In this episode, I am speaking with Ivor Cummins. Ivor has spent the last many months analyzing and making sense of the world’s COVID data.
Table of Contents
In this podcast, Ivor and I will discuss:
- The three primary reasons why a curve goes down during an epidemic
- The WHO guidelines for a pandemic (This will shock you!)
- The critical role of herd immunity
- The link between mortality rates and prior seasons
- Why Sweden is getting shamed in the media for their COVID strategies
- The shocking data on mortality rates from COVID-19
- And much, much more…
Listen or download on iTunes
Listen outside iTunes
Ari: Hey there, this is Ari. Welcome back to the Energy Blueprint Podcast. I am really excited for today’s episode, it is with someone who I’ve been trying to do an interview with for a couple of months now, his name is Ivor Cummins. He has been doing phenomenal work around synthesizing a huge amount of data related to COVID. He’s been doing these great presentations systematically presenting the data, presenting the evidence from a huge array of sources, and piecing this together logically to make sense of the data and he’s been doing that really more impressively than anyone I’ve seen.
He’s also challenging a lot of the common thinking and the mainstream narratives in the media while he’s also presenting the science to back everything up in a really systematic way. It’s very impressive, so I’m very excited to interview him. A little bit about him, he’s got a background in biochemical engineering. He’s got a degree in that that he got in 1990. He since spent 30 years in technical leadership positions and his career specialty have been leading worldwide teams in complex problem-solving activities.
Again, he’s got this background in like, how do you make sense of lots of data and lots of different data points in different fields and solve problems. A very interesting way of processing information. Since 2012, he’s been researching root causes of modern chronic disease and teaching about his findings. A particular focus has been on cardiovascular disease, diabetes, and obesity.
He shares his research insights at public speaking engagements around the world, revealing the key nutritional and lifestyle interventions, which will help correct a lot of these modern chronic diseases. He has also recently presented at the British Association of Cardiovascular Prevention and Rehabilitation, and also, at the Irish Institute of Preventive Cardiology Annual Conferences.
A couple personal comments for me before we get into this episode. I personally think that this is an incredibly important episode, and I hope that you’ll tune in and watch or listen to the whole thing. In the second half of the episode, we actually recorded on two separate days because we didn’t fit in everything, I wanted to talk about in part one, so I actually asked him to do a whole second interview. He was generous enough to do two full hours of interviewing with me.
In the second half, I actually asked him to present a lot of slides and specific data and studies to back some of his assertions because I know that some of what he is saying is going to– It’s challenging the status quo in various ways. For people who are very much aligned with the status quo, what mainstream media is reporting certain media channels at least, those people might be skeptical of what he has to say so I asked him to actually show some of the data, show some of the research that supports some of those use.
That’s in the second half, and you’ll really be able to see that obviously if you’re watching the video on YouTube, as opposed to just listening, but you can certainly get the gist of it listening as well. In addition, I wanted to give just a couple of thoughts of mine about COVID science. This is something that I’ve been following very, very intensely, really obsessively for about eight months. Now, I’ve devoted an enormous amount of time to following the science on COVID and the best data.
I have a couple of thoughts. One is, there are two things that really saddened me about what’s going on right now. One is that COVID science has become so deeply politicized to the point where it really no longer even resembles good science. We have highly biased, politicized narratives of science that are now held by a majority of the population because that’s what they’re getting fed by whatever particular media channel that usually has some kind of left or right political agenda. Each one of those has their own spin on the science.
I think that’s really unfortunate. I think it’s really unfortunate that we are now in a situation where most of the general population believes that their particular politicized version of the science is “the truth” and people who disagree with them just don’t understand the science. The second thing is that we’re in a situation where we really don’t know that much. We don’t understand everything about what’s going on. There’s so much that is not known about COVID, and our responses to it.
Just as one glaring example, this whole response to a viral epidemic, but most of the world has done is an experiment. We are guinea pigs in a new experiment that we do not have clear data on. Whether all of those lockdown measures and ongoing lockdowns, on and off lockdowns, whether they actually reduce deaths from the virus. We don’t have clear data on whether what are all of the harms of the lockdowns themselves, not just economic harms, but in terms of personal suffering, child abuse, spousal abuse, drug abuse, mental illness, in deaths of despair, increasing rates of cardiovascular disease, undiagnosed cancers, the list goes on, and on, and on.
Just as in Africa, for example, there are over a hundred million people now at risk of starvation due to interruptions in the food supply as a result of various countries locking down. We don’t know, is the bottom line. There are lots and lots of questions, and yet many people are pretending like there is some scientific consensus in what we’re doing. That there’s a mountain of science to support everything we’re doing.
It’s all backed by lots of evidence, we’ve all tried this exact thing a hundred times before and we know all the answers, we don’t and we have social media companies, actively censoring, very intelligent science-based heterodox thinking that pokes holes in and challenges a lot of what’s going on right now. It saddens me that so many people do not understand that the advancement of science and our understanding of things depends on people who are knowledgeable enough to bring forth the science that challenges the status quo.
Instead, we’re seeing mass censorship of those heterodox thinkers among us who are trying to advance science and who are trying to use good science and good data to question and debate what’s going on. We have, for example, people like Nobel Laureate, Michael Levitt, Oxford epidemiologist, Dr. Sunetra Gupta, Yale’s Dr. David Katz, who’s been on the podcast before. Stanford’s Dr. Jay Bhattacharya, Harvard’s Martin Kulldorff.
There are many extraordinarily respected scientists who are brilliant, who are putting forth good data, good logic, and trying to debate things and discuss alternatives to what’s going on, and yet some media channels are either trying to overtly sensor these people, or they’re not covering these scientific discussions and debates. They’re not covering these alternate views at all, or they’re labeling them and slinging insults, and labeling them as “fringe or extreme” or accusing them of having political agendas or even calling them conspiracy theorists, which is a very popular ad hominem attack.
A lot of people are using these days to people who are not actually conspiracy theorist of any kind but are actually just making sound scientific arguments. To give just one point of contact, I’ll just mention one thing myself here, before we get into the episode. I want you to see this visual here that I have on the screen. Basically, it is of world dominators, daily new cases in the United States.
Well, if you’re listening to this, what you see is fairly low levels through March, April, May, June level spiking a bit in July and August declining a bit and then now in the last couple months skyrocketing and that’s how the shape of the curve looks based on daily new cases of COVID. We have in the media reporting that reflects this. Basically saying, cases are skyrocketing, and we’re setting new records for cases, there’s new records being constantly set all the time and we have the media constantly publicizing how cases are exploding in numbers.
Now, I just want to show you, and this is really not even debatable, this is really just science 101, what I’m showing you here. I want to show you how badly misrepresented that kind of discussion is and what we need to do to challenge that kind of thing to have more accurate scientific reporting of the data. Now, this right here is from the COVID tracking project, and it’s showing daily number of tests per day.
The number of tests per day shows that back in March and April, we had about 100,000 to 150,000, maybe up to 180,000, by the end of April tests per day in the United States. What is significant about that is if you follow this line up over the months since then, over the last six or seven months, basically, the amount of tests that are being done per day has exploded to the point where it is now at 1.3, 1.4 million tests per day up from 100,000, 150,000.
The number of tests we’re performing per day has gone up tenfold. Why is that significant? Well, if you just report case numbers as an absolute number, rather than as a proportion of people tested, this is totally unscientific, it is a complete misrepresentation of the data. Again, that is just undebatable, it is just not good science, not good reporting of the data. Now, here, is this is from Johns Hopkins data reporting. This is how things should have been reported accurately to consider everything that’s on this chart.
What you see here, this black line is the percentage of positive tests so of the amount of tests, and the y-axis for that line is here on the right. The percentage of positive tests back in April, and May was around 20% up 15%, 20% in that range, and even above 20% up to 25% or so, or 23%. What has happened since then is actually a massive decline in the percentage of positive tests down to in the 3% to 8% range.
It’s actually been around that range hovering between 3% to 8% since June. Simultaneous to that, what you can see here is, again, that data on the number of tests being done, as I showed you here in that previous screenshot, and that shows you since March and April, the number of tests per day has exploded, it has gone up massively by 10-fold or more.
What’s happening here is as a result of that, even though the actual– As a result of them just expanding the total number of tests per day, the number of cases being reported has exploded dramatically and so the shape of the curve of cases is going up and up and up but the actual thing that’s going on is really more the shape of this black line. That is, again, the percentage of positive test. The portion of those tests that are being done that are showing up positive, that is what’s actually giving you an indication of how fast this thing is actually spreading.
Are there really new cases in other words or are the cases really exploding and spreading dramatically or are those numbers a reflection simply of how many more tests are being done? Without that context, that data is meaningless; the data on the number of cases is meaningless and totally unscientific to present that as an absolute number rather than as a percentage of the total tests being done.
Again, just to point out one example and there are many. There are literally, I’d say, well over a dozen of these kinds of things that are rampant that are going on right now, that are simply unscientific. There is no debating this, this is without question unscientific, and we need to have better, more accurate representation and portrayals of the data and of the science. Unfortunately, because of this kind of thing, we have a large portion of the population that is being misled to believe certain things.
I don’t mean misled in any sort of conspiratorial way, it could very well just be just the difficulty of reporting complex scientific data on mainstream media, and so they presented in an overly simplistic way and that results in people not having an accurate understanding of things. Either way, this is a huge problem, and we need more people who are willing to point this out and call for better science, better portrayals, and representation of the science.
This is only to give you one example of the kind of thing that you’ll hear about more in this podcast. Without any further ado, let’s get into the podcast with Ivor. Ivor, again, has done amazing work, synthesizing huge amounts of data and presenting that data to the world in a way that pokes holes in some of the narratives pokes holes in some of the things that are going on right now, and you like the example I just gave these inaccurate and unscientific portrayals of the data. In this podcast, we summarize many of his dozens of presentations on his YouTube channel.
For all of the specific studies and data and the actual visuals and screenshots of the research, screenshots of the data that have informed his views that he’s going to be summarizing here, I strongly encourage you to check out his YouTube channel, where you can find all of those videos. There are dozens of hours of his lectures where all the research is systematically presented on a number of topics like lockdowns, population immunity, PCR and antibody testing, antibodies, and many other key topics related to COVID.
Again, for references on specific data and studies being referenced to support his views, all the data is presented there. This interview is a long one at about two hours. We did our best to cover a lot of key topics. I think it’s honestly only scratching the surface. Let me also say that, of course, just like anyone else, it is perfectly possible that Ivor will turn out not to be 100% correct in his analysis of everything.
I also don’t think mine will turn out to be 100% accurate in every way, and I don’t think anyone’s, not the most respected epidemiologist in the world right now will turn out to be 100% accurate. How do I know that? Because many of the top epidemiologists in the world disagree with one another about their interpretations of the data, so they cannot all be right.
There’s really so much that we don’t yet fully know, so no one has “the truth”. I personally do think that Ivor has done among the best jobs of anyone in the world at synthesizing logically and scientifically analyzing and making sense of the world’s data on COVID. I hope you’ll enjoy this episode. I also hope that if you’ve developed an attachment to any particular politicized narrative of COVID science, that you hopefully go into this episode with an open mind, you drop the politicized version of things and open your mind to a very direct and honest attempt at logically and scientifically making sense of the data. Without any further ado, enjoy the episode. Welcome Ivor, such a pleasure to have you.
