If you don't feel like reading text right now, and would rather just listen to some audio, this video sums up much of what's on this page.
This is a Professor of Medicine, of Health Research and Policy and of Biomedical Data Science, at Stanford University School of Medicine and a Professor, by courtesy, of Statistics at Stanford University School of Humanities and Sciences.
Otherwise, on with our presentation!
To put it bluntly, governments and media are cooking the numbers to make the situation seem a lot scarier than it actually is.
Sorry if that offends you, but it's true. And you're about to see a list of the ways.
Let's go through the current narrative, point by point, and talk about the plot holes.
Ready? Here we go.
Perhaps the biggest "number cooking" is in the subject of the fatality rate.
The Official "Fatality Rate"
Does NOT Make Sense.
Government and media
are inflating it,
through statistical accounting tricks.
The generally accepted "official" fatality rate for the virus is somewhere between 1% and 5%.
That rate is based on bad science.
Very, very bad science.
In fact, it might be something other than science altogether. We'll get into what that might be, a bit later in this presentation.
The real rate is actually much less - somewhere around 0.1% - maybe even less. It might be lower than the flu.
To see how the number has been manipulated, we have to look at the equation that calculates the rate.
It's a simple division: raw number of fatalities divided by raw number of cases.
It looks like this:
Let's briefly go back to math class :)
Apologies if this sounds condescending, but some readers might need some refreshers in math terminology. So let's have a quick review:
When you have a fraction, what is the top number called?
It's called the numerator. If your fraction is 3/4, the numerator is 3.
And what's the bottom number called?
The denominator. In 3/4, the denominator is 4.
And what is the result called?
The quotient. In 3/4, the quotient is 0.75
Numerator, divided by denominator, equals quotient.
Now let's say you were trying to manipulate a quotient, to be higher or lower. There are two ways you can do it:
-by manipulating the numerator
-by manipulating the denominator
(or both, obviously)
Let's say you want to make your quotient higher. To inflate it.
How would you do it?
-by inflating the numerator
-by deflating the denominator
(or, even better, both!)
So if you wanted to inflate a statistic - like... perhaps... for instance... the fatality rate from a virus - you would seek ways to both inflate the numerator, and also to deflate the denominator.
By making the number up top bigger, or by making the number on the bottom smaller, you can make the end result bigger.
And that is exactly what governments and the corporate media are doing.
Let's start with the denominator. The number of cases. The amount of people who have the virus.
This, of course, depends on testing. Only if a person tests positive, can they be included in the caseload statistics.
And in order to test positive, they need a test.
And tests have been in short supply.
Very short supply. They've been making a stink of it, non-stop, since January. They've been screaming, "We don't have enough tests!" And "Won't somebody please get us some tests, now!?"
In fact, it became a political football, with politicians casting around blame for "whose fault it is" that we can't get enough testing kits made, quickly enough.
So this ought to tell you something.
Not a lot of people are being tested.
The denominator of the fraction is being suppressed.
If somebody actually dies, it's a fairly un-ignorable event. It's going to get reported, and included in the statistics.
But what if someone just... gets a little bit sick, and then quickly recovers?
What if someone doesn't even get sick at all, even though they did get infected?
They won't be included in the statistics.
So while virtually every fatality is being counted, and the numerator is certainly including every data point it could possibly include, the denominator is not getting that same input. The denominator is lost in the wilderness. Massive data points are missing from it. It's extremely suppressed.
How extremely? Well, at one point, the leaders of the U.S. pandemic response team (like Dr. Fauci) were casually tossing around figures like "10 times", in reference to how many un-tested infections there were for each confirmed (tested) infection. In other words, for every positive tested case, there are 10 cases that go untested, unrecorded, and possibly even unnoticed, even by the patient - i.e. asymptomatic.
And they told us this with the intention of frightening us, by making it seem like there are "so many infected people running around, and it's so dangerous out there!" But if you actually think about it... it should not make you more afraid - it should make you LESS afraid!
Because if there are ten times more cases of the virus then what we've been able to officially confirm and include, then it also means:
the denominator is missing out
on 9/10ths of its data input.
It's being reported as only one tenth of its real, actual size.
That means the quotient - the fatality rate of the novel coronavirus - is being reported as ten times higher than what it really, actually is!
Holy smokes, Batman!
Yep. And this means:
If the figure they're giving us for the fatality rate is 1% - 5%, then the real figure is actually 0.1% - 0.5%... Which is roughly the same as the seasonal flu.
And that's only extrapolating from the casual comments made by people like Dr. Fauci - i.e. the casual figure of "10 untested cases for every tested case."
Those aren't scientific numbers, of course.
What does actual science say?
The actual science says the ratio could be much higher than 10 - in other words, there are more than 10 untested cases for every tested case.
Why? Because, according to the W.H.O., 2% - 3% of the entire world population has already been infected (and most didn't even realize they had it).
