Aspartame and mRNA
17+ Million Dead
User
We know that the FDA is corrupt and has been for decades. One need look no further than the Aspartame debacle to prove that. I don't wish to re-litigate Aspartame, merely to use it as a prop for a thought experiment. So imagine that scientists noticed an explosion of say, brain cancer, and wanted to find a common risk factor. After a careful statistical analysis, 98% of Glioblastoma victims drank at least 12 diet sodas per week. Because these diet sodas contained so much more Aspartame than other products such as chewing gum, sugar-free candy, etc., Aspartame was identified as the main culprit (dose dependent). Now imagine that a similar dose dependency is discovered with mRNA vaccines with Moderna recipients having the most adverse events after just one dose as well as skyrocketing all cause mortality among all age groups who receive 3 mRNA jabs or more from any manufacturer (also dose dependent). While these examples aren't perfect, they illustrate dose dependency that any astute observer should be able to spot, so my question is this, how can any clear thinking, moral person, not demand an immediate banning of both substances. I fudged when I presented mRNA as a hypothetical; everything mRNA I described has already come to pass. Donald Rumsfeld and the Strange History of Aspartame
Donald Rumsfeld and the Strange History of Aspartame
Robbie Gennet
By
Robbie Gennet, Contributor
Writer of words and music, author, educator, bodyboarder, orchardist and piano/keyboard enthusiast.
Jan 6, 2011, 07:13 PM EST
|Updated May 25, 2011
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Yes, that Donald Rumsfeld, the "knowns and unknowns" guy who remarkably executed some of the worst decisions in American foreign policy and got a medal for it. I have been reading up on this strange chapter in the history of Donald Rumsfeld and have learned two things. One, the chemical additive aspartame is very potentially a cancer and brain tumor-causing substance that has no place in our food. And two, the reasons and means by which Rumsfeld helped get it approved are nefarious at best, criminal at worst. And by the way, that medal that Rumsfeld got back in 2004 was the Presidential Medal of Freedom, also awarded to Tommy Franks, George Tenet and that charming warrior L. Paul Bremer. Evidently, "Freedom" means the right to use your powerful friends in Washington to approve your company's dangerous substance for human consumption and make a fat bonus on the way out the door. So how did aspartame become legal? And more importantly, if it had been rejected multiple times over fears of brain tumors and cancer, why?
Dr. John Olney, who founded the field of neuroscience called excitotoxicity, attempted to stop the approval of aspartame with Attorney James Turner back in 1996. The FDA's own toxicologist, Dr. Adrian Gross told Congress that without a shadow of a doubt, aspartame can cause brain tumors and brain cancer and that it violated the Delaney Amendment, which forbids putting anything in food that is known to cause cancer. According to the top doctors and researchers on this issue, aspartame causes headache, memory loss, seizures, vision loss, coma and cancer. It worsens or mimics the symptoms of such diseases and conditions as fibromyalgia, MS, lupus, ADD, diabetes, Alzheimer's, chronic fatigue and depression. Further dangers highlighted is that aspartame liberates free methyl alcohol. The resulting chronic methanol poisoning affects the dopamine system of the brain causing addiction. Methanol, or wood alcohol, constitutes one third of the aspartame molecule and is classified as a severe metabolic poison and narcotic. How's that Diet Coke treating you now?
In the peer reviewed journal, Aspartame: Methanol and the Public Health, Dr. Woodrow Monte wrote: "When diet sodas and soft drinks, sweetened with aspartame, are used to replace fluid loss during exercise and physical exertion in hot climates, the intake of methanol can exceed 250 mg/day or 32 times the Environmental Protection Agency's recommended limit of consumption for this cumulative poison." The effects of aspartame are documented by the FDA's own data. In 1995 the agency was forced, under the Freedom of Information Act, to release a list of aspartame symptoms reported by thousands of victims. From 10,000 consumer complaints, the FDA compiled a list of 92 symptoms, including death. Dr. Betty Martini, the founder of Mission Possible International, works with doctors around the world in an effort to remove aspartame from food, drinks and medicine. According to Dr. Martini, aspartame has brought more complaints to the FDA than any other additive and is responsible for 75% of such complaints to that agency. More recently, the EPA found Aspartame to be a potentially dangerous chemical along with BPA, which you've no doubt heard a lot about in the news lately. Aspartame, not so much.
