What Really Killed Millions? | Denis Rancourt

December 1, 2022

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The government and media have been telling us since the start of the plandemic that millions have died from Covid. But the All-Cause Mortality figures from around the world tell a different story. Professor Denis Rancourt is an expert in All-Cause Mortality data analysis. In this in-depth interview he shows the proof that if governments around the world had not announced a ‘pandemic’ and then taken disastrous actions, no extra people would have died.

  • What did cause an additional 1.3 million deaths in the U.S. alone?
  • Why did so few extra people die in Canada?
  • Is the Canadian government altering mortality data?
  • How have the vaccine injections affected extra deaths?

LINK:

DenisRancourt.ca

SUMMARY KEYWORDS
people, deaths, mortality, died, cause mortality, pandemic, vaccine, excess deaths, data, fragile, period, age group, canada, peak, antibiotics, rollout, vaccinated, correlation, conditions, bacterial infections
SPEAKERS
Prof. Denis Rancourt, Will Dove

Will Dove 00:15
During the so called pandemic, our governments and the media told us that COVID-19 was killing large numbers of people. While people were indeed dying the all cause mortality figures show that it was not due to a virus. Danny Rand Corp holds a doctorate in physics is an expert in data analysis, and has authored over 100 Peer Reviewed papers. He has held a postdoctoral research position in institutions in France and the Netherlands, and subsequently worked as a physics professor and lead scientist at the University of Ottawa for 23 years. He has now co authored four papers on the all cause mortality figures, and the truth they reveal about what is killing people. His data can also be found online that Denise rank for.ca. Professor Ron coral, it’s a pleasure to have you on the show.

Prof. Denis Rancourt 01:05
Hey, it’s nice to be here, Will, thank you for the invitation.

Will Dove 01:08
I’ve looked at your research. It’s absolutely amazing. The detail you’ve gone into, the depth of analysis you’ve done I don’t see how anybody could possibly challenge your conclusions. So I’d like to start with that fact that we referenced in the introduction about, yes, people were dying but your figures from all cause mortality show not from a virus. So what was killing people?

Prof. Denis Rancourt 01:30
‘People were dying’ is a very punctual thing to say. But actually, the data is dimensioned in time, and in space, it’s very important. So what was happening in terms of mortality was very different from place to place, and changed in time as well. So for example, right after the pandemic was announced, there was a large, sudden peak in mortality immediately following the announcement of, of a pandemic. But that peak only occurred in certain places hotspots, but it had, but it occurred simultaneously, in those hotspots, even on different continents. So that right away tells us that it could not be a spreading disease, but that in fact, it was deaths that were caused by the immediate government and medical establishment actions that followed the announcement of the pandemic. And those actions were very aggressive. And they included pulling people out of ICUs fragile people and putting them into care homes instead, in order to free up the hospitals, and locking them into those care homes and transforming their lives of these most fragile people. That would have killed a lot of people and it did you see these very large peaks of mortality in the province of Quebec, especially in Canada, and in New York City, Paris, certain hotspots in Europe. So for example, in the United States, there are about 30 states that do not have that initial peak in mortality, but the other states do. So it’s very heterogeneous, it’s very different from place to place. And that’s one of the lines of evidence that we give that this cannot be, you know, a viral respiratory disease that spreads and that is very contagious, because it wouldn’t behave in this way. So they’re there are — and it’s very different from country to country. So you have 1.3 million excess deaths in the United States over the COVID period, and virtually none in Canada. This means that this virus, if it’s a virus refused to cross the border, which is ridiculous, it’s absurd.

Will Dove 03:40
Now, just before you continue, I have to ask this question, you said 1.3 million excess deaths in the US during the COVID period? Is that from the announcement of the pandemic to the vaccine rollout, or does it include the vaccine period,

Prof. Denis Rancourt 03:52
it includes the vaccine period. So it’s basically from the announcement on the 11th of March 2020, all the way to almost the present. That’s — we have data almost to the present. So it’s about half of that time, there were no vaccines, and the other half the time that rollout had been accomplished and most people had been vaccinated. In about half of that time, there is many deaths before after the vaccination was accomplished. In other words, we have absolute proof in terms of hard numbers, that the vaccine did not save any lives as can be seen by all cause mortality, there is no way that the vaccine had any beneficial effect.

Will Dove 04:30
But now I want to back up to that spike that occurred in certain places immediately following the announcement of the pandemic. And if I’m understanding correctly, what you’re saying is that that spike happened only in certain places and it always happened as a result of government actions that affected the vulnerable population; things like taking elderly people and crowding them together in the same space where the disease could spread rapidly.among them.

Prof. Denis Rancourt 04:55
The people that they moved were already on the edge of death in a sense, they were among the most fragile, so —

Will Dove 05:01
Right.

Prof. Denis Rancourt 05:01
If you pull them out of a place, move them, put them in a strange environment, change who their caretakers are, and isolate them, they don’t have as many contacts with caretakers or with family, all these things can be fatal to someone who is in that kind of precarious health condition. And so this would have killed a lot of people. But it’s not just the elderly that died, contrary to what the media have told us. Even in that first spike, there were a lot proportionally a lot more deaths among young adult and younger teens and so on as well. When you look at the deaths as a function of time and by age group, you can actually see that peak in the younger age groups as well.

Will Dove 05:40
And when we say younger age groups, can you give me an age range?

