 --> 49:13.680
of magnitude higher than any ever seen for any product ever before.

49:15.040 --> 49:23.360
And what the response was after this absolutely flawed because I began hearing people spectacularly

49:23.360 --> 49:28.080
committed to lying, trying to make up that these vaccine records were input by anti-vaxx

49:28.080 --> 49:33.600
mainly comes was after this absolutely flawed because I began hearing people spectacularly

49:33.600 --> 49:38.240
committed to lying trying to make up that these vaccine records were input by anti-vaxx

49:38.240 --> 50:02.640
members of the general public. It's a claim which doesn't even stand up to very modest

50:02.640 --> 50:06.640
scrutiny. That's just an impossibility. Even worse is the claims that these injuries were

50:06.640 --> 50:12.000
really long COVID. Of course, that's obviously long COVID. A condition for which there is no

50:12.000 --> 50:17.520
sound clinical definition and which has failed to evidence of existence in any sound statistical

50:17.520 --> 50:24.080
test. They claim this even to explain the massively elevated rates of cancer and heart

50:24.080 --> 50:29.280
deaths being witnessed the world over. And the worst thing is that they know that we know that

50:29.280 --> 50:36.080
they're lying. When it comes to claims regarding the impact of the vaccines on COVID transmission,

50:36.080 --> 50:41.440
the warning signs came far earlier than this by decades, in fact. Research into the question

50:41.440 --> 50:45.520
of whether serum antibodies are sufficient to elicit mucosal immune response necessary to

50:45.520 --> 50:50.400
prevent infection and transmission has been consistent and clear. There was no sign of such an effect.

50:51.120 --> 50:54.720
And when it came to the COVID injections, among the earliest findings admitted to even by the

50:54.720 --> 50:59.920
sanctity faulty himself was that there was no difference in viral titers between infected vaccinated

50:59.920 --> 51:05.600
and infected unvaccinated people. Yet, despite the non-existence of any plausible mechanism for

51:05.600 --> 51:09.840
transmission suppression and interface of abundant evidence that there actually wasn't any,

51:09.840 --> 51:13.120
the lie of transmission reduction pulled forth from the miles not just a faulty,

51:14.000 --> 51:19.680
but of diverse characters such as Rachel Maddow and Albert Boula, the CEO of Pfizer and Bill Gates.

51:21.040 --> 51:26.720
Given that transmission reduction was the prime and virtually the sole motive behind vaccine

51:26.720 --> 51:33.120
mandates, this was for me a particularly disgusting turn of events. A somewhat depressing reality to

51:33.200 --> 51:40.000
acknowledge is the sheer lack of commerciality entailed in accepting the received narrative

51:40.000 --> 51:46.000
around the COVID phenomenon. By day, I run a successful private equity fund. Private equity

51:46.000 --> 51:51.120
management firms suffer one of the highest mortality rates in the world, principally because

51:51.120 --> 51:55.760
very few people are able to sustain the degree of skepticism that is necessary in an environment

51:55.760 --> 52:01.600
that's characterized by very intense information asymmetries. The lesson that every would be private

52:01.600 --> 52:07.440
equity transactor has to learn in order to avoid obliteration is that claims made by people

52:07.440 --> 52:12.560
whose financial well-being entails making those claims are to be assigned very low

52:12.560 --> 52:19.280
credibility. Simple little principle. Sorry, wait a second.

52:26.400 --> 52:31.360
The uncomfortable reality is that all of our media, our universities, our institutions of

52:31.440 --> 52:36.320
public health and all relevant regulators are deeply in the pockets of pharmaceutical stakeholders

52:36.880 --> 52:40.720
very deeply. This chart just shows the funding from the largest family foundation that happens

52:40.720 --> 52:46.160
to be also one of the largest investors in vaccines. Funding just for South Africa and I would just

52:46.160 --> 52:49.440
point out that there are some aggregations that need to be done there to work out the true scale

52:49.440 --> 52:53.040
of the funding at some of these institutions. They're neatly pocketed them into different divisions

52:53.040 --> 52:57.600
and mark them as if they're going to different places. But officers of these institutions,

52:57.600 --> 53:02.480
all of them, are able to speak out only if they are willing to see their careers destroyed.