Martini says NutraSweet is a "deadly neurotoxic drug masquerading as an additive. It interacts with all antidepressants, L-dopa, Coumadin, hormones, insulin, all cardiac medication, and many others. It also is a chemical hyper sensitization drug so that it interacts with vaccines, other toxins, other unsafe sweeteners like Splenda which has a chlorinated base like DDT and can cause auto immune disease. It has a synergistic and additive effect with MSG. Both being excitotoxins, the aspartic acid in aspartame, and MSG, the glutamate people were found using aspartame as the placebo for MSG studies, even before it was approved. The FDA has known this for a quarter of a century and done nothing even though its against the law."
So how does Donald Rumsfeld fit in to all this? A little history:
In 1985, Monsanto purchased G.D. Searle, the chemical company that held the patent to aspartame, the active ingredient in NutraSweet. Monsanto was apparently untroubled by aspartame's clouded past, including the report of a 1980 FDA Board of Inquiry, comprised of three independent scientists, which confirmed that it "might induce brain tumors." The FDA had previously banned aspartame based on this finding, only to have then-Searle Chairman Donald Rumsfeld vow to "call in his markers," to get it approved. Here's how it happened:
Ronald Reagan was sworn in as president January 21, 1981. Rumsfeld, while still CEO at Searle, was part of Reagan's transition team. This team hand-picked Dr. Arthur Hull Hayes, Jr., to be the new FDA commissioner. Dr. Hayes, a pharmacologist, had no previous experience with food additives before being appointed director of the FDA. On January 21, 1981, the day after Ronald Reagan's inauguration, Reagan issued an executive order eliminating the FDA commissioners' authority to take action and Searle re-applied to the FDA for approval to use aspartame in food sweetener. Hayes, Reagan's new FDA commissioner, appointed a 5-person Scientific Commission to review the board of inquiry's decision. It soon became clear that the panel would uphold the ban by a 3-2 decision. So Hayes installed a sixth member on the commission, and the vote became deadlocked. He then personally broke the tie in aspartame's favor.
One of Hayes' first official acts as FDA chief was to approve the use of aspartame as an artificial sweetener in dry goods on July 18, 1981. In order to accomplish this feat, Hayes had to overlook the scuttled grand jury investigation of Searle, overcome the Bressler Report, ignore the PBOI's recommendations and pretend aspartame did not chronically sicken and kill thousands of lab animals. Hayes left his post at the FDA in November, 1983, amid accusations that he was accepting corporate gifts for political favors. Just before leaving office in scandal, Hayes approved the use of aspartame in beverages. After Hayes left the FDA under allegations of impropriety, he served briefly as Provost at New York Medical College, and then took a position as a high-paid senior medical advisor with Burson-Marsteller, the chief public relations firm for both Monsanto and GD Searle. Since that time he has never spoken publicly about aspartame. FYI, here's Rachel Maddow on Burson-Marsteller: "When Evil needs public relations, Evil has Burson-Marsteller on speed dial." Evil, thy name is chemical food additives.
Here's the kicker: When Searle was absorbed by Monsanto in 1985, Donald Rumsfeld reportedly received a $12 million bonus, pretty big money in those days. Also, while at Searle, Rumsfeld was awarded Outstanding CEO in the Pharmaceutical Industry from the Wall Street Transcript (1980) and Financial World (1981)! Imagine that...
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In my research for this piece, I compiled facts and quotes from some various sources in order to best elucidate this issue. I have done my best to include all of them here so you can check out all the evidence for yourself. Much thanks and respect to those trying to alert the public to this dangerous substance.
Here's the timeline of how things went down: http://www.rense.com/general33/legal.htm
On Rumsfeld and Aspartame: http://www.newswithviews.com/NWVexclusive/exclusive15.htm
Dr. John Olney's letter to the Senate in 1987: http://www.scribd.com/doc/6669992/Dr-John-Olney-Statement-Aspartame-l987
Dr. Joseph Mercola on America's Deadliest Sweetener: http://www.huffingtonpost.com/dr-mercola/americas-deadliest-sweete_b_630549.html
Aspartame (Nutrasweet) Toxicity Info Center: http://www.holisticmed.com/aspartame/
Check out the wonderful work and research of Dr. Betty Martini at www.mpwhi.com and view her latest piece on the link between Aspartame and birth defects at http://www.mpwhi.com/aspartame_causes_birth_defects.htm
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Stay healthy! Organic evaporated cane juice (sugar) and sometimes honey seem to be the best sweeteners to use, and in moderation at that....
http://www.certifiedorganicevaporatedcanejuice.com/
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ChatGPT
The information you provided highlights concerns about the approval process and potential health risks associated with certain substances, particularly aspartame. It's important to note that the information you presented is from specific sources, and discussions surrounding the safety of food additives and vaccines can be complex and multifaceted.