Prof. Denis Rancourt 05:43
Zero to 14 years, and then 15 to 25 years, and then 26 to 35 or 45 years old, and then older than 50, and up to 65 and so on you can you have all these age groups that you can select in order to look at the data, the mortality data by age group, and you see that peak and all the age groups in basically all the age groups. Yes. So what was done was very aggressive. And we believe we’ve come to understand that the people who died are the most fragile people, whether they’re young or old. So for example, in the United States, people don’t generally know this, but there’s 13 million people in the US who have a serious mental disease, you have to wrap your head around that, okay, that they’re officially characterized as having a serious mental disease. And these people are on medication, they’re mostly institutionalized and mental disease disproportionately affects young adults, more elderly people. So you’ve got this very fragile, and very dependent group of people who depend on caregivers who are institutionalized, who are already fragile, and you completely disrupt their lives and isolate them socially, during this sudden change in many jurisdictions, and that would have killed a lot of them. So it’s not just the elderly it’s basically the the most fragile populations, what we found in the US is that death was highly, highly correlated to social economic factors such as poverty, and for the correlation between poverty and excess death during the COVID period in the United States is plus 0.86, which is a very large correlation coefficient, it’s considered a very strong correlation, it’s really hard usually to find socio economic factors that correlate to death and disease that strongly

Will Dove 07:34
Yeah, plus 0.86 wouldn’t be an average correlation?

Prof. Denis Rancourt 07:38
Well, generally, in the social sciences, people are going with, you know, 0.23 – 0.45. And they’re happy about that. Okay, they’re actually finding correlations, basically, a linear dependence on poverty. And it’s not just a correlation. It’s proportional to the number of people living in poverty. The people living in poverty are typically the people who are dependent, who are institutionalized, who have mental illness, elderly also, and so on. These are the people who died in the United States. So you have this proportionality, meaning that in a state where you had twice as many people living in poverty, you would have had twice as many excess deaths during the COVID period. So that’s how strong the correlation is. And of course, poverty co-correlates with several things such as obesity, and disability and things like that. So you will also find strong correlations with the number of people living with a disability that prevents them from having work in society, and so on. There’s strong correlates with this excess death, and so on. So in the US, because you have 50 or more states, and you can really look for these correlations and we find them we find them. So these are the people who died fragile people of all ages. And the same is true in Canada. We’re now doing a study in that much depth for Canada. And get this I’m giving you the scoop here. Will, we haven’t published this yet, but here it is. In Canada, the excess death during the COVID period correlates strongly to the number of people in the province who are Aboriginal. So the Aboriginal population

Will Dove 09:11
that’s very intriguing is well, it’s terrible, but it’s also intriguing. So is it because the Aboriginal population tends to be living in poverty or is there some other factor there?

Prof. Denis Rancourt 09:20
Your Aboriginal status, in turn correlates to many things that are health related, obviously, right? So yes, poverty, obesity, various medications and drug problems. You name it, isolation and living in an environment of oppression. All of these things are known to dramatically affect health and make it even more susceptible to infection and so on.

Will Dove 09:45
I can personally attest to that I was a paramedic when I was younger, I worked on a reserve for several months. The conditions are deplorable. So I’m not at all surprised by what you’re telling me if you take people who are already living under those absolutely horrible conditions and then you put all this other stuff on them. Yeah, right, you can see where it’s definitely going to have an impact.

Prof. Denis Rancourt 10:07
Right. So what we’re finding in our all cause mortality as we do more and more research in that area. And what we’ve been finding for a long time we’ve been doing this for a couple years now, more than a couple of years is that you can’t think of the deaths due to so called COVID, in terms of how we see our middle class lives, the average person that’s, you know, using social media, you know, and has a relatively comfortable life, you cannot understand the mechanism of death, because you’re not in an environment where you see who is actually dying. But when you look at the statistics, what you find is that the people who are actually dying, are people who are in those pools and those groups in society that are particularly fragile. We find social economic factors that allow us to, to find these correlations, but what it really means is there are individuals in institutions, on reserves, in various places in society, that are extraordinarily sensitive to if you completely transform their lives, by isolating them, and removing what they normally have access to, and treating them in this way, like putting them in a kind of isolation prison. That will be devastating to many people who are fragile, and who are used to, you know, are on the edge kind of thing in terms of being fragile, but not dying, because they get regular help. And they have their regular routine and everything. And when you take that away, when you transform it, those are the people who are dying, those are the people who have died. So it’s not the athletes on the soccer field. That is a very small number of deaths in all cause mortality. When you look at all deaths, the bulk of all cause mortality, virtually all of it is these fragile people in these different groups in society. And so in Canada, it’s the Aboriginal people. And not just the Aboriginal people, there’s other groups as well, that are very impacted by these aggressive COVID conditions in Canada. And they are in the western provinces. And they are young, adult males, who have been devastated by the economic changes already in Alberta, for example, loss of job, loss of self image, loss of identity, loss of relevance in society, in addition to that, isolated, made more irrelevant, and so on. And they suffered a lot. And there are a lot of extra deaths in those age groups that are beyond just proportionality to the Aboriginal population in Alberta, especially, for example. So Alberta is one of these hotspots of death that goes beyond the large Aboriginal population that they have.

Will Dove 12:51
I have to ask those deaths among the young man, especially in Western Canada, and especially in Alberta. Yeah, now, that’s not deaths from disease, I have to assume that that’s deaths from things like suicide, substance overdose.