53:03.120 --> 53:07.520
Therefore, anything they do say about the COVID narrative must logically be ignored.

53:08.400 --> 53:13.120
Victims such as follow the science and appeals to authority of such creatures

53:13.120 --> 53:18.560
should bring hollow to anybody who hears them. In a similar vein, common sense dictates that

53:18.560 --> 53:23.680
under such conditions it is wise to look at who is trying to censor whom. Throughout history,

53:24.320 --> 53:30.080
censorship has never been the objective of the good guys. I've been reminded so many times

53:30.880 --> 53:37.360
during this saga of Alexander Solzhenitsyn's great work, the Gulag Archipelago. His notions

53:37.360 --> 53:42.160
of the banality of evil and how the line between good and evil runs through every human heart

53:42.720 --> 53:48.720
have never rung to her for me than in the last few years. It is the rule, not the exception,

53:49.360 --> 53:54.480
that people who commit evil acts are generally sincerely convinced of their own good intentions.

53:55.200 --> 54:01.600
And an episode of evil that I would say surpasses any event in world history has befallen us

54:02.560 --> 54:10.720
these past few years. And it continues to befall us. Wait, what I mean continues to befall us.

54:11.840 --> 54:16.800
As we speak, South Africa and many other nations are set to sign up to a World Health Organization,

54:16.880 --> 54:20.880
a court and a subsidiary set of international health regulations that make the outrages of the

54:20.880 --> 54:26.320
COVID period pale into complete insignificance. In terms of these agreements, countries agree

54:26.320 --> 54:31.360
whenever a public health emergency has been declared to regard all the whose health recommendations

54:31.360 --> 54:37.120
as compulsory, including but not limited to mass mandated vaccination, mandated medical

54:37.120 --> 54:42.480
examinations, boarded closures, incarceration or quarantine of the unvaccinated and mandatory

54:42.480 --> 54:47.680
censorship regimes. In short, whenever a health emergency is declared, the sovereignty of any

54:47.680 --> 54:51.680
nation and all civil liberties would be suspended for as long as the World Health Organization demands

54:51.680 --> 54:57.840
it to be. No condition is imposed on this other than the declaration of a threat, regardless of

54:57.840 --> 55:04.560
whether there is any demonstrated harm or mortality rate. And it can be imposed at the

55:04.560 --> 55:10.560
sole behest of the Director General with no obligation upon him to follow any sort of democratic or

55:10.560 --> 55:14.480
consultative process. And I'll remind you that the person sitting in that chair right now

55:15.040 --> 55:18.480
is a former terrorist with a long history of human rights abuses.

55:20.480 --> 55:24.640
Now, agreeing to do this may well be contrary to our Constitution and there's a legal

55:24.640 --> 55:29.360
fight to be had there. But what the Bretton Woods organizations did throughout COVID and clearly

55:29.360 --> 55:34.880
signaled they were enthusiastic to do some more, is that non-compliance with World Health Organization

55:34.880 --> 55:39.920
dictates resulted in exclusion from the global financing system. And there are only a handful

55:39.920 --> 55:43.840
of nations on the whole planet who are sufficiently autarkic to survive that.

55:45.360 --> 55:49.920
The accord also expands the scope of the very perverse One Health System. It's a creepy philosophy

55:49.920 --> 55:55.440
that extends the definition of health outcomes to include all sorts of non-human priorities.

55:56.480 --> 56:00.400
If you haven't heard of it before, I really suggest you read up on it. Both of these documents

56:00.400 --> 56:06.880
set up a requirement as well for a very intensive and continuous surveillance for viruses and

56:06.960 --> 56:12.320
their so-called variants. Now, they will definitely find some of these as they exist in nature all

56:12.320 --> 56:18.720
the time, all the time, always around us. And next time, they will not have to fabricate a story

56:18.720 --> 56:25.440
about a pangolin and a bat in the bar. And this can then be used, the discovery of any kind of

56:25.440 --> 56:31.440
novel sequence for the inception of further lockdowns of populations potentially all over the planet.