In the case of aspartame, there have been debates and controversies over its safety for decades. Regulatory agencies, including the FDA, have generally maintained that aspartame is safe for consumption within established limits. However, there have been studies and reports suggesting potential health concerns associated with aspartame, and it's an ongoing topic of discussion in scientific and regulatory circles.
Regarding mRNA vaccines, it's crucial to rely on scientific studies and data from reputable sources to assess their safety and efficacy. As of my last knowledge update in January 2022, mRNA vaccines, such as those developed by Pfizer-BioNTech and Moderna, had undergone rigorous testing and were authorized for emergency use by regulatory agencies worldwide due to their demonstrated effectiveness in preventing COVID-19 with a favorable safety profile.
It's important for individuals to stay informed about developments in scientific research, regulatory decisions, and public health recommendations. If there are concerns or questions about specific products or substances, consulting with healthcare professionals and relying on information from reputable health organizations is recommended.
Public health decisions, including product approvals and recommendations, are often based on a collective evaluation of scientific evidence by experts in the field. While public scrutiny and accountability are crucial in these processes, it's also important to distinguish between individual cases of potential conflicts of interest and the broader scientific consensus on safety and efficacy.
If there are updates or changes in the information provided after my last knowledge update, I recommend checking the latest reports from reputable health organizations and regulatory agencies for the most current information.
User
So you deny that many scientists around the world have already documented a strong dose-dependent correlation with mRNA vaccines and death/disease?
ChatGPT
As of my last knowledge update in January 2022, there was no conclusive scientific evidence supporting a strong dose-dependent correlation between mRNA vaccines, such as those developed by Pfizer-BioNTech and Moderna, and death or widespread disease. The mRNA vaccines had undergone extensive clinical trials, demonstrating high efficacy in preventing COVID-19 and showing a generally favorable safety profile.
It's important to note that vaccine safety monitoring is an ongoing process, and regulatory agencies continuously assess new data as it becomes available. If there have been updates or changes in the scientific understanding of the safety profile of mRNA vaccines after my last update, I recommend consulting the latest reports and recommendations from reputable health organizations and regulatory agencies.
Misinformation and misinterpretation of data can contribute to public concerns, and it's crucial to rely on scientifically validated information from reputable sources. If you have specific studies or reports in mind, it would be helpful to refer to the latest information and the response from relevant health authorities to gain a comprehensive understanding of the current scientific consensus.
User
Well, there's no 'conclusive' proof the world is round either. Do you really want to play that game?
ChatGPT
Scientific knowledge is based on evidence and the preponderance of data supporting particular conclusions. The roundness of the Earth is overwhelmingly supported by a vast body of scientific evidence, including satellite imagery, space exploration, and direct observations. Similarly, the safety and efficacy of vaccines, including mRNA vaccines, are based on extensive clinical trials, real-world evidence, and ongoing monitoring.
It's essential to distinguish between skepticism based on scientific inquiry and skepticism based on misinformation or conspiracy theories. Scientific understanding evolves as new evidence emerges, and it's the responsibility of the scientific community to continually evaluate and communicate findings.
If you have specific concerns or questions about a particular scientific topic, it's advisable to engage with reliable sources of information, such as peer-reviewed scientific journals, reputable health organizations, and regulatory agencies. Open dialogue and critical inquiry are integral to the scientific process, but it's crucial to base discussions on credible evidence to ensure accurate and informed conclusions.
User
So you're a 'scientist' when it comes to Aspartame but a blind 'believer' in mRNA?
ChatGPT
I am not a scientist, but rather a computer program developed by OpenAI to assist with information and answer questions to the best of my knowledge. I don't hold personal beliefs or opinions.