Prof. Denis Rancourt 13:03
This is one of the difficulties with this kind of research is that we’re looking at all cause mortality. So we’re purposefully looking at all cause mortality in order to avoid the problem of attributing the cause of death, right? Because there’s a lot of bias, when you try to attribute the cause of death, a lot of bias in that and the data is much more tenuous, more difficult to get reliable data, and so on. So we look at all deaths, and then we try to interpret it. What we just said is that there was a lot of young males are dying in the western provinces, exactly the provinces that where the origin, if you like, of the Truckers Convoy, okay? And this could be seen when you went to the Truckers Convoy and I did. I live in Ottawa, near the center of town, I went there many times, spoke once at the Convoy and so on. And you could see, not just truckers, but a lot of young men, in their cars, in their pickup trucks, sleeping in their cars, who had driven out from the western provinces to be there, I chatted with them, and so on. These are the people who were suffering the most from these consequences, the changes that we were imposing, the aggressive measures that we were imposing, and so on, and they — so you can see it in the all cause mortality, that that’s the origin of the conflict. So that’s just a comment about those deaths. But to backup, you asked me about cause of death, let me explain it this way. So in the US, for example, go back there, we find all this excess mortality that’s correlated to poverty, disability and so on. Okay, but what is actually mechanistically causing the death, right. And what we found was that these same people probably died mechanistically of a bacterial infection in the lungs, pneumonia, basically. So when you are made fragile by psychological stress and social isolation, it’s very well established scientifically, that you are more susceptible to infection. And when you look at the CDC data of mortality, when they attribute a cause of mortality, they find that more than half of the people that they say, would have died with COVID 19. They also say had a co infection of bacterial non COVID pneumonia. So there was an epidemic of pneumonia at the same time now cause of death is tenuous. And it relies on the person filling out the death certificate. And they don’t always analyze for the different bacteria that might be co infecting the lungs, and so on. Right, but in any case, they’re reporting that more than half of them were co infected, and had bacterial pneumonia as a cause of death. So you have this huge epidemic of lung infections at the same time that they reduce prescriptions for antibiotics by half. You have to understand that all the western countries during the COVID period, stopped prescribing antibiotics. Yes, it’s something I had not heard before. So well, it’s in our papers, we’ve explained it. And we’ve shown the graphs. So they basically recreated the conditions, like you had in 1918, before antibiotics were invented. So you have a large, already fragile people who are susceptible to lung infections, and you’re not prescribing antibiotics, you’re not treating them. And they’ve been made even more susceptible to those infections by the psychological stress and social isolation, which we know has that impact on the immune system and makes you more vulnerable. And it’s the same populations in the US that I normally have the most prescriptions and antibiotics every year, every winter. Okay, so you can do a map in the US of how many antibiotics are prescribed year after year. And all the poor states, a lot of poor people, more obesity, and so on, they have a much higher rate of antibiotic prescription that was cut to nothing. Prescriptions for antibiotics were stopped. And one of the reasons was they couldn’t see their patients as much, they weren’t seeing them, they were telling them to stay at home to isolate. So they weren’t prescribing they weren’t detecting these bacterial infections. And prescribing for the medical establishment was also told, do not prescribe antibiotics, that this was a viral infection. And it would be irresponsible to be prescribing too many antibiotics. So they were shamed out of prescribing antibiotic. When you talk about cause of death, you have to discern what really caused the system to be fragilized in order to be infected, and to be very serious. And those causes, in a sense, those higher level causes are psychological stress and social isolation, and the usual fragility, health fragility that you normally have, because you’re obese, because you’re living in poverty, all the things that would not help you, what you eat, your nutrition is very sugar intensive, and so on, all these things don’t help, that would be the thing that would make you more susceptible to infections of all kinds, you get, therefore you get an infection. And in addition to that, you’re not being treated, right. So that is how people die. That’s the neck aneurysm of the final death. But the cause is really all these other factors.

Will Dove 18:05
You’ve hit me with some information I didn’t know before, despite the fact I’ve been in this war for two years, I did not know about the withdrawal of antibiotics. So I’d like to try a lot.

Prof. Denis Rancourt 18:14
A lot of people are not reading our papers, I have to say, they’re big papers. And I give a lot of interviews. And I say this all the time, you know, the mainstream media is not talking about this.

Will Dove 18:25
So let me try to summarize what you’ve just told me. First of all, it appears that while we’ve all been told that putting people in isolation, putting them under stress is going to affect the immune system, it appears that the impact is far greater than most of us would have assumed. And as you pointed out, especially on those vulnerable populations, as you’ve said, this isn’t something that most of us who live a comfortable middle class life can understand. Because we’re not in that environment. I myself have seen that environment as a paramedic, I know exactly what you’re talking about. And folks, Professor Rancourt is exactly right. If you have lived your entire life in a relatively comfortable middle class life, you can’t understand what it is like in those sorts of communities. It’s nothing like your life experience is. So now you’ve taken these people who are already vulnerable, as you say, due to poverty causing comorbidities, and fragile mental states, and you put them in a position where they’re likely to get sick, and then you’ve removed from them the possibility for treatment. So essentially, what I’m hearing here is that these government actions have recreated the conditions of the Spanish flu,

Prof. Denis Rancourt 19:27
We should stop calling it the Spanish flu, because there are about five really good scientific articles – peer reviewed, that have shown that the people who died during the so called Spanish flu, actually died of bacterial pneumonia, which was exactly my point. They looked at the preserved tissue under the microscope and they were able to establish by looking at many, many people who died in the preserved lung tissue that they died of bacterial lung infections. There’s no reason to think objectively that this was an influenza that caused these deaths, okay, it was an epidemic of bacterial infections. Really, if you have to objectively say, of course, there’s always co infections. If you’ve had a viral infection, there’s clinical studies that suggest that you’re more likely to get a more serious bacterial infection that follows it, you know, this kind of thing. All that is true. But in the end, what killed these people is bacterial infections at a time where there were no antibiotics, and 1918 was just after major war upheaval, major economic problems in society, entire populations of young families and young men who had horrendous working conditions – if they had work, and living under absolutely horrendous living conditions, you know, bad water, rats, everything. These were the conditions of the so called Spanish flu. It was not a flu, it was not about a virus, it was about people living under horrendous conditions at a horrendous time in history, and not being properly treated, not having the possibility of treating them for their bacterial infections.