56:32.240 --> 56:36.240
And what waits in the wings is the thing called the CEPI 100 Day Vax Initiative,

56:36.240 --> 56:41.280
which is then anticipated to deliver a new mRNA vaccine which will be profit as the only path out

56:41.280 --> 56:47.600
of lockdown, under peril of financial isolation. To make matters worse, taxpayers will fund all

56:47.600 --> 56:52.640
of this nonsense, but the profits will go to the pharmaceutical industry. The surveillance

56:52.640 --> 56:57.360
set up and the bureaucracy behind it make it inevitable that we will have recurrent threats

56:57.360 --> 57:03.360
declared and acted upon. The funding involved here is nose bleeding, far higher than for any

57:03.360 --> 57:09.920
endemic disease on the planet. The World Bank says about $3.1.5 billion a year. But that's

57:09.920 --> 57:13.040
a small fraction of the profits that stand to be made by the pharmaceutical industry in this

57:13.040 --> 57:18.400
process. And all of this is true despite the fact that no broad recirculating virus has produced

57:18.400 --> 57:22.880
even a miniscule fraction of the disease burden of major infectious and non-communicable diseases.

57:23.760 --> 57:28.560
It's all perfectly bananas. And unless you're entirely brainwashed, a recipe for disaster for

57:28.560 --> 57:33.520
everyone except the soon-to-be-minted trillionaires who sit at the top of this epic food chain.

57:34.880 --> 57:44.480
It should worry you. That is so brilliant. This epic food chain. I mean, what he just said there

57:44.480 --> 57:49.280
was just genius. It produced even a miniscule fraction of the disease burden of major infectious

57:49.360 --> 57:54.960
and non-communicable diseases. It's all perfectly bananas. And unless you're entirely brainwashed,

57:54.960 --> 58:00.160
a recipe for disaster for everyone except the soon-to-be-minted trillionaires who sit at the top

58:00.160 --> 58:07.520
of this epic food chain. It's perfectly bananas. Perfectly bananas. There's two words that I would

58:07.520 --> 58:17.120
never put together myself in Nick's accent from his tongue. It is the sharpest of sharp knives.

58:17.120 --> 58:23.200
It is perfectly bananas what we've done. It's perfectly bananas that we've let them do it.

58:23.200 --> 58:27.680
And it's perfectly bananas that we aren't already having heads on pikes.

58:29.600 --> 58:34.880
It should worry you that not have worded this has been spoken in our parliament or any parliament

58:34.880 --> 58:38.640
anywhere in the world and that the mainstream media have been completely mute on any of the

58:38.640 --> 58:46.960
significant aspects of this whole arrangement. You will appreciate why I am choosing to end

58:47.120 --> 58:52.000
by saying that I hope that this period during which we have accepted the refusal of people

58:52.000 --> 58:56.160
promoting the most damaging and extreme actions the world has ever encountered to submit their

58:56.160 --> 59:00.480
ideas to the scrutiny of their peers and to engage with their critics in public forums

59:00.480 --> 59:05.920
will come to an end very soon. Maybe our discussions together now can signal the beginning of the

59:05.920 --> 59:12.960
end of that blind acceptance. A sign of this would be one of the injection promoters accepting our

59:12.960 --> 59:17.280
long-standing invitation to submit their sanitized data and methodology to us full of you. It's

59:17.280 --> 59:24.880
perfectly standard scientific process. And above all as the fog of the COVID hysteria lifts it's my

59:24.880 --> 59:31.600
hope that many more members of this profession will recover the common sense and the commerciality

59:31.600 --> 59:39.200
that should be their pride and joy and see the evil for what it has been that they will recover

59:39.280 --> 59:44.320
their courage and take a firm stand alongside me against the spectacular commitment to line

59:45.200 --> 59:54.240
and say no more of this abject nonsense. Thank you. He said it twice, baby. He said it twice, baby.