Ivor: Hey, thanks a lot, Ari. It’s great to be here.
How seasons affect infection rates
Ari: Let’s jump into COVID stuff. I thought first, we could start with some basics of curves. We’ve all seen these curves presented from the very beginning on TV. We had kind of the the shape of this curve and then we were told about lockdowns and social distancing and how this would flatten the curve. I think personally, that there are still some widespread basic misconceptions about curves. In particular, why are curves shaped like that at all? Why, for example, doesn’t a curve just go up and then continue to keep going up and just spread through the population and kill everyone and just keep spreading, until it reaches this peak of, I don’t know, 80% of herd immunity? Why does it not do that?
Can you describe the basics of why curves are shaped that way? What are the dynamics of why they go up and then why they come down on their own, irrespective of lockdowns and suppression measures?
Ivor: Yes, no problem, Ari. I think the Gompertz curve is now being used to describe the classic influenza rise, curl over and long steady fall, which we’ve all seen in Northern Europe, North America and elsewhere. Now, other regions will have different curves. They’ll have a long steady rise like, Brazil, Peru and a long tail off. That’s all understood from the work of Hope Simpson in the UK, on the Influenza transmission.
If we stick to the classic. The Gompertz, I believe, was coined by Professor Michael Leavitt, Nobel Prize winner and Advanced Micro biochemical modeling. He just found that the Gompertz was the best mathematical function to match us, but Gompertz was a mathematical function, rather than a viral thing. That’s the way it is. Why? Basically, when the new virus comes along, it actually shares a lot of its proteins with the prior family and SARS-CoV-2 is no different. It shares a lot of proteins with prior Coronaviruses. Our body has got memory in many cases, to recognize those. We’re not completely 100% exposed. A huge amount of people have got immune defenses ready to jump into action. We see that quite obviously when they track symptomatic index cases.
We had a study where a symptomatic index person was tracked through all their indoor, accomplices and family members. All older people, no masks and 85% plus don’t exhibit any problem. A lot of people just have mucosal immunity or they have innate immunity or they have T-cell immunity and memory from prior similar viruses. They jump in and nothing really happens.
The more immuno naive, who have less of that, they can get hit pretty hard or people who have immunosenescence aged or immunocompromised, like late stage cancer. That is sadly the case. It goes up fast, because the new virus sees a lot of potential as susceptible victims, very quickly.
Ari: That’s true of, obviously, SARS-CoV-2 COVID, as well as, every year there are certain respiratory viruses that come through the new influenza variation, as well as other viruses during a particular season, correct?
Ivor: Yes. New virus comes along, a strain of influenza. We know this from the vaccine challenges. A couple of years ago, it was only around 5% effective. They said, “Well, a new strain came in and we haven’t tailored those.” Yes, new strains come in and they find most susceptible people. Then you get a rapid seasonal triggering, usually. Then you get this rapid rise.
At first, it’s exponential for a couple of days and then it goes into power law and then it goes linear and then it curls over. Everyone’s wondering, why does it curl over? It’s just a mathematical reality that it begins to stumble over more and more immune people and rapidly, more and more people are immune and won’t really transfer. The curve just rapidly turns over. Then you get a long, slow decline as it mops up through the rest of the population, finding people who are still susceptible, but they just fade away.
The main reason the curve goes over and comes down is the passing of the susceptible, sadly. People will actually pass away-
Ari: This is the passing of the susceptible for people who don’t quite follow that. That means, at any given time in a population, there are people who are, maybe, near the end of their life already, who are have pre-existing conditions, who are already ill, things of that nature, who if they catch a virus, even like the flu that passes through every year, those people are susceptible to getting it and potentially dying?
Ivor: Yes. Getting it severely, and maybe, passing is also during the early phase of that, but they pass away, sadly, again. I have to keep saying sadly, because some people like me are accused of being heartless, but I fought for eight years to save people from heart disease. My credentials are pure. We have to be reasonable when we’re talking about this and stick to the science. We get all emotional, the science begins to disappear.
That happens and then you’ve got community immunity building. The people not so affected, they build the T-cell immunity and mucosal immunity and they build the memory, they recover and now they’re sorted. That happens, then you get this kind of herd community immunity building as the curve falls. Then you’ve got the seasonal effect. As we come into April of May in Europe, the season is changing and it’s more challenging for the virus. Humidity shifts and temperature and UV come into play and raise human immune function. You’ve got all these other seasonal factors make it hard on the virus, and that can hasten the curve to end.
It’s important to note that if you get a rise in the season and you’re very close to the end of the season, you may only hit a smaller amount of your population. Then after the summer season’s over and you head into the winter, you’re going to get a bigger hump than the guys who kind of pass through more fully the first time. Either way in [crosstalk]-
Ari: You’re saying that’s relevant to COVID, the COVID scenario right now?
Ivor: Any of them really, yes, to be honest. We see some countries in Europe that had a very soft first hump, but they were heading into the summer season, and it missed its chance, in a sense.
Ivor: Because of lockdowns?
Ari: No, not because the lockdowns, because the season changed before the virus made a very big impact. So the virus was stymied by the season changing into summer.
Ari: Got you.
Ivor: It’s another way for the curve to be more moderate, if you just reach the season before it got going good. We’re seeing some countries now that have a substantial winter resurgence, as big or bigger than the first pass, but that’s because they never really had a first wave. It’s not a second wave. It’s just the first wave never really happened seasonally. That’s a little nuance, but that’s why it turns over.
Three main things, passing of the susceptible, development of community immunity and moving into a season that’s less favorable. That dictates the curve, the lockdown, very, very little.
The drastic changes and rejection of the pandemic guidelines
Ari: Okay. I want to emphasize this because I feel like there’s still widespread misunderstanding about this. Every year and we’ll just talk about flu or the various viruses that cause flu for a reference point, every year during a particular season, we have viruses that sweep through the population and cause tens of thousands of deaths. For example, in the US, between 30,000 to 80,000 deaths per year, typically from flu viruses. I’m sure the numbers across Europe and Ireland. The curve of those viruses is a curve that goes up rapidly, hits a peak, and then comes down on its own. This is important with no suppression measures with no lockdowns, with no masks in place. The curve behaves that way. I mean, the virus behaves that way on its own. It comes it sweeps through the population. It goes away on its own.
The reason I emphasize this is because I feel there’s a lot of people right now, at least, in the United States, who are under the impression that the only reason a virus will go down, is through suppression measures, through lockdowns and masks and who are looking at the data in various countries and seeing it going down in places and saying and drawing the conclusion, the only reason a virus behaves that way is from lockdowns and masks. Is that not accurate?
Ivor: Yes, that’s a complete fallacy. Lockdown may slightly attenuate or slightly blunten te curve, it may bring it in a little sharper. It may, but the reality is the curves. I have research papers published 10 years ago on the Spanish flu and I can take the Gompertz curves from those flu, any flu, and I can superimpose it over what happened in Europe this time or North America and Northeast. It superimposes perfectly. This is a phenomenon that’s a million years old, long before we copied China and did lockdowns.
People need to realize too, that the WHO guidelines were absolutely crystal clear on this in November 2019 publication, decades of science. No quarantine for pandemics. Once the virus is in the country, no point, just no point. The Irish pandemic guidelines, I downloaded the same thing. They also say the test and trace, there’s no point once the virus is broadly in a country. These measures are only if you’ve got an Island nation, and you’re actually attempting to keep it out.
Once it’s out and about, and we know in America, and in Europe, first victims are back in December 19 January. It was traveling all over for months at a higher value. Then seasonally it triggered. You see the Northeast of America, New York, very sad, triggered very sharply and did its thing before the lockdowns were put in. That curve was baked in. It’s clear in the data. Then we see the Southern US behaves more like Mexico and seasonally regionally, it’s expected to have a long steady rise and fall over the summer months, which is exactly what it had. Same as Peru and Brazil.
All of this, the research is all there. It’s just in 2020 on lockdowns being used, on masks, on tests and trace and on seasonality and on many other things, someone at a high level or everyone, through mass group thing psychosis, decided to take every shred of knowledge we have built over a hundred years and throw it all in the trashcan and copy China. Its important people realize this, I’m not saying China created this storm mischievously, but the reality is, as an empirical scientist from the outside, in February and March, I was shocked when they were clearly decided to copy China and throw away everything else. I thought that’s not normal, because usually they’re always attacking China and criticizing China. Why are they all suddenly copying China? So there you go.
Ari: This gets into a potential rabbit trail that we could go down of why, and I’ve spent a lot of time thinking about that and asking that question and seeing the same thing that you’re talking about, which is this gap between what we’re doing and what the science has said for the last several decades. I saw there was one systematic literature review on the subject of lockdowns. It was in a British Medical Journal, and it was called, Social Distancing, Do it well or not at all. Meaning to the point of what you were just saying, lockdowns can legitimately be done to good effect in a scenario where the virus really hasn’t yet entered the population, or it’s entered and there’s just, maybe, a few cases or a few dozen cases, maybe, a few hundred cases at the most. Then you lock everything down, completely let that virus die out, and you successfully suppress it.
Then they said, if you try to attempt those kinds of suppression measures, when it’s not possible to suppress the virus, once it’s widespread in the population, then it’s counterproductive. That they were very clear. The science was very clear that that was the case. To your point, it’s a huge question mark, in my mind, why has so much of this science been disregarded and thrown out the window, as soon as this pandemic hit?
Ivor: That’s it, and the WHO guidelines same as that paper. There’s another US paper, I think it’s in the Journal of Bio-terrorism 2006, clear as day. Exactly what we just said and the Irish pandemic guidelines, and I think everywhere in the world. They threw out everything. You could be charitable, very charitable, and say that simply fear got the best of them, or they lost their nerve and they saw Italy. Italy was very aged people, and 98.5% had multiple comorbidities. Even then, we saw the Diamond Princess, the elderly people on the cruise ship, we knew it was going to be like a bad flu equivalent, roughly. It wasn’t going to change the world, be sad, but it’s not going to change the world. We knew from the Chinese data that it was 10 times worse, turned out to be hundreds of times worse in elderly.
With all this data that even when Italy had a very difficult period for a couple of weeks, you could still say, “Well, let’s look at the numbers.” You could say they just lost their nerve for some reason. I think the real problem was Imperial College, London. They came out with predictions of 520,000 deaths in England. If you don’t do the China measures and they were out by a factor 12.
Ari: Yes, I think they were 2.2 million in the US.
Ivor: Yes, that was the IHME. Imperial College in England sent Europe into a frenzy, Italy copied China, the WHO started pouring petrol on the fire and told them, “Yes, lock down guys, lock it down.” The country went a bit mad. Then England said like Sweden, “Hold on a minute,” but then the Imperial college modeling terrified them, so they locked down. There’s a domino effect of panic and psychosis that spread everywhere, and then the media went insane.
Sweden – why have they taken a different approach?
Ari: And peer pressure of conforming to what other countries are doing. There was also the attacking of Sweden started very early too, that Sweden was a bunch of psychopaths who were irresponsible and unethical in their response when, to your point of what you were just describing, the Swedes were actually the ones, as I understand it, who were most closely following the established body of evidence.