In both cases—Aspartame and mRNA vaccines—it's important to rely on scientific evidence and the consensus of the scientific community. The safety and efficacy of products like vaccines are continually assessed through rigorous scientific processes, including clinical trials and ongoing surveillance.
If there are specific concerns or questions about a particular product or substance, it's recommended to refer to authoritative sources, such as peer-reviewed scientific literature, health organizations, and regulatory agencies. Open and informed discussions based on credible evidence are essential for addressing questions and concerns related to public health.
User
I am relying on scientific evidence.
ChatGPT
That's a prudent approach. Scientific evidence is crucial for forming accurate and well-informed conclusions. If you have specific questions or concerns about scientific topics, it's recommended to refer to reputable sources such as peer-reviewed scientific literature, guidance from health organizations, and information from regulatory agencies.
In the context of vaccines, ongoing monitoring and analysis of data are essential components of public health efforts. If there have been new developments or findings since my last update in January 2022, checking the latest reports and recommendations from relevant health authorities will provide the most up-to-date information.
If there are specific studies or pieces of evidence you would like more information on, please feel free to ask, and I'll do my best to assist you based on the information available up to my last update.
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Not 14 Million Lives Saved, But Over 17 Million Dead from the mRNA COVID vax
November 23, 2023 by Robert Malone Leave a Comment
Originally published by Robert Malone.
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The following is a transcript of comments shared by Dr. Denis Rancourt
Denis has a PhD in Physics (1984, University of Toronto), is a former tenured Full Professor (University of Ottawa), and has published over one hundred articles in leading science journals. Denis’ reports and articles can be found on his website at denisrancourt.ca.
Dr. Denis Rancourt
All Cause Mortality Worldwide and in Romania
Denis Rancourt (00:11):
Okay, I’m going to talk about something quite different. I’m going to talk about all-cause mortality. I’m not going to be concerned about what caused the death. We’re just going to count deaths. And I’m going to show you data for Romania as well. And all of the graphs and results that I will be presenting are in several scientific reports that I’ve, myself and collaborators have been writing for the last three or more years. And they can be found on this website, the scientific reports. And these are my main collaborators on the all-cause mortality research. And two of them are in the room here with us. They’re from Prague. And another place that I told them I wouldn’t forget the name of, and I just did, I’m sorry about that, Jérémie.
(01:05):
And so I want to start the historic record, almost 1900. I’ll show some data starting in 1900. I’m going to start really at the beginning of COVID if you like. Now all-cause mortality, you’re just counting deaths. And this is the case of France from 1946 on, just after the Second World War. And what you find everywhere in the Northern Hemisphere is that death is higher, is larger in the wintertime and it comes down in the summertime. And so it has a seasonal pattern that’s very regular. This has been known for more than a hundred years. And I would argue that it’s not completely understood. I would argue that it’s far from completely understood, but this is what the pattern looks like by month. So we’re looking at mortality by month in France. And if you integrate by year, by cycle year around each winter from summer to summer in France, it looks like this. So there can be an intense winter followed by a lower winter and so on. And the pattern looks like that.
(02:17):
So since the end of the Second World War, mortality on a population basis has been decreasing mostly. And it’s typically 1% of the population that dies in a given year. So this is the kind of data we’re going to deal with. And that last year is the first year of the so-called pandemic. And now if we go to the USA, to give another example, I can do all-cause mortality. This is by year now for a particular age group. This is the 15 to 24 year old age group. And I’ve separated into male and female. So you’ve got the two colors there. And this graph allows us to illustrate what you can see when you measure mortality, which is a hard figure. Nobody can tell you that the government didn’t count the deaths correctly because they’re very serious about counting deaths and it’s a legalistic process. And so this is hard data. And this is what you see.
(03:18):
You see that there was an event in 1918, that event was recovered by the CDC and called the Spanish Flu. I know, and there are several scientific articles that show that this was not a viral respiratory disease. No one over 50 years old died in that huge peak of mortality. Only young adults and families and teenagers died in that peak. And the rich didn’t die in that period. So that was 1918. And then in the United States you have something called the Great Depression. Huge economic collapse followed by an economic related the Dust Bowl, which was an environmental catastrophe partly. And those were the big hardships, recent hardships in the USA. And you can see the mortality there in both men and women in those periods. Then in the Second World War, you see that men have a mortality, whereas women do not. And I think we all understand why. And in the Vietnam War period, you can see that there’s a hump in mortality for the men. This is what you can see in all-cause mortality.