Will Dove 21:09
I’d like to move on then. You’ve talked about using the view, I’ve known from reading some of your material, you’ve used a lot of US data, there’s European data, that’s also very good. For example, France, you’ve referred to where they record right down to the postal code, the person who dies, you get very – but Canada, you say our data here is not so good, and much more alarmingly, you have evidence that they’re tampering with it.

Prof. Denis Rancourt 21:29
Canada has not been great in terms of putting out the data quickly, it’s been not as good as the US and most Western European countries, that’s for sure. So Canada has a problem regarding putting out its data. But the data that it does eventually put out is of good quality. That’s not something we looked at and published about in a scientific report. But there is some talk in the media and others that New Brunswick did adjust figures and so on. That’s true. But the data that StatsCan eventually puts out is we’ve always found it to be good and solid data. There have been huge lags which are inadmissible. And especially when you’re saying that we’re in the middle of a pandemic, it’s inadmissible that Canada was so slow. And that is a problem. That’s true. But eventually the data comes out. And it’s good. I want to stress something now will you summarize what are the factors that give you ill health and more likelihood of becoming sick and dying? There are many, many animal studies, social animals, researchers, that have all shown that the single most important factor of individual health and individual death is the chronic stress from the dominance hierarchy. What that means is that social animals, including humans, always construct and inhabit dominance hierarchies, there’s always a hierarchy of control. And this is true of all social mammals or animals of any kind. And to maintain that dominance hierarchy, you aggress the people in the lower in the lower parts of that pyramid by all kinds of methods, structural aggression, and so on, and you apply a stress, there’s a chronic stress associated with that, where you’re constantly putting them in their place. That chronic stress is the first determinant of health. Okay, so stress is absolutely the most important thing. So those individuals who are constantly put in their place and kept in their place, I guess, in a human environment, you would say, they’re the poor, or they’re the people that are living on reserve for historic reasons, and so on. But they’re structurally maintained in that place where they are more likely to be sick, have poorer health, have less life expectancy. This stress of the dominance hierarchy is the big killer among social animals. And that is like the number one biggest thing, there’s a basic amount of nutrition that you need of resources that you need of, you know, you can’t freeze to death, and so on. But once those things are satisfied, and you don’t have a complete lack of essential vitamins, and things like that, once those things are satisfied, the number one determinant of your individual health is stress from the dominance hierarchy. And in other words, your place in the social order of things.

Will Dove 24:18
As you say, it’s not just stress is specifically stress to do with the dominance hierarchy. So what that sounds like to me is that if you take away a person’s sense of control over their own lives, if you make them feel powerless, that is what is going to make them the most vulnerable?

Prof. Denis Rancourt 24:32
There’s a whole area of health psychology that is centered on this question that it’s all about your self image, your ability to actuate things in your life, to have control over your life, to serve a purpose and to feel and to have a self image where you do have a purpose in your life. All these things are essential to your health and to your well being into your continuing your life as an individual in this society. So if you remove those things if people suddenly are transformed not as people that you interact with, but as people to be isolated because they could get this virus, and that’s all they are, and you treat them that way that is going to be devastating to their self image and to their sense of self, you know, in their place in the world, and so on. And that is a massive strike against your health.

Will Dove 25:23
You’ve revealed so much from this data already. I do want to move on to talking about what the data shows after the vaccine rollout. But because you’ve given me so much good information already. Before we get to that, I want to ask if you have anything else you want to talk about in regards to just that general analysis that we’ve been discussing. Yeah, causes of death?

Prof. Denis Rancourt 25:41
Well, there is one more point I mentioned that in Canada, the US virtually all Western European countries, they stopped prescribing antibiotics at the same time that there was this epidemic. It would be important to look into how and why that occurred in detail. You know, there were recommendations made by the medical association there all kinds of things happening there. And they stopped prescribing antibiotics at a time when there was a high likelihood that a lot of people need this kind of treatment. And I want to relate that to the MDs who are acting in really good faith and who have come to believe that they were able to help their patients with ivermectin. Because ivermectin is known scientifically, there’s a really good scientific article about that as being an extraordinary antibiotic agent in the sense that it really helps with bacterial infections of the lungs. Okay, it’s very effective. Yes. So at a time when you’re told that this is viral, and you can’t prescribe antibiotics, MDs we’re prescribing ivermectin for so called COVID. And we’re helping their patients. And I think that’s not an accident. I think it’s very difficult to discern what your patient is most suffering from, and exactly what the nature of the infection is, and everything so you do what you can, given the symptoms that you observe. And I’m not surprised that ivermectin would have helped people at a time where you’re not prescribing antibiotics, and people are susceptible to bacterial lung infections. That’s just one of the consequences of our analysis meshes in with what many clinical MDs we’re seeing and reporting.

Will Dove 27:16
And you’re absolutely right. I’ve done interviews with a number of doctors who have been using these treatment protocols. Everybody, of course, is aware of Dr. Peter McCullough, with his McCullough protocol, which included ivermectin reduced hospitalizations, and deaths dramatically 85%. minimum, often higher than that. And most recently, I interviewed Dr. Rapiti from South Africa, who had an extremely aggressive early treatment protocol. And out of 3,000 patients, he last seven.

Prof. Denis Rancourt 27:44
There’s a high potential for bias and data like that, because your patients are your patients, they’re the people who are well enough to come to you. They’re the people that you happen to see in your community. They’re the people that happen to be in your network of people that you may treat, whereas all cause mortality statistics include everybody, right? Okay, you’re looking at mortality in the entire population. So to say that we saw this many patients, and only seven of them died, for example, is not really a statistic at the same type that you can compare to the kind of work that we do with all cause mortality.

Will Dove 28:17
I do understand that doing is giving weight to your statements about the infection.