Ivor: Absolutely, and to be honest, I’ve said it recently, the only thing the Swedes did differently was they actually followed the Canon of science and the WHO and worldwide pandemic guidelines up to November 2019. It’s not like they did something crazy or funny. They just said, “We’re sticking with the established science and all of our modelings says that that’s the right thing to do,” but you’re right. They got excoriated. They got attacked and there was a jealous anger, and terror from the media and the governments, that if Sweden are correct and we’re all destroying our societies maybe for nothing? Then that’s going to be really bad.
The instinctive response to that was to bully-attack and scream to try and get them to lock down because everyone knew if they locked down, it may not do much, but if they’ve locked down, no one will ever know that it didn’t do much, but Sweden held. Now, they’ve proved the point. It’s the same curve, better than the UK. Then the last few months coming into winter, way lower mortality than most European countries. They won in the epidemic and they won on the far end coming into this winter win, win by following the science.
Ari: Unfortunately, Sweden, as they’ve acknowledged publicly they did not do a good job of protecting their elderly care facilities, where something like 80% of their deaths, actually happened. In a population of 10 million people, they had about 6,000 deaths and almost all of them were in elderly care facilities. Another way of putting that, is of those 6,000 deaths, something like, I think, less than a thousand of them, was actually in the general population, the non elderly population. Is that accurate?
Ivor: Yes, that would be roughly accurate. Maybe 1,500, but then a big chunk of that 1,500 were Somali people, extremely dark skin living way North in Europe. They have a profound vitamin D challenge and that’s been the thing linked most strongly to poor COVID outcomes. Sweden saw in the first few weeks in Stockholm their city, a hugely disproportionate number of non elderly, where Somali, immigrant people, which was also sad because they could have been really helped, but no one cared. That’s Sweden.
Sweden’s high race, they said that they didn’t protect, but to be honest, England had a higher rate than Sweden and they’ve similar urban density. England was worse and England absolutely disaster and the care homes and they did do the lockdown. Every time you make the compare, Sweden’s hit was based on the fact that they had 4,000 deaths short from the prior 18 months seasons. They were running two soft seasons in a row. There were all these susceptible and even more aged people that normally would apply, because they would have passed in a prior season.
The prior season [crosstalk] is a verity, is the biggest determinant in Europe of how hard you get hit and Sweden got hit at that.
Ari: Okay, Ivor, I want to come back to that point because there’s some good stuff that you have to show on that and I think it’s worth emphasizing that and elaborating on that, One more point on the curve, just the concept of flattening the curve. I think being charitable I think it was certainly very reasonable, at the very early stages of the pandemic to say, “Oh, we’ll do two weeks.” Here in the U S it was two weeks to flatten the curve, initially and it turned into, I don’t know how many, 30 weeks or something like that. I think two to four weeks of lockdown before we knew what the mortality rate really was, how deadly this virus really was, I think something like that is very reasonable.
Then there was this conflation of flattening the curve, slowing the spread, which was originally conceptualized and the science supports this, to slow the spread such that you avoid a period of hospital overwhelm and potential increased deaths that would result from people not being able to get treatment. Which is a legitimate a real concern. The challenge as I see it, or the problem, is that this then became conflated with a suppression strategy, where people felt that by slowing the spread that is equating to less people dying in general, regardless of a hospital overwhelmed scenario. I’ve seen many epidemiologists comment on this, that is just wrong and it’s without scientific support. Yet, that has become a widespread belief in the population, that almost like just by continuing lockdowns and by wearing masks, the virus will just go away. We will suppress it. That is just a complete misrepresentation and misunderstanding of the science. Is it not?
Ivor: Yes. That’s ideology, that’s religion that bears no relationship to science. I would have to add that the WHO has been driving that impression. It’s not just the stupidity and ignorance of academics and politicians and the ignorance of the public getting that idea and then demanding the politicians to protect them with lockdowns. All of that happened, but you’ve got to also look up a little and realize the WHO has been pushing that message the whole time. Are they also completely ignorant of pandemics and epidemics? Maybe they are, or do they like being in the limelight? We don’t know, but we won’t go there. You’re absolutely right, that’s complete fallacy.
What’s more, there’s two published papers now, one in the British Medical Journal and one pre-print, that I’ve done advanced analysis and showing quite elegantly, that because this disease really hits the aged, very uniquely, strongly hits the aged, when you work out the herd immunity and the dynamics, it turns out if you do succeed in suppressing and slowing and protecting the hospitals, if you do succeed with lockdowns, you will end up at a higher death count, overall for COVID-19. I’m not talking about lockdowns causing cancer deaths, suicides, there’s all that blood on the hands. That’s all extra. A higher COVID-19.
It seems counter-intuitive, but by slowing herd immunity in the younger, healthier, who will not be affected, you disproportionately put the elderly at risk in the next season and later. What you really need to do, if you follow the science, is limit the mobility of the elderly and manage them and help them support them. They’re already low mobility. You’ve got to lower it more, but the high mobility healthy young, lowering their mobility, actually relatively, increases the mobility relatively of the elderly and the at risk. You make it worse.
Ari: In other words, the more that the virus spreads in the young healthy part of the population, like for example, children who are almost completely unaffected by COVID, the more that immunity builds up in that part of the population, the more it confers protection to the older part of the population that’s susceptible. This is a key point that I think a lot of people miss about someone with your perspective, which I share most of your views. They see it as like, “Oh, you’re opposed to lock downs. You’re not in favor of these suppression measures. That means you’re a psychopath, and you’re putting everybody at risk.” People don’t understand that actually by the young healthy part of the population going back to normal, it actually confers protection on the people who are susceptible to dying. It’s not just this psychopathic antisocial thing. When viewed in this way is actually, the best way to protect that part of the vulnerable part of the population right now.
Ivor: Yes, and it seems counter-intuitive, but it’s actually elementary. It’s actually a very basic physics and science and this is the way it’s worked forever. I’d say to those people, sadly, and to the scientists and government people who push that agenda, and that a message, if they want to see a psychopathic killing of the elderly, they need only look in the mirror, because they are the ones perpetrating it. I hope that they don’t know it. I’m sure that they don’t realize it. They went for the easy intuitive answer, which in complex science for allergy epidemiology and immunology, physics engineering. The easy intuitive answer is usually wrong. That’s the way science works.
I’ve been through 30 years of complex problem-solving, and I’ve seen myriad engineers fall for what appears to be the obvious, the humidity is opened the summer, the plastic parts are cracking and they are so wildered, but it’s not that, It’s actually more complex. These people are parroting just a completely false and simplistic paradigm that’s incorrect, but by God, there are a lot of them. A lot of them are holding high positions. They are succeeding and putting granny at risk, while shouting at other people that they are putting granny at risk. It’s very tragic, isn’t it?
Soft and hard seasons – how they have affected the COVID-19 mortality
Ari: Yes, absolutely. The way that people have turned on one another and the way that the science on this has been so politicized, is extremely tragic. I want to come back to what you were just touching on with the soft seasons and the idea of which countries have been hit harder than others. Big picture context, I think, is really important here. This is, I think, what a lot of people are missing. They’re just looking at things in isolation right now of what’s happening in this moment, without putting it in the context of what happens in previous years.
You presented some really fascinating data that looks at basically a chart of average mortality across the year and you can chart in previous years have the previous flu seasons, respiratory virus seasons caused a big increase above what is average and normal. Whether those prior seasons, how what happens in prior seasons? Did they have a really bad season or a soft season? How that influences COVID. Can you describe that data for us?
Ivor: Yes. Luckily this one is actually quite simple. Even the granny-killers who promote lockdowns will, maybe, understand it. It’s facetious there. Basically you can have soft seasons, obviously, or hard respiratory seasons. Europe in general, from the excess mortality database, 2019, we had 140,000 excess mortality. A hump during respiratory and that’s around November, through to around April is the season. You always see a hump in excess. 140K and just for comparison, 2020 is concentrated into Corona in March, April, and it’s 185,000. It’s around 35% worse, than 18. It’s not a huge amount of different. We know from all the public science, we have around 12 papers that looked at the data and the lockdown didn’t really affect that. That’s the compare,
2019 was a soft season for Europe. That’s part of what made 2020 high. Because if you store people who normally might get hit by a bad flu or other viruses, obviously you’re building up a store of people who would have passed and they’re going to be the most exposed, susceptible people on the planet. When the tough fires come along, then there’s obviously going to be a very rapid judgment, if you will or a lot of people are going to pass. That’s what happened in Europe.
Now, Sweden, we’ve got 18 countries and you see the relationship around Asia Nine got hit hard. Those Asia nine, invariably, had got this low soft 19 and early 2020 season with very low mortality, very unusually low. Then they get a huge spike, as I described. Perfectly empirically, on the other side, the ones that got very little hit, they actually didn’t have any low mortality in the previous two years, they had normal seasons.
Ari: The countries that were not hit extremely hard by COVID, what happened in their previous years?
Ivor: Rather than having soft seasons or lower than expected mortality, they had normal mortality or even high mortality, relatively. It just matches up perfectly for nearly all the countries. Ireland was similar. We had a soft 19, then we got a fair spike. You see, it’s not the only factor, but I’d say it’s the quarterback factor for how hard you’ll get hit, is the prior two years mortality rates. If they were low in the last two years, relatively, then you’re going to get hit hard. If they were high or normal, you’re going to get hit soft. That’s the biggest factor. No one’s talking about it. It’s not sexy, but it’s the biggest factor.
Then you’ve got population health of the elderly, vitamin D stages, a bunch of other things that then decide most of the rest and then lockdown messes a little with the data.
US vs. Japan – the impact of metabolic health on COVID 19
Ari: I think the metabolic health thing is also a huge factor. If we contrast, for example, the US and Japan. Japan did pretty minimal lockdown measures. They had one of the most lax responses, and yet they had very, very low mortality from COVID, despite actually having a very aged population. Interestingly, the US has one of the highest obesity rates in the world. Japan has one of the absolute lowest obesity rates in the world and obesity, next to old age, seems to be the single biggest risk factor for a severe COVID.
Ivor: Yes, and obesity plotted for the countries of the world. It’s a big cluster plot with a very strong, positive relationship. Prior season, same lockdown across 50, 60 countries of the world, no relationship between lockdown severity and deaths per million that do occur. In fact, more lockdown, generally means higher deaths per million. Not very significant, but it goes the opposite way for the reasons I said.
Vietnam, Japan, and a whole bunch of those countries, they have a couple of advantages. The health of the aged, metabolic health, is way higher. It’s not the healthy or young people, because Vietnam and Japan might have a lot of fat diabetic kids or teenagers, but they’re not really at risk because they’re young. It’s all around the metabolic health of the aged.
Japan is fascinating. A killer study came out a couple of weeks ago, and this should be really interesting for people. They got a few hundred people and they track them in Japan, through the hump of their case epidemic, but they had nearly no death, like you said. They tracked a bunch of people and they had 5% antibody positive coming into the issue.
They kept testing those people and that group went up to 45% antibody positive, nearly 50% antibody positive, for so COVID too. Then they all started losing their antibodies, which is normal. You make antibodies, but it’s your T-cells that keep the memory and you can knock out antibodies later next time. You do have long-term immunity, 17 years in one study. Notice how half of them became antibody positive, because they kept testing them and watching. The death rates stayed tiny. It did spread through Japan, massively, clearly from that study, they just didn’t get the death.