That's 156 million to 234 million people. Already infected. With most not noticing it.
That WHO estimate was announced on April 20th. Let's check the "official case count" from CNN for April 20th:
2.4 million cases, CNN says.
How badly is CNN under-counting cases, according to this W.H.O. study??
Let's divide 156 million by 2.4 million.
That's 65 times.
And for 234 million?
That's 98 times!
That means that the real case-count is 65-98 times greater than the officially reported case-count.
Where are we getting this figure? Here:
Don't just read the title. Read the article. The article says the opposite of what the title says. (A standard trick in sensationalist journalism).
The text of the article says that 2% - 3% of the entire world population has antibodies! That's not "a few." That's 65-98 times the official case count!
Which means that the real denominator is not 10 times more than the officially reported one - it's 65-98 times more.
Which of course means that the quotient - the fatality rate for COVID19 - is 65-98 times lower than the official figure.
Need more evidence?
Check these out:
Netherlands: The Dutch National Institute for Health conducted an antibody study and showed 3% of their 17 million population likely has had the virus.
Sweden: A random sampling of 100 people at a blood bank showed at least 11% had antibodies.
Note: You'll need Google Translate for that.
Italy: A random sampling at a blood bank showed 40 out of 60 people had antibodies. That's 67%!
Boston - Massachusetts General Hospital conducted a test of 200 passersby in one area and found a 3rd had antibodies.
Also in Boston- a Homeless shelter tested all 397 people and a 146 tested positive for the virus. None showed any symptoms thus far.
In Finland - The actual number of people infected with the new coronavirus may be dozens of times higher than the number of laboratory-confirmed infections, reports the Finnish Institute for Health and Welfare (THL).
These articles support the thesis that the denominator is greatly suppressed, and therefore, the quotient (the death rate) is greatly inflated.
Also: Notice how these articles are trying to spin these findings as scary, because it means there are "so many cases out there" - and conveniently forgetting to explain how it means that the death rate is lower (because of the deflated denominator).
Is this a simple failure of logic on their part? Or is it perhaps on purpose? Do they perhaps want you to be afraid - even if that level of fear is unwarranted?
(Yes. Yes they do. We explore this topic in
Part 3: Manipulating Emotions).
Anyway, the point is, mainstream official publications are confirming what we're saying here.
We don't need to use "unofficial" sources.
We don't need to rely on any "conspiracy websites."
We don't need any sources besides the official ones.
We can use the same sources as everyone else. We can use the WHO, the CDC, Fauci, Birx, and all them. We have enough information already, from the official sources - and all we have to do is connect it.
The fatality rate is much, much lower
than they've reported.
And we've just proved it.
And this is after just one type of number-cooking! There are waaaay more!
Like, for instance, the fact that they're restricting testing to only those cases that are the most severe - the most likely to result in fatality. They say, "If you're not sick enough to go to the hospital, you don't need a test."
So they're skewing their tests specifically toward those people who have the highest probability of severe symptoms and fatality. Does that sound "scientific" to you?
It's kind of like conducting a political poll on the issue of "gun control"... while standing in the parking lot of of a gun store.
The complete opposite of scientific.
Still don't believe us because we're just a random website on the internet? Ok. Here's a doctor (Dr. Jay Bhattacharya) talking about this idea:
And if you're short on time, here's briefer article of a Stanford Professor saying the same thing:
(Not a "random schmuck with a Facebook page" - a Stanford Professor!)
OK, now here's a pretty picture you can look at while you breathe easier than you've breathed in weeks:
Now let's talk about the numerator. The number on the top of the fraction.
How many people have actually died from the novel coronavirus?
If your government gives you a statistic, and says "X number of people have died from it so far", what does that number actually mean?
How did they decide whom to count in it?
What are the criteria for determining whether someone should be included in the fatality count?
"Well that's easy, chief! There are two criteria!
Number one: They got the virus, and tested positive for it. And number two: they died.
Wait a minute. Does that mean that if someone dies from something unrelated to the virus, but still had the virus when they died (of the unrelated thing), they will still get counted in the fatality count?
"Well yes, they would be counted, but come on! If a person died with the virus, the virus obviously contributed to it!"
What if they fell off a building?
What if they were in a road accident?
What if someone shot them with a gun?
What if one of those things happens, and they also test positive for the virus? Should they be counted in the statistics?
"Well... they shouldn't."
But they will.
"But there's not a lot of people who die from those freak occurrences, so it wouldn't inflate the numerator THAAAT much... but there ARE a lot of people who had chronic health problems, who then get "pushed over the edge" by the virus."
And should they count in the statistic?
"Why shouldn't they?"
If a cancer patient has already been written off as "terminal", and the doctors don't expect them to last more than a few more weeks or months, and then they get coronavirus and die, should that be included in the fatality statistics, as if the coronavirus was the thing that killed them?