Prof. Denis Rancourt 28:20
I just feel it’s important to say that because one of the most important conclusions from our work is the following. We see no evidence from all cause mortality, time dependence, addiction, dependence, and so on, that there was a particularly virulent pathogen that came into play here. In other words, there is no reason to believe in fact, there’s every reason to say that these excess deaths could not have been due to a viral respiratory disease. All right, that’s our conclusion. It was all due to the measures, yes. Okay. There’s always bacteria that can infect your lungs, that doesn’t change. If you make people fragile, put them out in the cold and stop feeding them, they will die from that. That doesn’t mean that all of a sudden there’s a more virulent bacterium, it means that the people have been made fragile. Okay. So the important thing is that we don’t see any evidence that there was a virulent strain of anything that came into being here. Okay, there was not a pandemic-causing pathogen that became that entered the society and was the origin of the problem. And that’s a firm conclusion, from all our work on all cause mortality. You can’t understand it that way. For example, such a pathogen from clinical studies would cause death that is exponential with age. Well, we see no correlation with the age structure of the population. When we do all cause mortality from state to state or country to country. There is none.

Will Dove 29:50
Because governments and the media have been telling people for the last two and a half years that the elderly are vulnerable, that we have to protect the elderly and what you’re saying is they all cause mortality. figures do not show any correlation to age.

Prof. Denis Rancourt 30:02
That’s right. When you do state to state when you look at factors such as that represent the age structure in that state, for example, with a fraction of the population that is 85, or over 75, or over 65, or over, when you take those kinds of numbers and try to look for correlations with excess mortality during the COVID period, you get a shotgun pattern, there is no correlation. So, where you have strong correlations with poverty and all these other socio economic factors, there is none with age. And likewise, if you do all cause mortality by age group, you do not find the exponential dependence that clinicians are claiming are exactly what COVID does, okay, in controlled clinical studies. And what is always found with viral respiratory disease is exponential age dependence of death, of probability of dying. So we don’t see that in our data.

Will Dove 30:54
And I just want to clarify what you’ve just said, because we could confuse some people if we don’t. What you’re not saying that elderly people didn’t die disproportionately to younger people, what you were saying is that there is no correlation between the supposed COVID pandemic and the increase in deaths in any particular age group, it’s across the board. So we’re not seeing it, it’s not disproportionately elderly people.

Prof. Denis Rancourt 31:21
Obviously, older people die more than younger people that score general thing, you know, you’ll have an exponential increase of probability of death with age, the doubling time of that increase is about nine years, for the human species across history and across societies. There’s that background of everything, then you look at the excess mortality, and you try to see if that is exponential with age, and so on. And what we find is that, when you look at all cause mortality, and its excess, it is incompatible with the story they’re telling us about viral respiratory disease, and a pandemic of that nature. It’s completely incompatible. It’s contrary to it. Okay? And you would if it were true, you would see a correlation with the age structure of the population state to state and we see none at all. So, you know, you have to read our long papers to really get the details. But that’s the point. There’s no way this was a viral respiratory disease pandemic that caused excess death. There’s just no way. The reason I’m insisting on this is because a lot of well, meaning MDs will say, Oh, it’s a crime. We weren’t treating people, there’s kind of an implication that there was a particularly virulent disease out there, there wasn’t. There was aggression against people that caused them to be more sick, you don’t need a special COVID protocol of treatment, you need treatment, okay. And that means you’re looking at your patient, you figure out what might help them, given your experience, and you treat them. And those treatments, like ivermectin will work against bacterial infection, and other things, you dose it and you individualize. That’s what that’s what MDs, do they treat people. But if you believe that there was this COVID out there, and that is, you know, a pandemic grade pathogen that that all of a sudden invaded the planet, it’s that belief is inconsistent with the hard data of all cause mortality,

Will Dove 33:22
The simplest question I can then ask would be this, based on your research, the excess deaths, had nothing to do with a virus and everything to do with the government interventions. Therefore, if, if it had never been a no —

Prof. Denis Rancourt 33:34
— no, there was, yeah, government interventions, including the behavior of medical institutions.

Will Dove 33:42
Right. So if there, if a pandemic had never been advanced treatment, if there had never been any interventions, if we’ve just gone on with life as normal, all of these excess deaths would not have happened?