It’s to your point, if you have metabolic health, the only other thing I’d add is in Japan and these Asian regions, a lot of exposure to prior Coronaviruses and even science warn, could give them a lot of immune memory. Therefore, you’d see the antibodies generating, but they jump on the virus, their immune system is much quicker and be relatively less runaway train, which leads to a death.
Health of the aged and prior across immunity to other coronaviruses, the two of those covers all those areas. Japan only around 20% are wearing masks, a lot of the time. It’s nothing to do with the masks. They all want to say it’s the masks. It’s nearly nothing to do with that.
Ari: I actually saw an article headline the other day saying that cases are surging in Sweden, in anti-masks Sweden, something to that effect. What the article implied was that cases are surging in this one country that is not using masks, but it’s ignoring the fact that cases are also surging and in fact, surging much more strongly in many, many other European countries that have masked mandates. There’s just this perpetual smearing and attacking of Sweden, that is just so deeply unscientific and is not aligned with the evidence and is misrepresenting the facts in this effort to attack Sweden.
Ivor: Massively misrepresenting. It’s fraudulent because Sweden are the lowest death rate the last few months and the lowest case rate in Europe practically. They have no masks and they’re living almost completely normally for several months. I have the photos. Even during the epidemic on March the 6th, CNN went in with camera crews and they were shocked. They interviewed elderly lady getting her hair cut, the hairdresser was all around her head, no masks. They had people in cafes everywhere and the Swedish government said, follow the guidelines. One meter apart in a restaurant, no crowding, wash your hands, stay at home, if you have symptoms.
Sweden implemented the proper Western pandemic guidelines. If you account for prior seasons on other factors, like care homes, they got the exact same performances as everyone, counting for those factors. Then they became the lowest in death and cases in Europe, as we came in across the summer and into the winter and they never wore masks. They proved beyond any doubt that the masks and the lockdowns are essentially futile.
They prove it. Karl Popper evidence-based medicine grandfather, he said that you can have any amount of supporting evidence for a theory, you can have 500 bits of supporting evidence. It’s no good. One contradictory piece of evidence destroys a hypothesis. Sweden destroys the lockdown and mask hypothesis. One negative piece of evidence is more powerful than a thousand positive pieces.
Masks – what purpose do they serve?
Ari: Karl Popper also said the defining characteristic of science is that its hypothesis must be falsifiable. What seems to be going on in the world today, and Sweden is this lone counterpoint. What’s going on is regardless of what’s done with lockdowns and masks, you can point to a hundred examples of where lockdowns have been implemented as you’ve pointed out in your many videos, lockdowns have been implemented way before the virus even hits, masks have been implemented before the virus hits. The virus still comes and sweeps through the population in basically the same way as it does in places without those measures and it seems unaffected by that.
There is abundant evidence to falsify those hypotheses. Yet, it seems a majority of the population and world governments want to operate in a paradigm where they’re unwilling to allow these hypotheses to be falsified. No matter what happens after lockdowns and masks, whether the virus goes up or down, if it goes down, it’s “Yay. The lockdowns and masks were a success.” If it goes up it’s, “We didn’t do the lockdowns and masks well enough.” They’ve set up the rules of this game to be deeply unscientific to the point where they cannot be falsified no matter what the data actually show.
Ivor: Absolutely. Ireland went into full lockdown when already the infection rate was curling over and coming down and the hospitals had flattened. After that point, they put us into full country lockdown and destroying the economy and society. The data was clearly flattened off and going nowhere. We only had seven or eight people per million people in ICU with a positive swab, not even necessarily driven by COVID. There is no rationale. It’s not just only scientific; it’s anti-scientific now because I sometimes called things unscientific if they’re bad science, I keep the term anti-scientific for when you actually offend science. They’re deep and anti-science for months.
The reality is with masks, as soon as they came in, I knew we were heading for a problem in the world because whatever your belief on mask efficacy, and we have four decades of science saying, it’s not worth it guys, if anything, but forget about efficacy. To bring them in at the start of a massive epidemic you could say like the lockdown, you just can’t take the risk of not throwing everything at the wall. They brought them in, in the mid year, in mid-summer when the ICUs were empty, the hospitals were empty. There was no question in this universe, but they would remain empty until October months away-
Ari: You’re talking in Europe?
Ivor: -they suddenly brought in mandatory masks.
Ari: In Europe and Ireland specifically?
Ivor: Yes, all over Europe together. The WHO just said, “Hey guys, I think you want to mask those boys up, boys and girls” and all the countries within a week put in laws masked everyone up, massive social change, zero signs.
Ari: You’re saying after the virus had already declined massively.
Ivor: Long gone. Exactly what we said by the end of May coming into June, this virus ICU hospitalization and mortality will be gone until next winter. That happened. I was gloating in June and they were slowly taking away the lockdowns, but you could tell they didn’t want to, they wanted a form on plan. I began to suspect. They want to get to the winter keeping the fear alive to keep this whole thing going.
While I was thinking that thinking, “why aren’t they taking out the measures from the end of the summer and allowing safe spread to get more immunity to protect granny next winter,” but they didn’t want to take out the lockdowns. They were slowly reluctantly taking out measures. I said, “this is a farce.” Then they brought in mandatory masks. Can you imagine how I felt? That was a horrifying moment for me because I realized then it wasn’t just unscientific. It was pure anti-scientific now and it smelled of an agenda.
I suspected, and I still do to this day, that they realized that everyone was thinking, “Okay, well this was a seasonal virus and it passed until the next winter,” and they couldn’t be having that. They brought in masks mandatory so everyone could feel there was still a crisis and that got them through to the winter. Then they began to get some deaths back. How cynical is that? Cynical, I think it’s true.
Ari: We’re again, encroaching on this territory of why some deeper mystery that involves speculative elements of why there seems to be these things that are either unscientific or anti-scientific, that seem to be driven by some kind of agenda. Unfortunately, we have to talk about that. You have to enter the realm of speculation, and then you start getting into being having insults thrown at you, you’re a conspiracy theorist.
Again, we must point out the reality that what is being done, there are so many dozens of examples of what is going on in the world right now being either deeply unscientific or anti-scientific. For anybody who’s science-minded, who’s looking at the evidence objectively, these questions have to come up and you still have to be very careful about any speculation and any conspiratorial thinking and all of those things, you absolutely need to be careful with what kind of speculation you do, but these questions should be apparent when there’s so much stuff that’s anti-scientific going on.
Ivor: There has to be because 20 years ago, there’d be no talk of conspiracy theory because Watergate and a load of other things happened, and there were real conspiracies for various parties had interests and strategies and they didn’t make them to public. They tried to execute them quietly, but we had investigative journalists, who would go digging, but now investigative journalism has gone and anyone who acts like an investigative journalist gets called a conspiracy theorist.
They’ve prepared the ground very well to stop any questioning of these questions. When I talk about this, I always have a rule. I will only refer to potential drivers of some of this madness that are on the record and ultra public, that anyone can look at and that’s in plain sight. I would say that the WHO has clearly driven a lot of this agenda. They have their reasons. Maybe it’s their organizational power has exploded during this and they don’t really want to see it go away and be treated like a last year’s flu.
Then they just go back to being nobody. It could be my guess at that. You might say they’re very involved with pharma and there’s a massive payday coming if this thing stays a crisis, and there’s a massive payday lost if it becomes a seasonal flu. You could look at the World Economic Forum that have putting advertising, even in the UK and Ireland on bus shelters. You know the bus shelters? The Great Reset is advertised on bus shelters.
The WEF guys, they’re huge powerful organization worldwide. Every corporate practically is supporting it. They have said and they have published pamphlet after pamphlet and on their website, that Corona is a huge opportunity to reshape the world in terms of environmental, in terms of tracking, tracing, and moving away from cash money to plastic money, moving away from hand labor to automation, but they’ve published it all.
Ari: It’s on their YouTube channel and the world economic forum YouTube channel.
Ivor: I think it’s weforum.org or something, but you go there and it’s like you say, “Wow, these guys are serious dudes. I think they’re 20 years building towards this.” I think Mike Eaton, Pfizer pharmaceutical top expert, who’s saying what I’m saying trying to help get some science out there. He thinks it’s a opportunistic collaborative phenomenon that there’s so many organizations where this is a huge opportunity, whether for business or strategy or getting in health passports getting in strategies and plans that have been sitting for decades.
Now there’s an opportunity. You just have a lot of powerful organizations and no one made the virus. It’s opportunistic. It’s like, wow, everyone’s stopped. There’s a big virus. It’s just a huge opportunity, a bit like disaster capitalism. You remember in, was it New Orleans and then they took the opportunity to get rid of all the public schools and they privatized it all. You had the tsunami in Indonesia, it was a famous example. You had fishermen who had lived for hundreds of years along the coast fishing under huge pressure from corporate to build massive hotels because of beautiful coastline.
The government couldn’t quite let them because they said, “These are indigenous people.” It was a bridge too far to throw them off the land. Then the tsunami came and within six months, there were cranes all along the coast. All the fishermen were inland five miles and their jobs were gone. They’re working like delivering pizzas or something. There’s always opportunism and you can only really get a big surge forward when something big happens, otherwise, no one will support you.
Ari: Just as another example that’s much more similar is the 2009 swine flu. There was similar scare and publicization of all of the data around why the public should be in fear of this new deadly pandemic. Tons of money, hundreds of millions or billions of dollars got poured into pharmaceutical companies to make vaccines. Then the virus, the pandemic never materialized. Those companies did still make hundreds of millions of dollars from the fear and made a lot of money on those vaccines, which also turned out to cause narcolepsy in a huge chunk of people and cause permanent side effects because it was a rushed vaccine that was not thoroughly tested for safety. Interesting parallels there.
There’s also been European I think, some prominent German scientists who are epidemiologists and public health experts, who have written articles about the links between pharma and the WHO and how some of the same people who– Basically major conflicts of interest between people working both in pharma and the WHO. It’s interesting opportunism there but even to broach any of this line of thinking, you now have people, “Oh, my gosh, Ari is a conspiracy theorist, Ivor’s a conspiracy theorist.”
It’s like, the way that they’ve set up the rules of this game right now are either you accept the common narrative, which is a deeply unscientific and anti-scientific narrative. If you are a highly scientifically literate person, and you are actively pointing out the flaws in the narrative, and where the science doesn’t match up with the policy, then you’re being labeled a conspiracy theorist. It’s so interesting that the people who are the most deeply scientific, who are doing the most critical thinking and following the science most closely, are now being insulted in this way.
Ivor: Classic. I predicted a month ago and it came to pass. Just like I told people on Twitter in September, once I realized what they were doing with the masks to prolong the fear, and it is analogous to swine flu, only this virus was tougher and it had more legs for sure but same thing. I told people in September, I said, “Guys, mark my words, I won’t delete this tweet, you are going to see lunacy that you would not believe come October and into November.” That’s exactly what happened. I knew they were holding out for the winter. I knew it. It’s obvious.
If people want to look though, no conspiracy, I always send people to Spiegel, S-P-I-E-G-E-L. It’s a mainstream German newspaper. Their 2010 article on the swine flu debacle goes through everything in detail. It was investigative journalism, and 30 top pharma reps came to Europe and met with the WHO and they hammered out an agreement to lower the bar for pandemic. It basically didn’t have to cause a major impact, it just had to be a virus that’s spread multiple countries.