59:56.960 --> 59:59.040
Thank you, Nick. Are there any questions from the floor?

01:00:00.640 --> 01:00:05.520
No, I know he's quoting me because he sent me a message about five days ago saying he thinks that's

01:00:06.080 --> 01:00:09.840
his new favorite phrase of mine is the spectacular commitment to lie.

01:00:12.560 --> 01:00:18.800
It's great. I don't see anybody with microphones. Why did you just stand up and shout out on

01:00:28.880 --> 01:00:34.400
Yes, he said it twice. One of the four papers that we obtained was the work of the behavioral

01:00:34.400 --> 01:00:39.760
science teams in the UK, the nudge units. If we run out of questions, I'm going to talk to you a

01:00:39.760 --> 01:00:46.640
little bit about that because it's fascinating. Carry on, Nick. Your base data, the presentation

01:00:46.640 --> 01:00:52.400
you showed. Have you, okay, first of all, we have to acknowledge that there were a lot of vaccines

01:00:52.400 --> 01:00:59.760
that were administered during the pandemic. So have you adjusted your slide with the actual

01:00:59.760 --> 01:01:04.800
vaccines at minister to people? Because obviously, if you look at the absolute number of address

01:01:04.800 --> 01:01:08.800
events, it would look great. Yeah, surprisingly, it doesn't make much difference. I mean,

01:01:08.800 --> 01:01:11.840
I've heard this quote as I actually made that quote as in months before, but what I was shocked

01:01:11.840 --> 01:01:15.120
to find out is how many vaccines I administered in America. It makes no difference to the broad

01:01:15.120 --> 01:01:19.600
findings. So the incidence rate here is orders of magnitude higher. You just think through it,

01:01:19.600 --> 01:01:23.680
you have 26 vaccines administered to every child born in America and a very high percentage of

01:01:23.680 --> 01:01:27.360
the population take flu vaccines every year. So there's billions of doses being handed out.

01:01:27.440 --> 01:01:32.640
It doesn't take away this money. I think it's actually helpful to show those stats because

01:01:33.440 --> 01:01:38.880
when you present a slide like that without the exposure, it is not helpful at all. It is not

01:01:39.680 --> 01:01:43.840
objective. And when you say it like that, how are we supposed to know that there is a real

01:01:43.840 --> 01:01:48.320
difference? There are all sorts of things going on in that data. They're changing attention rates,

01:01:48.320 --> 01:01:51.840
changing age groups and everything. It's a signaling system, not an observational study,

01:01:51.840 --> 01:01:57.120
so it's not meant to infer a death rate. Only somewhere between 1% and 10% of vaccine injuries

01:01:57.120 --> 01:02:01.600
and deaths respectively end up on the system. They know that. That's been documented.

01:02:01.600 --> 01:02:06.480
So it's an early warning signal, and I'm not making a claim that this is something that you

01:02:06.480 --> 01:02:10.560
can infer a mortality rate from. Nobody can make that claim. But the point is that that signal,

01:02:10.560 --> 01:02:14.960
which is designed to be reacted to immediately as you get something like that, was completely

01:02:14.960 --> 01:02:22.240
ignored. That's the problem now. Well done. Nick, two just quick things. So you started

01:02:22.240 --> 01:02:26.160
commenting on the Sweden mortality and the 10-year average. So I just went into a quick

01:02:26.160 --> 01:02:30.400
check on a couple of sites. And the numbers don't seem to tie up with what I heard you say.

01:02:30.400 --> 01:02:33.920
So perhaps I got that wrong. If you would follow that up with a written confirmation,

01:02:33.920 --> 01:02:40.320
that would be great. And the second thing was you had attributed the source to www.sars2acir.org,

01:02:40.320 --> 01:02:44.000
which is a website that doesn't exist. So again, if you could just provide some of the source

01:02:44.000 --> 01:02:48.320
material there, because I was worried that some of the comments you made about things being

01:02:48.400 --> 01:02:52.240
fantastical and all the rest of it might be well applied here, too.