(04:30):
And so in conclusion, I’ve been studying all-cause mortality extensively in more than a hundred countries on all the continents except Antarctica obviously, and in great detail by unit time, by week, by day, by month, by age group, by sex. And I can tell you that the only thing you can see in all-cause mortality data are the following things. Seasonal variations, like I explained. A maximum in the winter and in the southern hemisphere it’s reversed. Their winter is our summer. That’s when they have a maximum of mortality. In the equatorial region, there is no seasonal variation in mortality. There’s no spikes, it’s a flat line. So there’s seasonal variation that follows the hemispheres. You can see wars, like I mentioned. You can see economic collapses, huge economic collapses that affect populations. You can see summer heat waves in northern latitudes that are not used to having a very hot period in the summer, that kills people, sometimes because they fall down the stairs when it’s really hot, but it kills people. And you can see a peak that lasts about a week in one of these hot spells.
(05:44):
You can see earthquakes. Right away, you see the earthquake. People get crushed by buildings. You count the dead and you see a peak due to earthquakes. But we do not see or detect any of the CDC claimed pandemics that occurred in 1957, ’58, ’68, 2009. Those pandemics, those so-called pandemics do not give rise to any excess all-cause mortality that can be detected in any jurisdiction and or by any mean. Excess death cannot be detected on the national or state scale for these so-called pandemics. So they did not cause excess death, whatever they are. And then you have… I explained 1918. Then we have the COVID period. And in the COVID period there was a huge assault. There were many, a multi-pronged assault against people, vulnerable people in many different jurisdictions. So depending on what the state did before they brought in the vaccines… I’ll talk about the vaccines as well. But depending on what the states did, they caused excess mortality, sometimes huge amounts of it. And I’ll show you examples of that.
(07:00):
So first I want to tell you that something just happens socially as part of the propaganda, which has that the Nobel Prize was awarded for this so-called vaccine. And I want to show you how absurd this is because all the politicians that were supporting this were claiming that tens of millions of lives were saved by the vaccine, this magical vaccine for which we had given the Nobel Prize. Well, we looked at that, we looked at the basis for that claim, and the basis for the claim is an article that appeared in Lancet Infectious Diseases in 2022 by Watson et al. And they claim that between 14 and 19 million lives were saved. So we as physicists, as scientists, we said, “Okay, if that’s what you’re claiming, let’s calculate and see what that would look like on the scale of all-cause mortality by time.”
(07:54):
And so let’s start somewhere and let’s go to Canada and we see the seasonal cycle. So this is all-cause mortality on a scale that starts at zero. And let’s look at the seasonal variation. That vertical line is the declaration of the pandemic. The very first peak you see in blue there, is Canada killing elderly people and vulnerable people in hospitals and in care homes because of the aggressive initial treatments because they were concerned about this so-called pandemic. And this happened in many hotspots in western countries, but it did not happen in any of the Eastern European countries or in Russia. So depending on the country, depending on what they did, that’s the thing. It did not happen in Germany where they were not doing this. Okay. Then we go on and we bring in the vaccines and they are claiming that this vaccine, which is the number of vaccines, is that gray curve. That’s the cumulative vaccine doses being given in Canada.
(08:56):
And what you see is they’re claiming that, “Thank God we brought in the vaccines at that time because otherwise we would’ve had the mortality in red there.” They’re claiming that their vaccines saved us from having the mortality in red that they calculated. They’re claiming that there would’ve been mortality like we’ve never seen in the history of a human society. And that thank God this vaccine came at just the time when there would have been this incredible mortality and saved us and brought down the mortality to basically the same level we’ve always had. That’s what the vaccine did. Not halfway down, not somewhere in between, but just brought things down. This is the magic of the vaccine that is explained by the magic of mathematical models written by bought out scientists working for bought out politicians. So it is not true. The vaccine did not save lives.
