No, it isn’t. This guy appears to be Todd Callender. His numbers don’t make any sense because he’s misinterpreting the data. Don’t fall for it.
By Steve Kirsch
There are some real COVID misinformation spreaders on the Internet that may look very credible. The good news for the public is that most all of them are very easy to spot because they work for the White House, CDC, FDA, NIH or are a member of the mainstream medical community, Congress (with just a few exceptions), mainstream media, state or local government, or they are a public health official anywhere in America (except Joe Ladapo).
However, there are a few misinformation spreaders who are not as easy to identify and might look legit because they seem to say SOME things that are correct. Here’s an example of this and how to spot it: what they say is not self-consistent.
Why do they do it? It isn’t deliberate. It is because they misinterpret the data in front of them.
Check out this video before Twitter removes it:
The numbers he quoted simply do not “add up” so everyone should be very skeptical of this guy. You simply cannot have an 1100% increase in disease and only an 84% increase in all-cause mortality. That’s impossible because diseases cause about 90% of the deaths (see top causes below). So his statements are contradictory if you know a few facts. Making statements like that destroys any credibility you might have achieved.
Could there be some truth in what he says? The mortality data is elevated. But not by that much. Not even close.
Is Todd deliberately misleading people? I don’t think so.
What’s happening is that he’s misinterpreting data that was given to him, e.g., by looking at doctor visit statistics rather than disease counts. You can have tens of visits for a given new disease discovery. So if I never had cancer and now do, my doctor visits can increase from 0 to 20, but it’s still one new case of cancer.
So let’s switch gears and look at some data I collected recently from my readers. Such data is never perfect, but all data is imperfect, even data from double-blind randomized trials.
The death numbers since 2021 reported by my readers
I did a survey recently where I asked people to report cause of deaths for deaths in 2021 and beyond.
Here are the responses (raw data) so you can verify I’m not hiding anything or cherry picking.
Here’s the pivot table on causes of death vs. country.
Look at that. Cancer is killing more people than heart disease in every region except Asia (where there were only 4 responses). The consistency over each country (I picked the subgroup category randomly) shows that the subgroup analysis shows the same thing which suggests that the effect is above the noise level. What can cause pre-existing cancers to return with a vengeance? The vaccine of course!
But the vaccine also causes heart disease, but apparently re-kindled cancers far outweigh that effect. This is why accidents are way down because all the other numbers are increased by the vaccine, but not accidents! The numbers in the far right column should be monotonically decreasing because I’ve ordered the rows in the CDC official order of death count (see below) so you can see the anomalies in 2021. They aren’t. That’s hard to explain.
Now here’s what the numbers are supposed to be:
The other thing my surveys revealed is that 70% of the deaths were judged by the reporter to be vaccine related. We are trying to assess that now.
So a sizable bump in the all-cause mortality (ACM) is not that unreasonable, but I suspect that the vaccine is increasing ACM by more than 20%.
The key takeaways from my survey (these are signals at this point):
- Cancer is now the #1 killer, replacing heart disease.
- COVID kills fewer people than heart disease (i.e., <700,000 per year)
- More than 20% of excess deaths from the vaccine (comparable to # killed by heart disease)
Be careful to give the same scrutiny to info that confirms your beliefs vs. goes against your beliefs. The failure to verify information is what got people into this mess in the first place.
It’s clear to me that the statements in this video are not self-consistent and cannot be right. But that doesn’t mean there isn’t a there there.
On the other hand, survey data, such as the one I did, is particularly subject to biases that need to be carefully considered. I’m not going to the bank with my survey data, but use it as a way to identify potential signals.
I will say that I see clear and consistent evidence that cancers are way up. I hear story after story of people developing a new cancer or their cancer which was in remission coming back with a vengeance. It’s confirmed in surveys and in talking to doctors. That’s tough to explain if it isn’t the vaccine causing it. The survey data is quite consistent in each country and there is no bias in the survey that would favor cancer over heart disease. I don’t think anyone can explain the cause if it isn’t the vaccine.