01:02:52.240 --> 01:02:56.240
Yeah, that's no problem. I must have made a typo in the reference there. So I was just

01:02:56.240 --> 01:03:00.800
seeing it. Yeah, there should be an S on the end of that. Sorry. Yeah, what I will do for

01:03:00.800 --> 01:03:05.120
everybody's benefit is interested. I'm going to assemble a list of all the sources in this

01:03:05.120 --> 01:03:08.320
presentation, and just so you can kind of click and read two hearts content. I promise you, I'm not

01:03:08.320 --> 01:03:13.840
making anything up. I didn't quite hear the rest of your question. I'm sorry. It's very

01:03:13.920 --> 01:03:18.480
boomy. The sound up here was something that's unanswered there. No. Okay.

01:03:20.960 --> 01:03:22.720
Further questions? There we go.

01:03:25.760 --> 01:03:29.920
Hi. It's Rosanna Harris. Mine is not so much a question as a comment.

01:03:31.280 --> 01:03:39.200
So I guess I feel quite sad, actually, listening to this in a platform here and quite

01:03:39.760 --> 01:03:45.600
professionally disheartened. While some may have been locked away in their ivory towers trawling

01:03:45.600 --> 01:03:51.840
three secondary data and evidence, trying to desperately support an ill-conceived initial

01:03:51.840 --> 01:03:58.960
stance, I've been fortunate enough to be working with dedicated teams who have approached this

01:03:58.960 --> 01:04:05.360
problem with integrity and rigor and scientific curiosity to unpack the evidence and contribute

01:04:05.360 --> 01:04:10.960
to saving lives and saving the economy. I work for Discovery Health, and we administered just

01:04:10.960 --> 01:04:16.640
over six, just under six percent of the population on the schemes that we are under our administration.

01:04:16.640 --> 01:04:24.480
And for us, COVID was real. Our team was dealing with real world primary data. People who were sick,

01:04:24.480 --> 01:04:30.560
people who died, people who lost loved ones. There were 16,500 confirmed COVID deaths in our

01:04:30.560 --> 01:04:34.160
population, and we recorded a case fatality of two and a half percent, just under two and a half

01:04:34.160 --> 01:04:39.360
percent, and a hospital mortality rate of 15 and a half percent. That's one death for every six

01:04:39.360 --> 01:04:45.680
and a half admissions. Just under 82,000 of our members were admitted to hospital during COVID,

01:04:45.680 --> 01:04:52.240
and I assure you that there was not a conspiracy of doctors. There is no evidence in our data to

01:04:52.240 --> 01:04:56.560
support any conclusion that vaccines did more harm than good, quite the opposite, in fact.

01:04:57.200 --> 01:05:02.400
And transmission reduction was a valuable side effect of a program that was intended to protect

01:05:02.480 --> 01:05:07.840
people from severe illness and death. These are real numbers, and I can't help but feel the need

01:05:07.840 --> 01:05:13.360
to apologise to the many health professionals and everyone who worked tirelessly and selflessly

01:05:13.360 --> 01:05:18.320
during COVID, and to everyone who was affected themselves or their loved ones. Oh, he's getting

01:05:18.320 --> 01:05:28.080
ready. Oh, and there's clapping. Get him, Nick. Needless to say, this is not the first time I've

01:05:28.080 --> 01:05:35.280
heard such a speech, prepared, never responding to any of the analysis performed. Just to stop,

01:05:35.280 --> 01:05:39.840
apply your minds to the data. That is what actually is meant to do. How do we explain that in multiple

01:05:39.840 --> 01:05:44.720
regions around the planet, 2020 ended with very high zero positivity and no excess mortality?