Prof. Denis Rancourt 33:52
Exactly if a pandemic had not been declared. And nothing had changed, compared to the usual which is, you know, there’s more people in hospitals in the winter and we adjust accordingly. And MDs treat people to the best that they can, like they always have. And there’s not this constant blaring propaganda that there’s this virus out there and all the MDs have to think, have to put their COVID glasses on and think in those terms. If there had not been the propaganda, the lockdowns, the all the measures, all the recommendations to the medical establishment about what to do all the bad treatments, all the ventilators, all this kind of stuff, that they’re not being all of that there would not have been excess deaths in those places where there was excess deaths. and, and, and one proof of that is that there are many jurisdictions where there were absolutely no excess deaths. And Canada is very close to that. Canada had only 25,000 excess deaths and the whole COVID period, which is, you know, virtually nothing. You know, it’s like you It’s like you can’t even see it, we could share some data. And in fact this might be a good time to share. So I’m starting by showing my website and showing that there’s a section on the website about COVID, which is all the articles I’ve been writing about all cause mortality and evaluation of the science during COVID, and so on, in chronological order there. I wanted people to see that denisrancourt.ca. There’s under research, you can also see a section about climate change and geopolitics is very important because underlying this COVID madness is the geopolitics, which is really central. So I’ll just show that it for your listeners that have time to read and study this. And then I want to show you that I’m a researcher with the Ontario Civil Liberties Association. And the OCLA has a COVID section that has all of its reports and letters to the World Health Organization into Members of Parliament and all the things that we tried to do to warn people that, you know, they were being abused, and so on. So OCLA has been very, very active about the science and about the civil rights of this madness. Throughout the COVID period, there’s a whole bunch of documents there, you can look at to see what we’ve been trying to do and the information we’ve given. Now you can see this, this graph, which has all cause mortality in blue there. So on the Y axis, it’s all cause mortality by week, the Y axis starts at zero. And you see what the mortality is for all of Canada as a function of time from about 2010 all the way to the present. You see that? Yes. Okay. So there are seasonal peaks every winter, there’s higher mortality, that’s normal. Epidemiologists have seen this around the world for the last 100 years, as long as we’ve been getting good data, mortality data, we’ve been seeing this pattern, the cause of the winter, height of death is not completely understood. There’s a lot of debate about it, but it is there. So science does not know as much as we tend to think science knows, okay. But anyway, here’s the mortality as a function of time. And right here is when the pandemic was announced, on the 11th of March 2020. And you can see that the mortality is just continuing at about the same height at about the same amount of mortality per week, as we’ve been seeing for the last decade or more, and you can go back to the Second World War, you can see that it’s very – mortality changes vary very gradually. And so there’s been no change in mortality in terms of the amount. But there was this initial p right after the pandemic was announced. And that was especially high in Quebec. And that’s where they basically killed people with their, with their crazy measures right away. Very aggressive measures here. And there’s a very sharp peak here. That was a heatwave in BC that killed people for about for a few days. Okay. Now, this graph is interesting, because Theresa Tam and some co authors wrote a scientific paper recently, in which they claimed that if they had not vaccinated people and applied all these measures, and had the lock downs and did the distancing, and the masking, if they had not imposed all those measures, they claimed in their, in their peer reviewed scientific paper, that there would have been about a million extra deaths in Canada, you have to wrap your head around this, okay, during the COVID period. So what we did my co authors and eyes, we said, okay, they’re claiming there would have been a million extra deaths. So if we distribute that million deaths uniformly across the weeks of the COVID period, you would have a death rate up here, you get that? Yes, yeah, they’re claiming that if they hadn’t been the wonderful public health officers that they were, and imposed all these draconian measures, that our mortality would have been way up here, like more than double the entire mortality in the country, for that period. Okay, that’s what they’re claiming. And then they’re claiming, because we did these things, it brought it down to what it was, or what it was, is the normal down here, which is about the same as what you would expect, historically, nothing has changed. And what I want to explain is how crazy what they’re saying is, they’re saying that we applied all these fancy methods and vaccinated and we did all these things. And by some incredible coincidence, we brought the mortality down to exactly what it would have been if nothing had happened. So even though the vaccines only came in to the second half, even though, you know, you were doing different things in different provinces at different times. And all these measures, we don’t know if they’re effective. We brought down the mortality to this level, well, this level is when you look at it, it’s the same as it would have been, there is a 3% increase in integrated mortality over that period, you can’t even see it by eye. Okay. So this is their claim, it’s a nonsense claim that the paper should not have been published. It’s ridiculous. That’s the kind of story that they’re telling us. So that is the situation for Canada. This is the all cause mortality by month now for the United States from about 2000 to about the present. And that vertical dark blue line is the month at which the pandemic was announced. And here’s the peak that occurred immediately following that. Now, you have to understand that that we’ve called it the COVID peak, no peak like that had ever occurred in the history of epidemiology that was that intense, and that occurred that late in the winter season. Okay, so this was completely induced by the measures, and was completely absent in some 30 of the States, but in hotspots was present. Okay. So that’s the peak that that I talked about earlier on. Now, in the US, you can see that the mortality is higher in the COVID period, you can see that compared to the, to the historic trend, right, so the US had 1.3 million extra deaths, compared to the historic trend there. And we analyze that, here’s how we analyze it, we integrate the deaths over the COVID period, and this black dot is, the integration value, so the total number of deaths over the COVID period, this black dot is the total number of deaths over a period of same duration just before the COVID period. And this one, the period just before and so on. So this series of black dots is the historic trend of the deaths over about a two year period, which corresponds to the total COVID period. And then in the COVID period in the US, you get a sudden jump in total mortality. And this difference is about 1.3 million deaths. So that’s what it looks like in the US. So the US is completely different from Canada, in that there was a visible, measurable, huge extra death. And the reason is, the US has many, many more extremely vulnerable people that can be killed, when you start to isolate them and aggress them in this way than in Canada.

Will Dove 42:31
There’s a higher percentage of people out of the whole population that are living in poverty,

Prof. Denis Rancourt 42:36
Yes, poverty and institutionalized conditions, suffering from serious mental illness, you know, have a high degree of obesity, really bad health, diabetes, and so on, there’s way more people living under those conditions in the United States than in Canada. And that’s why you get that. And so you can do this exercise that I just explained by age groups. So this is for the zero to 14 years age group. And then as soon as you go to 15 to 24, you see that sudden rise during the COVID period. So you’re looking at very young people here in the United States, 15 to 24. And even among those young people, you see this dramatic increase in integrated mortality during the COVID period, you see that? Yes. And the same thing for 25 to 34. So this was not just the elderly, you can really see a significant increase in mortality in these age groups, 35 to 44, 45, to 54, and so on 55 to 64. And then the most elderly, this is the same data but with more time resolution where I’m doing it by week, rather than by month. And you see that announcement of the pandemic. And you see the various peaks in the COVID period there, that we analyzed and tried to understand. There’s some really unusual stuff going, it’s unheard of, to have a mortality peak abroad, mortality peaked in mid summer, and you had two of those during the COVID period. Right? That’s completely unusual. And that’s because of these very aggressive measures that were affecting people in the summertime. This is what the integration looks like when you do that integration methods with the data on by week by week the high resolution data and then you can do it by age group with that data as well. So you can really get a fine view of it. By age group, you can do maps, and this is the excess mortality now for the entire COVID period for the 10 most populous states in the in the US by age group. So you see the age group down here, and you see how that’s structured by age group. So you can see that in a relative amount the younger people actually died more than the older people So the percent increase in their mortality was higher in the COVID period.