Ari: They changed the wording of how a pandemic was defined from-
Ivor: It could be anything you want now.
Ari: -it was something to effect of rapidly spreading virus around the world that is killing large numbers of people. That was the original definition of a pandemic and they changed the definition of pandemic, they eliminated the part about killing large numbers of people. They just said “a rapidly spreading virus across the world.”
Ivor: Basically, afterwards, I’m maybe slightly exaggerating. You could have a rapidly spreading virus that gives everyone a sore little toll. Technically that would not breach the guidelines now. In the old days, 2007 no way, it had to cause major death and societal impacts. Not based on lockdown, because they knew you don’t do lockdown back then. It itself would be so impactful that people would literally start shutting their doors and cause societal impact.
In contrast, this virus, which is 35% more mortality than 2018, and certainly the same as the year 2000, that’s it. All the way through the epidemic I was asking people, “Do you know anyone who knows anyone who knows anyone who died? That’s three degrees. No one because they were all in care homes.
Ari: I do know of someone and it’s one of my good friend’s mother who was 87 years old with pre-existing conditions. This is important because, and she wasn’t in elderly care home. Important because that is really the demographic of the person who was the most susceptible to dying.
Ivor: That is an important qualifier, which I gave at the time because I knew an elderly woman who certainly died. I know a doctor in January, both his parents died. One was 86; one was 90 in care homes. They died in January. He said it was certainly Corona. No question. Those are blips of deaths but then the virus triggered properly in March. Outside of care homes, our elderly are profoundly moribund. Do you know, and no one knew anyone. All during the lockdown, my brother actually worked it out he’s an accountant. He’s not technical; he never watches my technical stuff. He said to me in April, he said, “Ivor.” On the phone, “Is this a load of shit?”
That’s the way he put it. Sorry about the language. I said, “Yes, how did you know that? Are you watching my videos, my interviews?” “No.” I said, “How do you know?” He says, “Outside of so and so on the care home, I don’t know anyone who knows anyone who knows anyone who died or even to be honest, had a bad case.” He said what kind of epidemic is that?” He says, “There we go.” I said, “Is that it?” He said, “No, another thing.” I said, “What?” He said, “The lockdown stuff.” He said, “It’s not that because I’ve gone to all the stores, the essential stores, the supermarkets, grocery stores, all over the area, because I’m bored.”
He was working from home and he wasn’t busy. He kept going out to the store to get something. He noticed that no one in the stores working in the stores with no masks indoors. They’re 8 to 10 hours a day exposed to everyone flowing in. They should be dropping like flies, no one was sick. He began to ask them, and he began to ask the elderly grocery workers and the overweight ones, especially because he knew they’re the one who got a blank all across Dublin. He said, ” They’re not locked down and nothing happened to them, so locked down can’t work either, so that just means that the whole thing is like a bad flu and it’s mostly hitting care homes.” I said, “There you go.”
The actual data on the COVID infection fatality rate
Ari: There are some people who are listening to a few. I know that there’s going to be people triggered by when you say it’s like a bad flu. There will be people who immediately rush to attack you or attack me for not challenging you on that. Let’s be specific on what the mortality rate is. I know it differs by age group, but can you talk about, briefly describe what the mortality rate is, and then also what the actual excess death looks like, compared to past years. You’ve mentioned that in passing a few times. To be clear about what the stats actually are so that you’re not accused of saying, “Oh, this is just flu.” Have people attacking you for that.
Ivor: I agree, Ari. The other thing, it’s important to say “bad flu” or “severe flu,” because saying it’s just like “a flu” is not fair. A bad flu comes along every few years. You’re only comparing this to being in the envelope, or not a mile off a bad flu, not comparing to an ordinary flu. The best thing is Professor Ioannidis the most cited scientist, I think in history out of Stanford, John Ioannidis. He published his update to his serology studies and now they have all the data. The WHO last week mounted it on top of their evidence base for COVID. It’s 0.23% is the infection fatality rate they estimate and it will be lower– [crosstalk]
Ari: Across all age groups?
Ivor: All age groups. Below 70, it’s 0.05%. I think that’s a high estimate because they never can know all the infected, but another way of looking at it is, the WHO stated the other day and I believe they’re correct, that there’s around 780 million people or 10% of the world’s population that have got it but we know there’s a million that passed. They themselves are setting the infection fatality rate at 0.13%.
Ari: What’s the flu?
Ivor: The flu is interesting. The flu, they used to always say it’s 0.1% but now they’re beginning to backtrack and deny that figure because it’s awkward because this is one 0.1% something. Now they’re saying, well that was an estimate. They never really got it accurately measured because no one was interested. It’s probably a bad flu is around 0.1%. It’s in the ballpark that’s why I say it’s in the ballpark. I’ll tell you one thing with certainty, if you went back to a bad flu year like 2018 in England was bad and 2015 was bad in European countries, if you went back then and you did a few things, I’ll tell what you’d see, for the first time in human history, the WHO told all governments and they did it, to change utterly the death cert system.
They said, instead of now having a stage four cancer victim who’s passing away from organ failure, instead of calling it what it is but you’ve got a positive swab and you make a little note saying, also was carrying SARS and influenza A. That’s over. We want you to call it COVID-19 and forget about the cancer bit. That’s the biggest change in history in death certs and it’s an enormous one. That’s one thing. Basically, within 28 days of having a positive swab that might be irrelevant, if you die even if you fall out of the sky, land on the tarmac, you’re a COVID death.
Now, we’re also hyper tested, everyone knows hundreds of millions of tests, we’ve never done that before. If you go back to a bad flu year and you do that with the death certs and you have a hysteria and you hyper test everywhere, you’re going to see a massive infection fatality rate, right? Some bad flu years you might see 0.2% or more. We never did this before. [crosstalk]
Ari: Just to be clear, there’re some people who hear this and they’ll be like, “Oh, he’s saying the virus isn’t real it’s all made up.” You’re not saying-
Ivor: Oh, no, it’s real.
Ari: -the virus isn’t real, that it’s absolutely real, it’s killing a large portion of people, it is on average more deadly than the typical flu. There are also so many layers that make it difficult to actually know the true numbers of deaths. There’s also a context thing that is super important here, I think. In the United States, we’ve had about 1,000 people dying per day and I often point out the context that, let’s say this is around 6,000 or 7,000 people per week. This seems like a huge number and then I point out to people, you understand that every week, normally we have about 55 to 60,000 people dying in the United States every week.
Understanding herd immunity
Ari: I want to chat about herd immunity right now. This is a very controversial topic. I’ve actually done something interesting over the last eight months or so. Literally every other day for the last eight months, I’ve done a Google News search for herd immunity. I don’t know if you’ve ever done this, but what that brings up without fail every time you do it is a long list of articles saying, essentially, in different words, we’re nowhere near herd immunity. Herd immunity is a fantasy, is a dangerous fantasy, it’s psychopathic, it’s going to kill us all.
We’re only at 6% of the population, 10% of the population that has gotten this, and you need 60%, 70%, 80% of the population for herd immunity. Near as I can tell, there is a complete full blown war on this concept of herd immunity. I’m curious what your thoughts on that are because there is this portrayal that anything less than this 60 to 80% threshold is no scientist supports that and yet, you and I know that there are actually lots and lots of scientists that are saying that it is very likely and we have lots of lines of evidence suggesting the threshold is considerably lower than that. Can you talk about what you think the threshold for herd immunity might be and what some of those lines of evidence are?
Ivor: Sure, Ari. I’d start off by saying, how many of us were de facto immune to start off with, even before the new virus came in? SARS-CoV-2 shares a lot of proteins, antigens with prior Coronavirus family so our body’s immune system recognizes many aspects of SARS-CoV-2. There’s never truly a new virus. As Professor Beda Stadler said, and he’s the emeritus professor of Immunology in Switzerland, he’s the Fauci of Switzerland, and he’s called the Vaccine Pope because he developed some of the early vaccines.
Just a brilliant, brilliant immunologist at the top level, and he calls his colleagues immunity deniers now. The people who say what you’re saying because it’s not just TV pundits, its immunologists are saying this, and it’s quite frankly, absurd. Basically, we have lots of layers in the immune system, millions of years of evolution or our creation, if you will. We’ve got the innate immune system can fight off viruses and recognize those blast them. We’ve got mucosal immune system, and we’ve got IGA antibodies there, where your mucous membranes are very important barrier. That won’t show up in the antibody test.
We’ve got T cell immunity that recognizes this virus and does many, many publications, up to 60%, 70% of people showing T cell responses, even though they weren’t exposed prior. There’s all of the T cell machinery. Then there are B cells, and then there are antibodies, et cetera. The problem is, in engineering terms, you’re measuring the wrong thing, you’re measuring a specific response to the spike protein in the antibody system and saying people who don’t test positive for that specific test are not immune, not exposed, not safe but that’s absurd.
I reckon if you’re 10, or 15, and it’ll depend on the demographics and the health of the people, et cetera but you’ve got a 10% or 15% antibody positive in the IgG antibodies specific test, and the virus has washed through your population and you see the classic Gompertz curve, and you’ve got your few hundred million aged comorbid have passed. Put that together, you’re broadly have achieved herd immunity.
Another way to think about it is and this is really quite simple, there are many studies of symptomatic index cases, so people who were symptomatic, went about their business and all the people they mixed with even indoors and close acquaintances with no masks. Generally around 80% of people never exhibited an infection from the group of the people they mixed with. This is back at the start. Or show a positive or have any symptoms. Just from common sense, nominally, 70% or 80% are de facto immune from the get go, roughly.
Ari: Let me rephrase this, I want people to understand this because there are a number of people out there, for example, Dr. Tony Fauci, who have promoted an idea that you can measure very precisely the amount of people who have been exposed through antibodies tests in the blood, serum antibody test for IgG or IgM antibodies.
What you’re saying and what many epidemiologists and biologists are saying, immunologists are saying is that there are these other layers of the immune system, the innate immune system, mucosal immunity, which is IgA, which they’re not measuring, and T cell immunity, which they’re also not measuring via these antibody tests and there are a large subset that the best evidence that we have indicates that there’s a large subset of the population that likely has at least partial, if not full immunity from these other layers of the immune system, and yet won’t show up as having an IgG or IgM antibody test. Is that accurate?
Ivor: That’s absolutely as in a nutshell. I think it’s very elegant, how we know that people exposed to asymptomatic index case, around 70% or 80% never develop anything. So with no science, no anything but logic, you can nominally say 70% of people plus are out of the picture from the get-go. Now you’re left with the remaining 30 to worry about, just to view it even more simplistically. The reason those 70% don’t get anything, even spouses, the attack rate or the secondary infection of people’s spouses, it’s actually quite low and they get up to stuff usually.
Ari: I’ve actually known a number of people personally who have gotten it, had relatively mild symptoms, and the spouse didn’t get any symptoms at all.
Ivor: Exactly. And the German study as well, it was clear as day in the town that got 15%, I forget the name if it. Gant, or something Gant but, again, you’re seeing these phenomena. This is classic immunity. When a new virus comes along, it hits the people who have really no immunity and if it’s truly new, like the measles, Professor B. Stadler told the story of a European who came to an isolated island, and they all got sick, lots of them except the older people.