01:05:45.680 --> 01:05:50.960
How can you explain that if we have a deadly virus on the loose and not an epidemic of catastrophic

01:05:50.960 --> 01:05:59.200
iterating standards of care? It's very hard. Germany ends up with 10 or 20% upwards in some areas

01:05:59.200 --> 01:06:06.560
and zero excess mortality at the end of 2020. Zero. And there are entire swathes of the planet

01:06:06.560 --> 01:06:10.880
that had exactly this outcome. And I take incredible exception to the idea that some are a volunteer

01:06:10.880 --> 01:06:16.000
organisation of academics who are forced to work in private because the cancel culture led by

01:06:16.000 --> 01:06:23.440
organisations such as Discovery is so intense that they cannot do honest work in their own

01:06:23.440 --> 01:06:28.720
organisations. Those people are working for no pay and tirelessly and putting themselves at

01:06:28.720 --> 01:06:32.400
great risk. There is no question in my mind. And this is not about a conspiracy theory,

01:06:32.400 --> 01:06:36.400
an immature approach to take towards a person who sits there presenting statistics. It's not

01:06:36.400 --> 01:06:42.640
a conspiracy theory. It's an alternative view. And we can engage. I'd love to engage on your data

01:06:42.640 --> 01:06:47.280
methodology, but you don't share it. An alternative view. Thank you so much, Nick. A wonderful

01:06:47.280 --> 01:06:52.800
plus for our presenters. It looks like this is all the time we have. Thank you so much, Nick.

01:06:54.560 --> 01:06:59.280
I think that's pretty good. I think Nick did really, really well.

01:07:02.320 --> 01:07:09.920
Congratulations to Nick Hudson, aka Mr. Spectacular. And I had tipped to Nick for using my phrase.

01:07:10.400 --> 01:07:16.160
Um, you know, just, I'll just show you because, you know, I can do that, I think.

01:07:21.680 --> 01:07:32.160
Just pull this out over here. I'll see if I can find, uh, messages. Nick.

01:07:32.880 --> 01:07:39.280
It's a spectacular commitment to lying. May turn out to be your best contribution to this saga so far.

01:07:39.280 --> 01:07:45.520
And you should not find that disappointing. It's a great phrase. That's what Nick said to me on

01:07:45.520 --> 01:07:51.680
October 3rd. And then he gave this talk, I think, on October 12th. So there you go. Um, there's no

01:07:51.680 --> 01:07:56.880
question that it's, that it's, uh, that it's, uh, that it's a, that it's a hat tip. And that's

01:07:57.440 --> 01:08:01.440
that it's, uh, that it's a hat tip. And that's really nice of him. And it's really,

01:08:02.400 --> 01:08:07.680
again, what are we talking about here? I put it on the bottom. I gave it the title, subtitle.

01:08:07.680 --> 01:08:14.080
And Nick Hudson brought his A game dog on it. Mr. Spectacular. I mean, he didn't let me down

01:08:14.080 --> 01:08:21.760
at all. Way to go, Nick. So this illusion of consensus is starting to break. That's what I think.

01:08:22.720 --> 01:08:29.520
I think this illusion of consensus is starting to break. And even though the illusion of consensus

01:08:29.520 --> 01:08:35.280
was about this mystery disease down here in red, we're starting to understand that with bad

01:08:35.280 --> 01:08:43.760
protocols and with bad tests, you can rope in, you can create the bursts of excess mortality,

01:08:43.760 --> 01:08:49.520
the appearance of excess mortality that you need in order to tell the story that you want to tell.

01:08:50.240 --> 01:08:56.560
And smeared around the map a little bit. And now nobody notices until Denny or Nick or anybody

01:08:56.560 --> 01:09:02.400
else crunches the numbers and realizes that the death and the disease didn't spread across borders

01:09:03.280 --> 01:09:09.840
that it had more to do with people's income had more to do with so many other things other than

01:09:09.840 --> 01:09:16.480
their symptomology. And that's really the problem because they declared the who declared a dangerous

01:09:16.480 --> 01:09:24.800
novel virus pandemic that everybody was vulnerable to. A guy that he said was guilty of human rights

01:09:24.800 --> 01:09:30.640
violations. I got to look that up that I just recorded an old video of him today for a future

01:09:30.640 --> 01:09:37.360
show in my archive. I didn't know he was a bad guy like that. Anyway, a clone could have been used.