Will Dove 45:07
Okay, all cases on all of these age groups, we’re talking about people who are living in a vulnerable population, they’re institutionalized. They’re living in poverty. Yes, that’s the common thread.

Prof. Denis Rancourt 45:17
Yes, the excess mortality during the COVID period is highly correlated to poverty, disability, mental illness, all these things. And therefore, these are people who are in care, basically, okay, they’re disabled people that cannot live on their own, they cannot work in society, and so on. These are the people who died. Now, the next thing we did was we looked at the vaccine rollout in relation to the all cause mortality by week. So here you have the all cause mortality by week in the United States. This is when the pandemic was announced. This is this dashed line here is the halfway mark, it’s the place where you have the first very rapid rollout military style rollout of the injections. Okay. And the blue line here is the cumulative number of injections, people who were injected at least once, okay, so it’s very fast rollout. And this yellow line is the rollout of the boosters. And so we’re comparing that to the all cause mortality. And we’re going to be looking by age group, and state by state to see if the vaccine rollout is associated with a peak in all cause mortality. So that’s what we did, we did it by age group like this. And eventually, we looked at specific states. So this is Alabama, in the 25 to 64 year old age group. And here’s something here’s where you see the effect of the vaccine. Right, in midsummer, you have this huge mortality peak, and Alabama, unheard of, at the same time that you have this rapid increase in the number of doses delivered. Now that rapid increase after the initial rollout, this rapid increase is related to what they call the vaccine equity campaign. So they have a huge vaccine equity campaign that was funded by all the big financial interests, where they hired 1,000s of people to go and vaccinate all the most vulnerable people in all the faraway places are in Alabama, and so on. And so they had this, this second rollout, if you like, that was that was tied to so called vaccine equity. And that was very deadly to people in poor states, such as Alabama in this age group. So you see a peak in mortality here, that should never occur from the historic trends. Because it’s an it’s in the middle of the summer. So we have argued that this is an association between the vaccines and mortality. And you see that in Mississippi as well. Same thing, same phenomenon, see that. So you have this large peak and mortality in the summer, right, when you’re doing this vaccine equity thing, when you purposefully go and get the people who were harder to find and harder to vaccinate, and that you didn’t dare vaccinate, because they were fragile at the beginning, you go and get them now and you vaccinate them. And so you kill them. Right. And then Georgia, same phenomenon. So all the states, where you have the most poor people, the most disabled people and so on, is where they applied is where the impact of vaccine equity was most dramatic, and where it actually caused measurable amount of all cause deaths, an actual peak of all cause deaths. So this and Florida have the same phenomenon, and Louisiana as well. So we’re seeing it repeatedly, in poor states exact coincidence between the vaccine rollout and all cause death. And we know from an analysis of the VAERS data, that deaths following injection, occur mostly in a peak that is in the first five days following the injection. So we know it’s going to be very rapid, we know it’s going to be time associated with the injection. Okay? So the injection is basically this means the injection is a toxic substance. And you’re giving an additional challenge to these people who are already on the edge by vaccinating them, and you’re inducing their deaths immediately. That’s what this means. Michigan is the only state where we saw an unusual peak in all cause mortality that was associated with the initial rollout of the vaccine. And we were surprised by this incredible coincidence. And we said, well, here you are. You have a coincidence here, you’ve got this very unusual peak that we don’t see in other states that exactly coincides with the vaccine rollout. Now, was it a different brand of vaccine? Is the institutional structure different? We don’t know what happened that would merit investigation. But what we did see in Canada is we have the same phenomenon in Ontario, Ontario has this peak in an unusual place in all cause mortality precisely at its vaccine rollout for this.

Will Dove 50:13
Could this be climate related? Because the poor states that you showed earlier that had those peaks in the summer. Yes, those are all southern states. Yes. And you’re showing Michigan, which is a northern state, which is gonna have another very similar winter conditions to Ontario. Yes, it seems to me like we’d have to have something to do with winter.

Prof. Denis Rancourt 50:28
Well, colder states, people don’t live outside in the winter. So there is accommodation, there’s the institutional structures are different, the way that we accommodate to our environment is very different. And so yes, it could play a role that the latitude could play a role like that it merits investigation, which likely will never be done, right.

Will Dove 50:49
Yes, unfortunately.

Prof. Denis Rancourt 50:50
Then we looked at integrated mortality after vaccines were accomplished versus before they were accomplished during the COVID period. So now we’re integrating over the COVID period when most people have been vaccinated, compared to the COVID period before they’re vaccinated, this data is for all the USA, and compared to the historic trend, but then you can do by age group, like we did before. So some age groups have higher when vaccinated, the lower in fact, most age groups have a higher mortality integrated mortality, after most people in that age group have been vaccinated than before in the COVID period. Okay. So this is 25 to 44 year old, this is 45 to 64, higher again, hear they’re about the same 65 to 74. Now, they’re lower in the older people, 75 to 84. Okay, lower again, for 85 plus people. So this could be a so called Tinder effect, where you’ve killed the most fragile, most elderly people sufficiently in the first year that there’s less of them to be killed or to die in in the second period, that could be a so called dried Tinder effect. Now remember, we have these kinds of graphs for the 10 most populous states? Well, this is what the by age group, excess mortality, expressed as a percentage of the historic mortality for that age group. This is before vaccination in the COVID period. And this is after vaccination in the COVID period, see how the structure has changed completely. Now, younger people are affected much more. Yes, before vaccination after vaccination. So that’s the kind of study that we can do.