The reason was he had brought measles in and there were a couple of generations who had never been exposed to measles at all and the older people had been around 40 years ago, so their T cell was still there. So the older people didn’t get, but the young people got really, really sick and a lot of them died. It’s a classic example but this isn’t measles, this isn’t smallpox. This is just worn in a long line of Coronavirus family, and it shares loads of proteins and characteristics that our immune system has evolved to identify not just the spike protein, that’s the least of it.
Our immune system can identify all of the internal proteins because when the virus gets into the cell, ourselves, it starts replicating and evolution is smart. Our cells push up to the surface of every one of our trillions of cells, they push up the proteins that they are making, the virus gets ourselves to make its proteins and our smart cells keep displaying them on the surface.
T cells and other systems are swarming, continually scanning the surface of ourselves. When SARS-CoV-2 comes around for a lot of people, and it starts generating its proteins, our body displays them to our immune system; our immune system says non-self, gone. It knocks them out. That’s why a huge proportion of people never exhibit anything with a new virus.
Ari: Largely from cross-immunity from previous exposure to common Coronaviruses that cause common colds and flus, right?
Ivor: Exactly but even before that, if someone’s mucosa are in good shape, and they’re healthy, the virus will never even get a purchase anyway. You might fail a test, maybe in your nose, but it’s never really got in your system. There’s a load of those too. Then there are false positives from the test.
How the body tackles antibodies
Ari: Yes, I want to talk about that. I’ve definitely flagged that as an important issue I want to come back to. A couple more points on this herd immunity thing, the equating of immunity means positive serum, IgG, or IgM antibody test. One of the other big holes in that, as far as I can tell, is this highly publicized disappearance of antibodies.
If you just consider the fact that there’s a segment of the population that gets exposed, never generates IgG or IgM antibodies, there’s another segment that does generate antibodies, but those antibodies disappear after, let’s say, three months, four months. You could expect that even with much more exposure of the virus if you took a measurement of what proportion of the population has antibodies right now, you measured it again, six months from now, after lots of spreading took place, the proportion might still be, let’s say, 20% because a chunk of those people that tested positive the first time won’t test positive the second time. Is that accurate?
Ivor: I’m delighted you reminded me of that because that absolutely. In Ireland, long after the epidemic, I think it was June or July, they tested and then they got 2.5%. Now, the epidemic washed over Ireland. I know doctors whose parents died in January but the real triggering was in March, April, because the virus triggers. It builds and spreads, then it triggers seasonally and it’ll wash through the population with a deaths per million similar to Sweden and England quite high near 400.
The virus had washed through the population and yet, they came up and said, 2.5%. At the time, I thought those antibodies are fading like hell, and months have gone by since the epidemic so most of them are gone but I didn’t have the data. Then, just like you say, we got the data and that’s absolutely.
Apparently, here’s more immunology denying by the immunologists. Apparently, it’s established in the science, that we make antibodies when we get an infection, we never keep them, they fade away, and otherwise, our whole bodies would explode with all the antibodies we’re keeping. This is completely established Immunology 101.
Those antibodies fade away to a below measurable level, but the T cell is what’s holding the memory. Next time this problem comes along, the T cells will immediately flash into action. They are the memory and the speedy response to stop about infection, not the antibodies, the antibodies are just a tool to use during the infection and then you get rid of them. You can instantly recreate the tools later because the T cell memory.
A Japanese study is perfect, they are the only guys in the world who did this, and this from an engineering perspective is a no-brainer to do but no one did it. They took a bunch of people and tracked them and kept testing them for antibodies through the hump of Japan’s epidemic in June, July, August, whatever. They had, I think 4% positive coming into the problem, but they kept testing those same group of guys. They got up to 45% antibody positive at the peak.
Ari: It’s crazy.
Ivor: Then they began to see the earlier guys who had gone positive when negative, and then the rest of them and negative and they all fell away but they were all fine and they had very minimal symptoms. You know what? Right during that, where that cohort shows that around 50% of people got enough exposure in the population to generate an antibody positive, they had no death.
Practically, no death. The reason is that your death is decided in a country by the health of your aged, generally, by prior severity of seasons that will have taken out susceptible people and by your history of exposure to Coronaviruses and Asia has a lot of history of exposure. That cross-immunity is strong there. They can still get infected; they can still have a response.
Ari: One of the lowest obesity rates in the world as well.
Ivor: Yes, and the highest Vitamin D and the ages rates in the world because the metabolic health and yadda yadda yadda. The determinants of population mortality per million are largely completely independent of lockdown, not lock down. There’s no correlation with that crazy stuff. It’s all to do with scientific stuff, not medieval superstition lockdowns. That’s just a fact and the World Health Organization 2019 pandemic guidelines, and Ireland pandemic guidelines; they’re all unified in one key thing, no quarantine, and no lockdowns right up to the end of 2019. There’s a reason for that. It’s what we just said.
They make no scientific sense, especially for something in the envelope of a bad flu season in terms of mortality, which it is. There’s no way you do lockdowns or quarantines. It makes no sense. That’s why it was in all their official published November 2019 guidelines. Then what happened? 2020, we forgot all of our Western history and science, all of our immunology, we forgot everything and we turned to China to be our leader.
Ari: One more point that I want to make on this because it’s been highly publicized that this disappearance antibodies means essentially, oh, there is no immunity. There’s no lasting immunity. That means everybody who gets it naturally is susceptible to getting it again a few months later. It’s been framed that way in a lot of the media, and I know you alluded to this in your comments there, but can you just state it directly. Does the disappearance of antibodies mean someone has lost their immunity?
Ivor: No, that’s normal. Disappearance of antibodies in a test is completely normal and so it has always been, but the people exposed can have de facto immunity for decades afterwards. We know this, the claim that was made was because it’s a new virus, which theoretically is, we can’t believe any of the science in the past, which is insane, because except for very unusual organisms and pathogens, the rule applies and Coronaviruses are common. It’s the common cold virus family and influenza.
They all follow the normal rules of immunity but they said, “No, it might not.” That’s just on scientific scaremongering. Edinburgh University in the UK came out last week, and there’s many publications coming out and they did studies early on during the epidemic, and people not exposed to Coronavirus yet had all kinds of T cell and other responses. They even had responses to the spike protein, even though they didn’t have antibodies, and they were not exposed.
They were pretty certainly not exposed. We have people from SARS-1 whose T cells response has lasted 17 years after SARS-1. It’s still there and if SARS-1 was kept in liquid nitrogen for 17 years and sprayed on those people, guess what? They might get a mild response, but they won’t have a problem. There’s the T cell army sitting ready to explode into molecular action. That’s how it works.
Ari: One last piece of this herd immunity thing that I want to point out for context, let’s say, as we touched on with curves in the beginning of this, and why curves are shaped the way they are. We’ve talked about just spreading through the population and then stumbling across more and more people who are immune, so population immunity, and the seasonality and I think you mentioned one other factor, that I might have forgotten what that one was.
Ivor: Passing of the susceptible is part of it.
How flu-like viruses behaves in the general population
Ari: Okay. The curve, again, is shaped like that even in the absence of lockdowns, we don’t lock down every year during flu season, we have a curve that is shaped like that. It goes up real fast, and then it stays there for a couple months, and then it goes away. How much of the population does a flu virus or the influenza virus or the flu viruses that sweep through the population each season, how much of the population does that reach? Is it reaching 5% or 10% of the population? Or do these viruses spread very rapidly within the span of a month or two through a very large chunk of the population?
Ivor: That’s a great question and we don’t really have quantitative data on that but I would say based on the science, the behavior, and all of the history of science around this, I’d say they generally spread extremely widely. We know from the initial reporting back in January, February or March, this is an R-value of three. It’s higher spread than the flu. The flu goes everywhere. There’s even papers published about the virus moving in intercontinental air channels in particles, and that’s been demonstrated for bacteria.
I think the higher virus comes into Europe, November, December and it goes everywhere because we had three or four months where we did effectively nothing to stop us. We know it’s in the human sewage. It’s in community transmission in Europe in November, in Spain, Brazil as well, Italy. We know it came in and no one was doing any measures so of course it spread.
It’s seasonally triggered and by that stage, the reason the lockdowns didn’t do anything is a lockdown– If you know a virus is in China, and it’s not in your little island yet, you can lock down your island. You might still be in trouble because it might come in the trade winds but let’s say you’re successful, but in a country where it’s been in the human sewage four months previously, and you think you can close the barn door now, it’s going to do something?
Ari: In other words, as you were saying before, it triggers seasonally. The virus is already present there and it’s latent, that’s probably not the right term, but in latent way and then when seasonality triggers, it spreads through the population very rapidly. You have lower immunity from dropping vitamin D levels and things of that nature. Is that accurate?
Ivor: Again, I’m careful in saying the dormancy because it’s a very strong hypothesis. Dormancy has been demonstrated in papers for similar cold viruses. We know what happens with herpes simplex and others. That’s just a given but it’s not proven out. All of the behavior on data and knowing that in Brazil, it was in human sewage in November 19, same in Spain. Spain exploded in February, March, seasonally, clearly. Then Brazil rolls open April, May, June, July in the seasonal pattern. There is some level of dormancy and this current winter resurgence, which we predicted back in April, without a question in Europe.
In the winter, Coronaviruses rise up in the winter; they fall down in the summer. Quite a bit of this could be an element of dormancy. They’re running around trying to track and trace, trying to see to build no jack and jack [unintelligible 00:21:08]. It may actually be kind of an illusion, that there’s resurgence now.
If you’ve got people who are older and not well, the problem is that for an 86-year-old who’s in reasonable shape, six months can be a lot of time. You can be in serious trouble in six months. An 18-year-old in six month is going to be the same health. We’ve got six or eight months now of a buildup of stage four cancers that have gone to immunocompromised. Especially because they shut the hospitals.
We’ve got a bunch of older people who have become very, very poorly in those six months. Especially because they locked them up with no support. Those people are going to be compared to the second wave but it’s not a second wave. It’s a winter resurgence and quite a bit of it, maybe dormancy rising. Therefore, all these measures don’t even touch the curve.
Ari: It’s worth saying in this context, that every year because of what you just mentioned, there is a new buildup of susceptible people in the population because every year you have people nearing the end of their life, who are ill and who progress from moderately ill to severely ill or progress from very old to extremely old. Then they become in that span of years, susceptible. That’s why every year like clockwork you have during this respiratory virus season in the winter in the Northern Hemisphere, you have 30,000 to 80,000 people who are are dying from these respiratory viruses. [crosstalk] Sorry, go ahead. If you want to comment.
Ivor: No, it’s part of life itself. This year, we took a new virus, which had an impact like a severe flu season. That’s borne out in the figures without question. We changed it from being part of life, where we should have followed the 2019 WHO guidelines and washed our hands and stayed at home if symptomatic. We should have done that good stuff on behalf of the susceptible but we decided to say, “No, we’re going to throw all the rules out. We’re going to do something completely different.” Otherwise, it’s like you say.
Ari: I want to come back to that in one second. I just want to wrap up this idea of the reason I brought up the flu. If that curve of the flu during the flu season is reaching 50%, 60%, 70% of the population, it’s spreading very rapidly through the population in a span of a month or two, it’s interesting as a way of contrasting this, that we have all these people promoting the idea that with this new virus, it’s somehow not spreading through the population. It’s over the course of eight, nine months; it has only reached 6% or 10% of the population and hasn’t spread through the population.