01:09:38.000 --> 01:09:45.680
I see Jiki still on the clone kick. He's still figuring out that really all RNA virology is cloning

01:09:45.680 --> 01:09:53.920
and all RNA virology would collapse if we didn't have recombinant DNA to use to make RNA infectious

01:09:53.920 --> 01:09:59.280
clones of all these things. It's really a standard methodology and the only source

01:10:00.000 --> 01:10:05.600
of a pandemic that is blamed on a single sequence. The surrender of individual sovereignty and the

01:10:05.600 --> 01:10:10.640
enforcement of an inversion from basic human rights to basic granted permissions is the goal

01:10:10.640 --> 01:10:16.240
of this little charade. The way that they're going to do it is they fooled you, of course,

01:10:16.240 --> 01:10:20.800
about the pandemic potential that's in nature. And there's a consensus that we could even,

01:10:20.800 --> 01:10:25.760
you know, sew things together and make more pandemic potential than Mother Nature can herself.

01:10:25.760 --> 01:10:32.720
Again, it's to invert your kid's minds. Invert the way that your kids think about their role

01:10:33.360 --> 01:10:40.080
in nature, their place in nature. It is to invert the way that their your kids should think about

01:10:40.160 --> 01:10:46.560
their immune system and should think about the temple that is their body. It doesn't need augmenting

01:10:46.560 --> 01:10:52.880
willy-nilly. We tell our kids that they shouldn't smoke marijuana or they shouldn't, you know,

01:10:53.600 --> 01:11:00.560
drink beer, but it's fine to inject a random combination of substances made by a pharmaceutical

01:11:00.560 --> 01:11:04.000
company into your muscle to augment your immune system. That'll be fine.

01:11:04.000 --> 01:11:16.080
And this illusion of consensus spread to the point where they created this orchestrated

01:11:16.080 --> 01:11:25.200
argument across nations and across languages and across cultures about who's responsible for

01:11:25.200 --> 01:11:30.560
leaking this virus. Who's responsible for lying? Who funded it? Where did it come from? Was it

01:11:30.560 --> 01:11:35.840
leaked in Ukraine? Or did it leak in China? Or did somebody spread it all around the earth?

01:11:36.640 --> 01:11:39.920
What a crazy thing we've had to solve for the last three years.

01:11:42.320 --> 01:11:47.840
And while we were solving that, we didn't realize that they changed the way we fundamentally thought

01:11:47.840 --> 01:11:57.520
about our immune system, disease, how it spreads, the potential for pandemic, what vaccination means,

01:11:57.520 --> 01:12:04.640
what it should do. And they just glossed over everything with either stupid, complicated,

01:12:04.640 --> 01:12:11.360
or dumb, simple. And in so doing, this enchantment of this Scooby-Doo allowed people to be killed by

01:12:11.360 --> 01:12:17.760
ventilators, medazolam, remdesivir, all the things that Nick talked about perfectly. Way to go,

01:12:17.760 --> 01:12:27.120
Mr. Spectacular. And so the general gist of the Scooby-Doo is that you're supposed to be thinking about a

01:12:27.120 --> 01:12:33.840
laboratory leak or a laboratory leak that was originally from a bad cave or a bad cave virus

01:12:33.840 --> 01:12:39.840
that had the potential for a pandemic all by itself, or the possibility that a lab leak of a virus

01:12:39.840 --> 01:12:45.920
that was sewn together could have even more pandemic potential than a bad virus would. You're

01:12:45.920 --> 01:12:51.360
just not supposed to think about the fact that they could make a lot of a clone and spread it around

01:12:51.360 --> 01:12:57.280
the world. And that'd be a real easy way for this to happen, especially if there was a background

01:12:57.280 --> 01:13:05.840
signal of RNA all over the place that this PCR test would be confused by. I think that's what

01:13:05.840 --> 01:13:11.520
they did. It's mostly lying. It's a background signal and lying. And that's why the protocols

01:13:11.520 --> 01:13:15.920
are murder and transfection is in medicine, you can call it an infectious clone release,

01:13:15.920 --> 01:13:21.920
you can call it a transfection agent, you can call whatever you want to. Just don't say that

01:13:21.920 --> 01:13:28.720
there are no viruses because that's ridiculous. There are definitely infectious clones. And so

01:13:28.720 --> 01:13:36.240
called a conflated background signal that was confounded by a infectious clone release. And now

01:13:36.240 --> 01:13:41.920
you have the perfect scenario where all the molecular biology lines up, all the PCR can be

01:13:42.000 --> 01:13:47.520
explained, all the symptomology goes away, and all of the deaths are murder.