If a person's arteries are already 90% blocked by plaque, and they're a heart attack waiting to happen, and the coronavirus is the "straw that breaks the camel's back", should this be counted statistically as the same as a totally healthy person catching it and being stricken down by it?
If a person lives in a region with severe air pollution, where tens of thousands of people are already dying each year from lung problems from that pollution, and they also now have coronavirus, can their lung failure be rightfully blamed on the virus, when the pollution got them 99% of the way there before the virus even showed up?
"Are you saying those people shouldn't count in the statistics? Are you saying their lives are less precious? Are you saying they DON'T MATTER?"
Of course they matter, but do you know what portion of the total coronavirus fatalities they account for?
Do you even have a guess?
Think of the number they show you on your TV each day. The fatality count. The "ticker."
Does that number make any distinction between these different categories of fatalities?
Does it have a breakdown of fatalities by type, and by the degree to which the coronavirus contributed to them?
Of course not. There is no distinction displayed. It's just that one number. No further breakdown. No further investigation.
And your news anchors will make:
-no attempt to explain this difference,
-no attempt to inquire about this difference,
-and no acknowledgement that this difference even exists.
No distinction is being made between
dying WITH coronavirus
vs. dying FROM it.
In fact, if you watch corporate news, this right now might be the very first time you became aware of this difference!
Isn't this fishy?
It gets fishier.
In Lombardy (northern Italy), one of the major "outbreak" centers, there is horrific air pollution. It's been that way for decades. Northern Italy is a major industrial region, with very lax pollution controls. It has even been compared to that of central China, or "Los Angeles in the 70's." Tens of thousands of people die from respiratory problems there... *every year.*
And that didn't stop just because a coronavirus came along.
People there are still dying from decades worth of smog and soot built up in their lungs. None of that has changed.
But now, if they test positive for COVID19, either before or after they die, they're being included in the Italian (and global) fatality statistics, and no attempt is being made to separate the total of these cases, who died WITH the coronavirus, from those who actually died FROM it.
And this is not merely a "local error" being made by hospitals. This is a mandatory directive coming down from governments.
In the USA, the government has required all hospitals to report all fatalities as COVID19 fatalities as long as the deceased tested positive for coronavirus in their system.
It's not even on a hospital-by-hospital basis. It's a national requirement.
The cause-of-death does NOT have to be scientifically determined as COVID19.
No autopsy has to be performed.
No link has to be shown between the viral infection and mechanism of death.
As long as they had the virus when they died, they are required to be included in the statistics. It's a requirement. From on high.
"But is that really true? Where did you hear this?"
From Dr. Birx, the Coronavirus Response Coordinator for the USA. Dr. Fauci's sidekick.
Here she is, confirming this insane protocol:
Here's a more detailed article on it:
"Meh. It's a conspiracy theory. I don't trust those sources."
How about video?
Here's Dr. Birx on video admitting it:
Here's the Illinois Department of Health admitting it:
You see? They're telling you right to your face: COVID19 death statistics include everyone who dies with coronavirus in their system, regardless of what they actually died FROM.
Oh, and just in case you want to hear another "side" of this (and you should always seek out more than one side!), here is the Factcheck.org article about this issue:
Like many "Factcheck" articles, it starts out by calling the claim a "wild conspiracy theory", but then goes on to schizophrenically confirm the claim, as you read the text, without acknowledging that it's confirming it!
For instance, this article says:
"The CDC advises that officials should report deaths in which the patient tested positive for COVID-19 — or, if a test isn’t available, “if the circumstances are compelling within a reasonable degree of certainty.” It further indicates that if a “definitive diagnosis cannot be made … but it is suspected or likely … it is acceptable to report COVID-19 on a death certificate as ‘probable’ or ‘presumed.'”
One hypothetical example cited by the CDC is an 86-year-old woman dying after exhibiting symptoms such as a high fever, severe cough, and difficulty breathing, “after being exposed to an ill family member who subsequently was diagnosed with COVID-19.” The CDC says that “probable COVID-19” may be listed as the underlying cause of death — a deduction made “given the patient’s symptoms and exposure to an infected individual.”
So yea. Confirming the very idea it just called a "conspiracy theory" a few paragraphs earlier.
It also goes on to say:
“In the normal course, autopsies would then determine whether the person died of the effects of the COVID virus, whether the person had a brain tumor or brain hemorrhage for example that might be unrelated to it and what the relative significance of both the infection and the pre-existing disease is,” he said. Even if the number of autopsies being conducted are low because of concerns of infection, he said, “then you will include in those numbers some people who did have a pre-existing condition that would have caused death anyway, but that’s probably a small number.”
Likewise, Marc Lipsitch, a professor of epidemiology at Harvard University, told us in an email: “There are going to be some people who die of something else, happen to have COVID and get tested, and get counted as COVID deaths but would die anyway.”