Will Dove 52:30
I actually think that makes perfect sense based upon the number of scientists and doctors who have demonstrated that these shots far from giving people protection actually damaged the immune system. So what you’re doing is you’re taking these younger people who would have been resistant, resilient would have been able to survive the infection, you’ve damaged their immune system. So now they’re going to start dying. And as you said, the elderly people have already been taken out. So that would cause that sort of inversion.

Prof. Denis Rancourt 52:57
Right. So we are trying to present objective hard data, so that immunologists and others can make the kind of interpretation analysis that you just described. And we do mention when we think there’s something in terms of interpreting that’s really essential to say, we say it, and then we let others say what they want. This is the strong correlation between poverty and excess mortality in the COVID period that I mentioned before. And this is the same data shown where you can see the origin and on the graph. So you can see that it’s actual proportionality, you double poverty, you doubled death, excess death in the COVID period. A graph like this has never been shown before. No one has found such a strong correlation between mortality and a social economic factor previously, not this strong. So and then we can do the same thing for household income. And for obesity, there’s a correlation as well. But there are no correlations for the age structure. This is what I was telling you before. This is a shotgun pattern. When you look at the age structure by state, you don’t find a relationship to excess all cause mortality. Okay. And this is a support program. This is the proportion of the population in this SSI support program because they’re disabled. And then there’s a different program. There’s also a correlation with that one. And this is straight up, how many people in the population are disabled. You have to you have to wrap your head around this in the US. Approximately 15% of the population of the working population is considered disabled, disabled. Okay. They cannot work. They’re just being taken care of. That’s a large fraction. This shows that the people suffering from serious mental illness It’s mostly young adults 18 to 25, much fewer suffering from this that are 50 years old and older. So that helps us to understand the age structure and our all cause mortality as well, regarding the vaccine killing people, what we have found in summary, is that the vaccine in combination with fragility that is pre existing, results in death. In other words, in all cause mortality, when you’re looking at the phenomenon in its large scale observation like this all cause mortality, the people who die from the vaccine are the people who are already in a fragile state. So if you go and vaccinate people who have been made highly fragile by social isolation, and all these horrible things that you do to them, or they’re already very fragile, that extra challenge of injecting them with this toxic substance, basically, the lipids are known to be toxic, and the vaccine is known to cause death, when you look at the VAERS data, those are the ones that would die. So generally speaking, it’s very rare that in terms of all cause mortality from our studies, it’s relatively rare, that healthy people who are not at risk would die from the vaccine.

Will Dove 56:18
And of course, most of us are aware that we have had an increase in athlete deaths, we have had people who were perfectly healthy report is dropping dead. But what you’re saying is, that is a tiny portion of the desk, because what’s really going on here is that these shots are acting as a multiplier in the already vulnerable population to make them, yet, many times more vulnerable.

Prof. Denis Rancourt 56:41
Well, enough times that they die.

Will Dove 56:44
Right. Right. Right, if you’ve taken this population that was already dying, but not, not from COVID-19 you but from the conditions that were that were forced upon them. And now you’re injecting them and making them even more vulnerable. So you’re gonna kill even more of them.

Prof. Denis Rancourt 57:00
Exactly. And it’s not because you made them more vulnerable by the injection, it’s because the injection itself is an is an immediate challenge to their health. Okay, it’s a toxic substance and the body perceives it as such right away. So they die basically, right away. The that peak in excess mortality in in mortality in all cause mortality is synchronous with the with the additional rollout, the so called vaccine equity campaign. It’s synchronous, there’s not much of a delay at all. So yeah, that’s right, that I have no doubt. I mean, it’s well established that the vaccine is associated with myocarditis and have no doubt that athletes will suffer these conditions. But as you rightly summarize, that’s a small fraction of all the deaths.

Will Dove 57:49
Professor Rancourt, thank you so much for sharing all of this data with us. It’s been eye opening that I’m sure not just for our viewers, but even for me, and I, I live and breathe this stuff every day. And you’ve shown me some things that I didn’t know, I would like to ask you. If, in summary, if you had some comments for our audience, what would they be?

Prof. Denis Rancourt 58:06
Okay, to summarize, the all cause mortality data is the most robust data that you can get, there is no bias because you don’t have to attribute cause of death. All right, so you’re just counting deaths in a jurisdiction and you know how old the person was when they died? And that’s, that’s the data, hard data. And that hard data shows conclusively that it’s not reasonable to think that the vaccines saved any lives whatsoever. Okay, first thing. Second thing, there’s evidence in that data, that the vaccine is associated with additional deaths that would not have occurred if they if you had not vaccinated. There are synchronous peaks and mortality associated with vaccine rollout. Thirdly, the people who are dying, whether it’s induced by vaccination, or by these horrendous COVID conditions that were imposed on them, are the fragile people in the society. So in Canada, Aboriginal people, young adults who have been devastated by economic changes, these fragilized, people who are the ones who are dying, overwhelmingly, in the US and in Canada. And finally, there is no way that you can think that there was a sudden appearance of a virulent pathogen on the planet, because the all cause mortality data is at odds with the idea of spread of a viral respiratory disease. There is no way that a virus can say, I’m not crossing the US Canadian border. No way. I’m not going there. That does not happen. It cannot happen. And this was not a viral respiratory pandemic. This was death induced by government measures, and medical bad treatment and medical non treatment. That’s what caused the deaths.

Will Dove 59:52
Thank you very much Denis for sharing this data. I know you’ve got a lot more I myself am going to be going through it. I’m hoping very much I can have you back for further interviews on some of your other data.

Prof. Denis Rancourt 1:00:02
It will be my pleasure.

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