01:13:50.160 --> 01:13:54.640
And the reason why we're here is because they really want to in birth the way that our kids think

01:13:54.640 --> 01:14:07.440
about their, their, what is the right word? What they owe to society, I can't think of their,

01:14:08.080 --> 01:14:16.000
their, why is my brain blank on that? But we are trying to change the way that our children think

01:14:16.000 --> 01:14:25.520
about our obligations to society. And the idea that we should feel obligated to be clean,

01:14:25.520 --> 01:14:32.480
the obligated to follow public health measures that keep everybody else safe, and that our

01:14:32.480 --> 01:14:40.400
safety is dependent on one another. That's a fundamental inversion of how we usually would think

01:14:40.400 --> 01:14:48.640
about disease and health in a free society. It's a fundamental inversion of what freedom means,

01:14:48.640 --> 01:14:53.600
because essentially it means that even if the technocrats get it wrong, you have to follow the

01:14:53.600 --> 01:15:02.000
rules until we get it right. That's not freedom. And we cannot lie to our children, we cannot let

01:15:02.000 --> 01:15:07.680
these TV people lie to our children about what's at stake, because this is the last 50 years,

01:15:08.880 --> 01:15:17.680
or last 70 years of 10 billion humans. And then it's going to start going down pretty fast.

01:15:19.120 --> 01:15:23.280
And it's going to be pretty rough ride, because there's going to be a lot of old people and not

01:15:23.280 --> 01:15:29.920
enough young people to support them all. So a lot of these countries that have an inverted population

01:15:29.920 --> 01:15:35.600
pyramid are in big trouble over the next 50 years, and they kind of know it. And so they need to

01:15:35.600 --> 01:15:39.920
take advantage of the crisis that's coming, they need to take advantage of the shift that's coming,

01:15:39.920 --> 01:15:48.560
and the crisis is also financial. As JC in the woods said so eloquently March 11th 2020,

01:15:49.600 --> 01:15:56.240
we watched that yesterday. Intramuscular injection of any combination of substances,

01:15:56.240 --> 01:16:02.560
as I said, transfection is not immunization. Please stop all transfections in humans. And that's

01:16:02.560 --> 01:16:12.560
really full stop. Now I'm going to try and eliminate the control group by any means necessary.

01:16:17.280 --> 01:16:21.840
Still, I'm trying to plug the broken science initiative. I want to get a few of them on. I'm

01:16:21.920 --> 01:16:27.440
going to have map rigs on, and I'm going to have a few. Maybe I can get great to come on. Who knows?

01:16:29.760 --> 01:16:33.840
Yeah, this has been good going biological. It's a weird ending, I guess. But you know, it's

01:16:35.920 --> 01:16:39.680
I'm not going to lie to you. I'm getting tired. I don't know how many days in a row this is. We're

01:16:39.680 --> 01:16:48.080
approaching 35 or 36. I'm getting a little tired. So I'm hoping that moving the streams earlier

01:16:48.080 --> 01:16:54.080
in the night so that I can get in bed and get to sleep and then get up earlier was going to help.

01:16:54.080 --> 01:16:59.840
I hope that playing basketball more is going to help my voice. I don't know, we're just going

01:16:59.840 --> 01:17:02.880
to keep working. I'm going to keep trying to come every day because this is really

01:17:03.680 --> 01:17:10.080
I think good for me and good for you guys. But thanks for joining me. And like I said, I'll see you tomorrow.