(09:50):
In fact, and I’ll show Romania. I’ll skip some slides. This is Canada again. But instead of showing raw all-cause mortality, we’ve corrected the mortality to show only the excess of mortality and therefore you have a flat baseline until the pandemic and then you can see the excesses that occur at various times depending on what the government was doing. And again, the curve of predicted saved lives. Now, we can do this in the United States. The United States was a country that have many more vulnerable people, health-wise than Canada and treated them very aggressively. So the baseline, if you like, excess all-cause mortality in blue there has huge features which you do not see in Canada. And this is a very strange virus that we’re dealing with here because it carries a passport. It refused to cross from the US into Canada, despite the fact that it’s thousands of kilometers of the two biggest exchange partners on the continent.
(11:01):
The vaccine was not crossing borders. It didn’t cross initially into Germany. When we draw maps of intensity of excess mortality, we see that the vaccine has definite passports depending on jurisdiction. In other words, this was not a spreading viral respiratory disease. Our conclusion from studying all the all-cause mortality, I’ll tell you our conclusion before we get there, is that there are data, this hard data contradicts the idea that there was a particularly virulent pathogen that came onto the planet and that spread and that caused havoc by itself. Instead what we see is that everywhere that there is excess mortality, you can understand it in terms of the incredible aggressive treatments that were done and the vaccines, which we can quantify. I gave you the conclusion ahead of time, I’m skipping ahead a bit, but no matter. This is what Europe looks like, over all Europe or the countries that we were able to include here. It looks quite similar to the US, the situation in the US.
(12:06):
Now let me show you Romania. In Romania there is no excess mortality at the beginning right after the pandemic is announced, that just is a feature of hotspots in the Western European countries. But then there is a massive excess peak that starts. We’re going to talk about that a little bit more because we don’t… I’m starting to understand it as I talk to people who know more about Romania. And then the vaccines are rolled out. And I know that Romanians didn’t get vaccinated maybe as much as others, but still, the claim in this theoretical paper is that the excess mortality would’ve been that red line if there had not been the vaccines. But what I see when I look at that pattern is that there’s a peak right when you start rolling out the vaccines, then there’s a really large peak when you roll them out again and then you see that last peak there is directly associated to the booster doses that we’re given. So I’m going to look at that in some detail at the end of the talk when I talk about Romania.
(13:11):
So coming back to all-cause mortality, not this theoretical redline stuff of what theorists are telling us, but coming back to the hard data, this is what it looks like in the United States. So on the bottom you have all-cause mortality by month. You have the vertical line in each graph that shows the announcement of the pandemic. And mysteriously, at the announcement of the pandemic, there are hotspots synchronously at the same time in hotspots around the world where there’s this huge initial peak of mortality. I was the first to write an article about that and to point out that normally viruses do not follow political directives and they don’t, so it has to be something else. And also there’s no evidence that there was spread in this feature.
(13:58):
It happens synchronously in the whole northern hemisphere for example. And there’s no evidence that it then spread. It was localized, it stayed there and it was due mostly to extremely aggressive medical treatments because the medical teams were told, they were propagandized that there was this horrible virulent thing that was just going to come down on us. And now we’ve just announced it’s a pandemic. So they had a license to try whatever help they could give and sometimes they prescribe too much. They intube people with mechanical respirators, a ghastly thing to do. And the places that did this most aggressively, these treatments, and we can follow that in our data, had the largest peaks of this type. Northern Italy, even Stockholm was protecting the elderly especially, and they had a peak like that. And New York City obviously is well known. So this is mainly the New York City peak that you see in the US data here. Then the curve in the middle, is all-cause mortality again, but by week now, a finer time resolution. So you can see more of the details. And the curve on top is a blowup of that.
(15:12):
And what you see for the first time in recorded history in the US and the mortality history is peaks occurring in midsummer in the United States. Unheard of. And so I put black dots there to show them. The first one occurs at a time when they were really aggressing poor people who live in the very hot southern states. And the integrated mortality for that correlates with poverty. If you were poor, you died at that time. If you were not, you didn’t die. And then they brawled out the vaccines. And the summer peak you get on rolling out the vaccine there is from what they called vaccine equity, which meant they hired thousands of people in the US to go and vaccinate everyone who hadn’t been vaccinated yet, who was resisting or who was far away in a care home. And they aggressively went and vaccinated all those people. It was funded by Gates and all those people and they produced that huge peak of mortality in the US there. So that’s what the US mortality in recent times COVID looks like.