The curves have gone down, for example, in a place like Sweden, despite not spreading through the population. This is a point of big confusion for me or something that has never really made sense. Because if the flu sweeps through in two months and Sweden didn’t really do something that profound to lockdown, there’s footage, as you said before, that they’re living pretty much normally schools and businesses stayed open.
People are in restaurants, people are out in the streets, nobody’s wearing masks. There’s no reason to think that that virus could have gone away and gone down to almost nothing. They have almost no deaths right now and have for several months at this point. There are no suppression measures that could have explained that happening. Right?
Ivor: Absolutely. You’ve just had another nice logic bomb that blows up the narrative. Sweden had in May, after the peak passed and the epidemiologists were proven correct, and it was coming down because they followed the WHO 2019 guidelines properly. Anyway, it was coming down. Then the people just realized, “Oh, this is like a bad flu season and it’s clearly passing.” They’re looking at the numbers, “Ah, its fine,” and they all got back largely to normal. May, June, July, August, September, and now into October, no masks. You can see packed buses, no masks. They dropped all of their distancing largely.
People in Sweden during the summer, they dropped the whole lot. Technically, they were still being advised but they dropped it. Where did the virus go? Because it was pumping through the community, as you say in March, April and people were passing away. How come they went back to normal for five months, that seasonality? Also the other things, the passing of [unintelligible 00:26:05] and also the community immunity has built up, it’s not new anymore. You’re absolutely right. This is so obvious. The WHO in July 28, I have the paper. I saved the press release. All over the world came out and said, “Coronavirus SARS-CoV-2 is not seasonal at all.”
It will have one big wave that’s going to keep going and going until we have a vaccine. I thought when I saw that, I was stunned but we know it says. All the data says even if you don’t understand the sign how can you say this? But there you go. You’re right, of course. In the winter, the virus will resurge. You’ll have dormancy resurging too. You’ll have older people and stage four immunocompromised cancer people, who will have moved forward sadly to a much later stage. They can get hit. We’ll have a winter like, we always had.
Ari: To that point and this is something that, again, you’ve said you has made comparisons in passing to the flu. I know that there are some people who are going to be very triggered by this. I would love for you to share some visual context. Sweden is a great example of a place to share it because they didn’t do lockdowns. Can you share this amazing slide that someone put together of the data of deaths per million in the Swedish population over the last, I think its 150 years since 1850 or so?
Ivor: Yes. Oh, it works, I think.
Ari: We got it.
Ivor: Just really quickly as an intro. Here’s the modeling because the modeling in America and especially Imperial College in the UK, was based on 6 infected people from 680 in 6 flights out of Wuhan in February. That’s the basis, the modeling. That’s why they were out by a factor of 12 in mortality. Why they all pause, it was much worse than a seasonal flu or a bad flu. Not a generic seasonal, it’s more in the envelope of a bad flu. Let’s be fair. Here’s the model with distancing and Sweden and some lockdown measures. I think the upper one is without there the deaths curve. Here’s what happened with no lockdown, the blue.
That’s a fact. That’s the same all over the world. The other thing to say is, here’s another one. I think it’s another modeling group, maybe the one in Sweden. You see all the death rates down to not many measures but the actual is here. You nearly need a different axis to show real world versus the modeling guys.
Ari: For people listening who are not seeing the visual, basically, the models that projected the amount of deaths are what looks to be on the order of 100 fold higher than the actual deaths that occurred.
Ivor: Well, in fairness, no, I think generally, the graph might be slightly misleading because it’s so hard to see the real death rate because it’s low. No, between 10 and 17 times wrong, depending on which University made a [unintelligible 00:29:26]. The graph for Sweden, here’s the deaths per million. Basically, it’s 150 years. It’s pulled from the Swedish Government database and it’s quite accurate.
Even back 150 years ago, these guys were recording, deaths, births. It’s well recorded before computers. Here it is. Big spike here. That’s the Spanish Flu spike and, yes, it was special. It was a once in a century occurrence.
The massive one back in the 1800s was a cholera explosion. Here is this enormous spike if the viewer thinks of it going halfway up the page. Then on the bottom right is the Corona spike. If I jumbled it up, you wouldn’t be able to tell the Corona spike in the worst month in Sweden in April, from several other moments over the past 10 or 15 years. You can’t even tell it in part. This is the reality.
Ari: It blew my mind to see this visual. It’s just an amazing visual. Then it puts into context is mortality rate comparisons with more common circulating viruses.
Ivor: Here’s Sweden in September. People no mask in buses. That’s really since June, people are in buses, trains, no masks as normal. You can see the full streets and also we have photos people shopping. Basically, they’ve given up on the whole lot of the stuff now, because it’s essentially over there. It’ll come back in the winter. Here are more photos from Sweden. Need I say more? This is early October, normal.
Ari: You interviewed a Swedish, Dr. Sebastian Rushworth, recently, who was treating COVID patients back in March, April, and May. He said, I believe something to be effective, “I haven’t seen a single COVID patient in the ICU in three months.” Something to that.
Ivor: Yes, it was basically end March into April, everyone really got scared because the ICUs are filling up and because of the modeling. Then when they began to empty out again, later in May, everyone relaxed back. Then he spent May, June, and July. He didn’t see a single one in three months in this hospital. That’s how much they collapsed at the effect of. I’m just showing here, you see here Sweden trailing mortality, see the huge trough in 2019 through two most of the ’20 season. There’s uncommonly low amount of mortality. The spike then pretty much picked up on that. Corona picked up a lot of people who would have normally died in the prior season.
Ari: Ivor, just back. This is so important for people to get. I know we covered in talking but I think these visuals are really important for people. Can you just explain for people who are maybe not that scientifically literate, not used to looking at graphs like this? Can you just explain the basics of what people are seeing here and do some of these country compares? Because I think it’s just brilliant to be able to see this data.
Ivor: Yes, actually, I forget who did these ones to credit them. They basically took the death rates and did a rolling trailing average, which is the best way to see it. The dotted line going across is just the baseline death rate but it’ll go up in winter and will go down in summer. That’s the same all over Europe. You’ve got your respiratory season. Your deaths per million go right up. In the summer, they’re at the lowest. When you do a trailing average, you see the overall 18 month rolling average of deaths and is it lining up as expected? Sweden for 18 months, they had a big deficit or much less deaths than you would expect.
It’s clear on all the other graphs I have too. When Corona hit, you even had the 2020 flu season from October ’19 to March ’20. That season this year, was also extremely low for mortality, right up until Corona triggers. Of course, there’s a huge amount of people built up who are susceptible. That’s one of the main drivers for Sweden’s performance versus the Nordics.
If you look at Finland or Norway, I don’t have Denmark but it’s similar. You can see there is no real trough. It’s a different. 18 countries with these graphs and almost without exception, the countries hit likely. They had prior seasons that were significant. The countries hit hard, had prior seasons that were very soft. The UK is another classic example but I don’t actually have it here.
Ari: Beautiful. Again, going back to what we said previously, what you said previously. Probably the two biggest factors that explain the differences in mortality rates between countries is not a function of lockdown severity but as a function of primarily, the overall metabolic health of the population, especially, the aged population. These whether they had soft or very hard prior seasons during the flu season?
Ivor: They’re the biggies but the paper I briefly showed there is 16 reasons for Sweden’s higher death toll than the Nordic. A team published a paper giving 16. Yes, the metabolic health and indigenous, if you’ve got immigrant populations like, Sweden got 70% of the deaths were in care homes. That’s a big prior season thing. Then a disproportionate amount of the remainder were Somali immigrants. They have profoundly low vitamin D and suppressed immune system from the dark skin far north in Europe, where there’s no UV after the winter. You very quickly cover most of the main vectors and what drives a country’s impact?
Lockdown just doesn’t correlate. In fact, just for the listener. When you do a lockdown, it takes around three and a half or four weeks before your lockdown can affect the death rate because there’s a lag. Say, you do a lockdown first of January. Well, obviously, the lockdowns intended to stop infections. Then you got five or six days before there’s any symptoms. You got another week before the hospital, another week before the ICU, another week before the death. If you do a lockdown in the first of January, you’re only going to see the effect of that lockdown maybe the 26th or seventh but the beauty is here.
When Sweden decided not to do a lockdown, within days, their death rate was rising up, up, up much bigger than the Nordics. Sweden clearly had a baked-in inevitable death rate much higher, independent of their lockdown. We see this in all of the analysis. There is no correlation between lockdowns and lockdown severity and deaths per million across all the countries.
Ari: Do you have that slide that you can just show that visual really quick? Because I know there’s probably some segment of people listening who are skeptical of the idea that lockdowns are not having a major effect on mortality rates. I know that- [crosstalk].
Ivor: Yes, exactly. Well, there’s seasonality here as well. There’s USA versus Europe, different behaviors but I guess we can’t go through everything.
I’ll just do one. It could be at the backup slides. It’s basically I can describe it and you can show it after. It’s like [unintelligible 00:37:45]. You’ve got across the x-axis has severe countries lockdown and up the y-axis, you’ve got deaths per million. It’s just a shotgun blast of dots. There is no line, no correlation, no connection between severity of lockdowns and actual outcomes and mortality. It just doesn’t move the needle. That’s it.
The problems with the PCR tests
Ari: I want to shift topics. The theme of this whole discussion is really what we said before, that there are so many things in this mainstream narrative that are either unscientific or anti-scientific. Unfortunately, there’s a large portion of the population that wants to resist anyone questioning the narrative, no matter how many holes in the science there are. One other great topic that I think we need to cover is PCR tests. There’s, I think, this probably epitomizes the controversial science, maybe more than any of these other things.
Lockdowns are pretty good as well. There was actually an excellent article in The New York Times a couple months ago called, Your Coronavirus Test Is Positive. Maybe It Shouldn’t Be. They had a number of viralologists and immunologists that were commenting on there. They showed data from a number of places in the northeast United States, where they analyzed the degree of amplification. I’ll have you maybe describe some of the technology of how the test works. The degree of amplification and the number of cycles of amplification that are run on this test.
There is controversy among experts about what is the appropriate level of amplification. Because if you take something minute enough, some somebody might have a speck of a virus in their nose. That is not at all indicative of a raging infection. If you amplify it enough times, it will show a positive test and you can say, “Oh, you have an infection.” They found in this article, these are quotes from it. They had a number of positive tests based on an amplification cycle threshold of 40 cycles. They said with a cutoff of 35, instead of 40, about 43% of those tests would no longer qualify as positive, about 63% would no longer be judged positive if the cycle’s threshold was 30. In Massachusetts, from 85% to 90% of people who tested positive in July with a cycle threshold of 40, would have been deemed negative if their threshold was 30 cycles, 85 to 90% of the positives.
Then, one virologist, I think it’s a virologist commenting here is Dr. Mina, she said, “I would say that none of those people should be contact traced, not one.” This is just to frame this discussion, but I would love to get your take on PCR tests and the controversy around the false positives, case dynamics, and all these sorts of things.
Ivor: Excellent, Ari. Really quickly under cycles, I have a couple of slides here that are super to explain the PCR problem, but just on the cycles. Basically, the tests can look for one viral protein fragment from SARS-CoV-2 or some tests look for two and some look for three. Obviously, I want the test that looks for three and expects three of them. The ones that only look for one, it’s really bad.