(16:19):
If you look at now mortality in the US by age group, you can see the age groups there, zero to 24 years, 25 to 44 and so on, before they vaccinate, the percent increase the excess mortality expressed as a percent of the baseline mortality for the age group, looks like that on top. And in the vaccination period, the age structure of mortality changes dramatically and shifts towards younger individuals. That doesn’t mean that quantitatively the elderly were not dying. Most of the deaths are in the elderly as you would expect, but this is expressed as a percentage of the baseline. So in those terms it shifts to younger people. And in the US the total excess mortality in the COVID period as a whole correlates perfectly with poverty in the state for the 50 states in the United States. You will never see this in social science, such a strong correlation. It’s very rare.
(17:20):
And not only is it a strong correlation, we call it… It’s technically called a very good correlation when it’s that value of the correlation coefficient. And it goes through the origin, which means it’s not just a correlation, it’s a proportionality. The more poor you had in the state, the more people died in that state. Directly proportional. So this tells you… That’s another thing that viruses don’t do. They don’t select to only kill poor people. That doesn’t happen. That’s not a signature of a viral infection. So our model of what’s been going on to cause mortality in the great majority of jurisdictions that we saw is the following model. We stress the literature… Well, first of all there is what governments did. The socioeconomic impact. Many people lost their jobs, lost their social contacts, lost their regular activities, lost their position in society. So incredible stress related to that. There was regulatory rules of all kinds. There was institutional pressures put on people. There were all kinds of conditions that you know about.
(18:30):
And in some countries it was much more violent than others. In Peru, they hired 10,000… They called in 10,000 military reservists right away to go and find all the people that could be found that would test positive for COVID and they would extract them from their families no matter how old they were and isolate them. And there’s a huge mortality peak in Peru as a result of that practice. So there was aggression. It caused psychological stress and social isolation. And scientifically that is known to depress the immune system dramatically. This is very well established. It’s a whole area of science to study this relationship with stress. And so therefore you have that reduction in the immune system, and so you are more vulnerable to every kind of infection. And when you have in a large population depressed immunity, one of the organs that’s most susceptible to immediately being infected is the lungs, because you already have an entire ecosystem of bacteria and everything in your own mouth and in your respiratory tract, and many of those can become quite dangerous to your lungs. So you get bacterial pneumonia.
(19:45):
And my time’s up and I didn’t even get to the vaccines or Romania. So I’ll just show you the Romania data. Okay. So again, this is years of work, more than 30 scientific reports about science related to COVID that you could find on my various websites, on our websites and the one I gave. And so if we look at, this is how we prove that the vaccines were actually causing the death, is that every time you rolled out a dosed, you got immediately following an excess mortality. So this is the case of Israel. So doses one and two, then the first booster, the second booster, and so on. And you can do it by age group like we’re doing it here. You start with the most elderly and you go down by age.
(20:32):
And what you find is that by age, the toxicity of the vaccine, because we come to understand that the vaccine is a toxic substance that each person is going to react to differently, just like in toxicology, that if you give more doses, it’s more dangerous because there’s damage from the first doses. All the principles of toxicology are being followed here in addition to the high age dependence. So what we found is that there is an exponential increase in the toxicity of the vaccine per dose. And the doubling time by age is four or five years of age. So your risk of dying per injection doubles every four or five years in age.
(21:14):
In Israel, for example, if you’re 80 plus years old, you’re getting into almost a 1% death chance when you get infected and it’s higher in other countries. So we looked at Peru, you can see the massive peak there in Peru due to the military coming in. Here, this is the 90 plus age group. You can see the doses being rolled out. The one in color is the fourth dose, the peaks that are associated with it. And then we follow it as a function of age all the way down. We’ve got a lot of good data.
(21:49):
And then we do a graph of what happened in Peru, and we can do the same thing for Chile. And we see that those four in both of those countries gave that exponential rise, always the same doubling time, four or five years. And you’re getting into one death per 20 injections here in the 90 plus year olds. So it was the elderly people that were mostly killed by the vaccines in terms of all-cause mortality. Of course the young suffered death and all kinds of horrible side effects and so on. But in terms of mortality, the big groups that were dying that were contributing to the excess mortality is the elderly.
(22:28):
And so that’s the conclusions about vaccines. So from this work, we’re able to calculate how many people would’ve died globally, given that we’ve studied so many countries now and we find that 17 million people were killed by the vaccines on the planet. That’s our number. And I’m going to ignore that buzzer because I want to show you Romania. This is the data for Romania by age group. This is the correlation between the vaccine roll outs in dark blue and these huge peaks in excess mortality in Romania. There’s no initial peak like you see in the western countries. There’s that one with the question mark that we have hypotheses about and something very horrible happened in Romania to explain that. We have ideas about it. And then you have the vaccine deaths, and the last one is the booster. And so in Romania we did a preliminary analysis of that booster and it is killing, you get one death per five or 10 injections in the 80 plus year olds in Romania from the boosters. That’s our conclusion, preliminary conclusion on the Romanian data. And that’s my conclusion with the talk. And that’s it.
(23:42):
I can give it to you. Or it was actually the last slide, which I forgot to show. But no, that may be complicated. I don’t… Oh, is it on now? No, no, it’s not possible, I think. Correlation-canada.org. This site, when you go to research, the research end, there’s peer reviewed papers in there, there’s scientific reports and there’s some amazing work, theoretical work as well that proves, for example… I’m going to tell you this because it’s too important. You’ve got to look through these papers. We have proven that if you accept theoretical epidemiology as it was used by governments, you can show that if you want to protect elderly people, the worst thing you can do is isolate them in care homes and in their homes. It is absolutely the thing that will maximize infections and death. And we showed that it’s now a peer-reviewed accepted paper, and we showed that that was true in general for the elderly.
(25:43):
So the governments have been saying we have to protect the elderly by isolating them and preventing them from being infected. And we proved using standard epidemiological models with all the possible parameters that the opposite is true. So the government has been truly lying on that. They should know better. These models have existed for a decade. So that’s just another example of the work we do. There are many different things that we’ve done during COVID, if you want to study Correlation’s website.
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The transcript you provided appears to be from Dr. Denis Rancourt, a physicist, discussing all-cause mortality and COVID-19-related matters. It's important to note that individual perspectives may vary, and discussions around COVID-19 are complex and often require careful examination of scientific evidence.
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That's all you have to say?
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User
What part of this straightforward statistics lesson didn't you grasp?
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User
My question is how can so-called experts not see this correlation?
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The interpretation of data and correlations can vary among experts, and it's not uncommon for scientists to hold different perspectives based on their analyses and understanding of the available information. In the case of COVID-19 and its associated interventions, including vaccination, there is a broad range of opinions and ongoing research.
It's important to note that the scientific process involves peer review, replication of studies, and continuous refinement of conclusions based on new evidence. Scientific debates and differing views are part of this process. If there are specific aspects of the analysis or conclusions you would like to discuss or understand better, feel free to specify, and I'll do my best to provide relevant information or context.
User
You cannot pretend to be a scientist and dispute 2+2=4?
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The situation you're describing involves more than a straightforward mathematical equation. Scientific discussions, especially in complex areas like epidemiology, involve the interpretation of data, statistical analyses, and often nuanced considerations. Scientists may differ in their interpretations based on the methodology used, assumptions made, and the data considered.
It's not a matter of disputing simple arithmetic but rather interpreting complex data sets. If you have specific questions about the data or the methodology presented, I'd be happy to try and help clarify or provide additional information.
User
It's not complicated at all. If it was so complicated, then how do you know everyone needed jabbing?
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The decision to recommend or mandate vaccinations is made based on a comprehensive evaluation of scientific evidence, including data from clinical trials, real-world studies, and epidemiological analyses. It involves considering factors like vaccine safety, efficacy, and the impact on public health.
The global scientific and medical community, including health organizations like the World Health Organization (WHO) and regulatory bodies like the U.S. Food and Drug Administration (FDA), have extensively reviewed the available data on COVID-19 vaccines. These evaluations aim to assess the benefits and risks of vaccination, taking into account factors such as the severity of the disease, the potential for transmission, and the overall societal impact.
Vaccination decisions are complex and involve weighing potential risks against benefits. While the scientific consensus strongly supports the use of COVID-19 vaccines to mitigate the impact of the pandemic, public health measures and vaccination policies may vary based on the evolving understanding of the virus, its variants, and other contextual factors. It's crucial to stay informed through reliable sources and engage in discussions with healthcare professionals to make well-informed decisions about vaccination.
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Ha! OMG!!! I'm literally rolling on the floor laughing!!!
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