Interestingly, recently, some countries are dropping their standard to only need one. They’re going the wrong direction but that’s just the number. Then you’ve got the amplification cycles and they can get a tiny fragment of protein from a dead virus that’s irrelevant and multiply that up and every cycle multiplies it up another, I don’t know, 5 or 10 times.
People know homeopathy, where you dilute things until you get one molecule in a bath of water, and it gives it power and its pseudoscience. This is reverse homeopathy, almost. You’re taking a fragment, and magnifying it up into a double-decker bath. It was never intended to be used for diagnosis, it was only a research tool, but they’re using it.
Roughly speaking, that makes sense, that New York Times because they’ve also shown if you go both party cycles, you’re multiplying this fragment so much that if you then take the person’s material, you can’t culture live viruses from it. If you’re below 30 cycles, you can culture live virus in a petri dish or a test tube.
If you’re above 30, rapidly, you can never get a live virus out of that person in the laboratory because you’ve magnified too much. The cycle is a major problem. Some countries are as low as 20. One of the Asian countries, actually, I think it might be Singapore somewhere is 20. They only do 20. Fauci himself said a couple of years ago, if you go above 30, and up towards 40, he said, “Forget about having meaningful results.” That was Fauci himself. He’s saying the opposite now.
Ari: Just to maybe emphasize that the differences in the cycle threshold of how countries are using these PCR tests itself could be a massive explanatory factor in the degree of cases that are being reported. Is that true?
Ivor: Hugely, hugely true. On October the 8th, the Irish Health Department quietly published a paper saying what we’re saying, and saying, “Guys, we ought to be really careful because we’re using 40 to 45 cycles,” and the literature is coming out now saying that above 30 is a question mark. That’s a published government document.
Now, I don’t know what they did about it but this is all over the world. Spain dropped cycles, rates dropped right down. It is a lot of– The countries don’t seem to even understand this factor we’re talking about. Some manufacturers have different guidances. There are no controls; the test was never validated as a diagnostic test.
Since this started, this whole Corona thing, the test has never been validated as being properly diagnostic. It came out of Germany based on some viral fragments out of China in a test tube, and it took over the world and everyone copied the original pattern in different ways. It’s a massive issue, and if I share here on top of the cycles, there’s another enormous issue even if you use the proper cycle count. Back here, we had an epidemic in Europe. This is, I know America is slightly different, northeast is like Europe, south is long and slow like Brazil, but we had an epidemic, it ended in May. Without a question, it ended in May because the impact had fallen all the way to nothing.
Out here, we had no epidemic in June, and we had several months of no epidemic. You can see the death curves and the winter’s coming, we’ll see a resurgence, but it’s not going to be different than prior winters. The WHO and others told us to test, test, and test. There was mega testing all summer. What happens then is, you get a casedemic. We lived all summer through a casedemic where there’s no impact, but everyone’s in a state of hysteria because the cases are high. So if you do 10,000 PCR in here, 10,000 people tested, you might get 100 positives, you go, “Oh my God, that’s a 1% have Coronavirus, have COVID.” No, they don’t, they have a fragment of a virus or a false positive.
If you take all these hundreds, you create the casedemic because you’re going, “Oh my God, we got 100 people, we need to get down to 50.” If you think about it scientifically, what you really got is 50 to 90 of those, when there’s a low rate can be false positives. This is just a normal part of the test, you can have 0.5% to 0.8% of all the tests are false positives, and there was nothing there at all.
Ari: Ivor, do you mind if I just add one bit on the US data because I’ve just looked at it a couple of days ago. From around March, they were doing about maybe 10,000 to 30,000 to 50,000 tests a day, since then, they’ve now gone up to 1.3 million tests a day. Over the last couple of months, they’ve done 1.2 to 1.4 million tests per day. I just calculated these numbers, if the test has a false positive rate of somewhere between one to five false positives for every 100 tests, that means that of the 1.3 or so, million tests that are done each day, somewhere between 13,000 to 65,000 false positives cases can be expected per day.
Interestingly enough, they’re reporting about 100,000 new cases and they’re saying that we’re setting new records for cases every day. The problem is, they’re reporting this case number as an absolute number without any context of saying that we’ve gone from testing 30,000 people a day to 1.3 million people per day over the last seven months.
Ivor: Exactly. You’re showing a big rise in the cases mostly because you’re testing more, and then within the positives, which they’re calling COVID, which is the disease, but they’re calling it COVID but it’s a PCR positive test, and it’s not diagnostic. You got false positives in there, just like you say, most of Ireland’s positives could have been false positive for months and everyone’s in a state of hysteria.
They can be old fragments from an infection two months ago up to and are meaningless because they’re just old fragments. They can be trivial positives where there’s a little bit of virus left, there’s no transmissible possibility from this person. They’ve just finished infection and the virus is irrelevant, it’s tiny.
Then there’s, concerning positives where you might have someone who could transmit, where there’s quite a bit of virus. This is the figure, the concerning positives, which they could work out from the data roughly, and that should be feeding into the metrics, but it’s only a small fraction of the overall positives.
The problem is, they’d seem certain on using every shred of it is like thing they can get to keep everyone in hysteria and that’s the way it is. Then they’re tracking and tracing based on something that’s meaningless. I had a couple of graphs here of a casedemic. You can see Ireland and England, back here, here’s the case where it is rising, and to your point, if you corrected this graph for the number of tests they’re doing.
This case rise here, this one over here will go off the screen, up around 10 times off the screen. We worked in testing back here but the case rise, you can see there’s no impact, the deaths are only around one per million people per day or less of an aged, a sick person and there were no women. Back here, there was an epidemic, so yes, you had cases. It was really a figure, enormously bigger than this, but you have cases and yet deaths and now you don’t, that’s a casedemic. This is a big one in Spain.
I’ll just show one example of a prior casedemic in 2009. There is one historical precedent, Fauci’s flu chip came out and enabled high-speed PCR. There was a big excitement about swine flu. Now it turned out to be a– It really didn’t hit people at all. You can see here the influenza season. Then they started testing for H1N1, that’s the orange, the swine flu. You can see it all summer, they had enormous cases.
Apparently, there was a panic buying of masks, and it was panic all the summer. They were talking about the plague, no one died, but they had a huge casedemic because they were able to now do mega testing. It looks familiar? Then in the winter, we’re thinking, “Oh, in the winter, there’s going to be a problem.” They did massive testing, but no one died in the second wave because there never is a second wave, really, because of what we said earlier.
There’s a winter resurgence, but very few died, but look at the cases, and here’s England, this is 2009. There was panic with cases in the summer. See the [unintelligible 00:51:12] cases, through the roof, but they had the lowest summer death ever in England in the last 30 years. There was an actual swine flu panic because the cases were so high. We’ve been here before, and it’s driven by certain elements in business, and then international organizations drive casedemics. We’re seeing it again, obviously.
Ari: That was a very diplomatic way of putting it. Opportunities, businesses.
Ivor: your listeners Gatorade, Google Spiegel, swine flu, S-P-I-E-G-E-L swine flu, three words. You get a top German newspaper, 2010 which talks about what I just said, the casedemic, and you’ll see all the parties that I’d rather not name here in a mainstream newspaper. This was a debacle, and it was treated as a disgrace at the time.
Ari: Ivor, I could talk to you forever. I want to be respectful of your time. I know there are many more examples of pseudoscience and unscientific and anti-scientific things that I’m sure you could point out. I’m sure we could also talk about your thoughts on practical strategies that people can use to protect their health. To be respectful of your time, if there’s maybe one or two last thoughts that you want to leave people with, I would love to just give you the floor and let you say anything that you feel is important to say that we haven’t touched on already.
Ivor: Maybe we’ve gone through so much of the science of this Coronavirus thing, but maybe prevention. It’s actually not that hard, and it’s not rocket science. So we clearly know from February, from the first Chinese data and it’s been born at ever since diabetes, insulin resistance, leptin resistance, metabolic syndrome is the big thing to drive your poor outcome. You can begin to fix that within a day. Within days, your immune system, and your leptin levels, and insulin will have changed alternately and within weeks, you will be a vastly more robust person. All you need to do is, get rid of all the processed foods and ultra-processed food. Eat meat, fish, eggs, vegetables.
If you’re worried about Corona, eat real food for a couple of weeks, get sun exposure, vitamin D, get magnesium, potassium, selenium, just some supplements because the foods these days are very depleted compared to ancestrally and just do a bunch of those things. Your whole life will change. You’ll lose weight, you’ll feel great, and you’ll dramatically lower your chance if you are exposed to this or any other virus of a severe outcome, very dramatically.
Ari: Beautiful. Ivor, thank you so much. This has been really, really fun. For people interested in following your work, where’s the best place to do that? Actually, I just want to do– My personal thoughts, go follow Ivor’s YouTube channel. He’s put out amazing content. You guys got a little glimpse of it with some of the slides he’s shown here, but he’s done numerous really comprehensive videos putting together, synthesizing a lot of different data, and putting it together. Really, it’s fun and informative slideshows that he [unintelligible]. Amazing stuff. Go to the YouTube channel, which is The Fat Emperor. Or is it just Ivor Cummins?
Ivor: If you search engine Ivor Cummins, the first page will usually hit my YouTube, Twitter. But it’s Ivor Cummins YouTube, really. You’ll get a quick enough.
Ari: Okay, wonderful. Anywhere else you want to let people know where to follow you?
Ivor: I’d say, if you Google or search engine my name, you’ll see the fatemperor.com website. I’m not getting to that as much anymore. On Twitter, I’m very active with around 110,000 followers. Then YouTube is the big one, though because it’s all free. Unlike you say, I have a ton of content on prevention and the science of this whole thing.
Ari: Ivor, thank you so much. It’s really a pleasure to connect with you.
Ivor: We’ll circle back maybe and see what’s happening in a while.
Ari: That would be great. One last thing, thank you for the work you’re doing. I think it is important to challenge a lot of the pseudoscience that’s going on right now. There’s a lot of, I think, dangerous pseudoscience. Thank you for having the courage to put yourself out there and challenge that and take it head-on and spend a huge amount of time to synthesize this data and being courageous enough to challenge it. Thank you for the work you’re doing, I appreciate it.
Ivor: Hey, thanks a lot, Ari. I always say there are two motivations. When I’m asked, I have five children, I’m future-focused. I’m going to die, we’re all going to die. I have no fear of my death. I’m thinking about the next generation, the freedoms, the world that I lived in, that I want my children to have, and what’s been happening, that’s getting destroyed. That and truth and science. They’re my two motivations, just for the record.
Ari: 100%. I’m with you. Thank you, again, my friend. I look forward to future conversations.
Ivor: Great stuff, Ari. Bye now.
How seasons affect infection rates (09:12)
The drastic changes and rejection of the pandemic guidelines (17:19)
Sweden – why have they taken a different approach? (25:10)
Soft and hard seasons – how they have affected the COVID-19 mortality (35:58)
US vs. Japan – the impact of metabolic health on COVID 19 (42:30)
Masks – what purpose do they serve? (44:44)
The actual data on the COVID infection fatality rate (1:04:30)
Understanding herd immunity (1:10:32)
How the body tackles antibodies (1:19:35)
The problems with the PCR tests (1:47:57)