This is interesting an deserves to be reported, showing high creativity with statistical methodology. Steve Kirsch had the idea of a survey to compare the all-cause mortality (ACM) death rates just PRIOR to a vaccine dose to the ACM death rates immediately AFTER the dose, based upon his readers to his popular blog. This gave him a population sample of 400. He then, in the survey, essentially ascertained that there was a report by each person based on what they knew from personal experience, of more deaths of people they knew after vaccination than the number of deaths right before they were going to be vaccinated. If the vaccines were safe, that is impossible. As well, if the vaccines are perfectly safe:
- “The death rates immediately prior to any dose should be exactly the same as the death rate immediately after the dose.
- The death rate should not be dose dependent. It should be 1:1 on every single dose (for the death rate before: after).”
These conditions were also violated, by a factor of 5 to 8 times. With some statistical work, Kirsch came up with a figure for the US, of 500,000 killed by the vax!
“A simple survey anyone can do provides convincing evidence that the COVID vaccines have killed over 500,000 Americans. They should be halted. Now.
Executive summary
A simple survey of my readers provided some extremely compelling evidence that 1) the US government has killed over 500,000 previously healthy Americans and 2) that the vaccine actually caused the deaths.
It took me around 30 minutes to create the survey and 11 hours to wait for highly statistically significant results.
I was able to accomplish something in less than 12 hours that the CDC has been unable to accomplish in 18 months: prove causality. We see both dose dependency and enormous changes in ACM deaths pre- vs. post-vaccine. We satisfy all five Bradford-Hill criteria applicable to vaccines.
We used 400 independent observers. I should note that all follow my Substack so they are correlated: all have excellent judgment, high intelligence, and immunity from mass formation effects. So they have the ability to see what is truly going on.
The survey compared the all-cause mortality (ACM) death rates just PRIOR to a vaccine dose to the ACM death rates immediately AFTER the dose. I predicted they would be dramatically higher after the dose and the effect would be dose dependent. It appears I was right. In fact, the survey projects far more deaths than I thought possible.
The number of deaths computed from the reports could be as high as 2M Americans, but the 500,000 number seems more credible, so I’m discounting the result by 4X to account for biases and confounders.
I don’t think there is any way anyone is going to be able to “explain away” these results once we redo the survey with a better set of controls (the next step).
And these results are ONLY counting the all-cause mortality increase for just the one month after each shot. We know you can die a year later from these vaccines.
We found Dose #4 caused only a 1.27X increase compared with 5.5X to 8.3X for doses 1 and 2 respectively and 2.3X for Dose #3. If this were a highly biased population, Dose 4 would have caused a larger discrepancy, but it’s approaching 1:1 as we’d expect.
The decreasing ACM increase with later shots makes sense… The vaccine eliminates anyone whose immune system is susceptible to auto-immune attacks on the spike protein. If it hasn’t killed you after 3 shots, it’s less likely to kill you on shot #4. You’re immune due to both survivor bias and the fact that your immune system has recognized the vaccine as an invader and clears it from the system quicker than on shots 1 and 2. This of course says nothing about it’s impact on effectiveness against the virus which is likely pretty minimal at this point which is a story for another day.
The higher ACM differential on Dose 2 was interesting. This may be somewhat of a poison accumulation effect. You’re basically doubling the dose over a 4 week period rather than giving your body time to recover.
Note that this factor is simply the difference between the ACM before the shot vs. after the shot. We have no idea whether the ACM goes back to baseline between shots or not. It likely does drop. We don’t know how fast. Hence, the progressively decreasing impact on ACM increases due to the jab. It could very well be that your ACM is 1.1X your baseline months or years after the shots.
When you do the math, based on these numbers, well over 500,000 people have been killed by the vaccines so far.
If the survey were more precise, I’d expect lower ACM increases, but still a final death toll north of 500,000.
The 500K excess death estimate is supported by the actual US mortality numbers as being plausible (which have a total excess death count of roughly 1M deaths since Jan 2021).
My colleagues are looking at this data and mulling over it.
We have identified a very large signal that I don’t think will go away when we redo the survey. We will need to think carefully about the next iteration of the survey and have the protocol peer reviewed to eliminate biases before we launch it. Now we know this will be time well spent.
So don’t break out the champagne just yet. But I think you’ll want to get it ready. We are getting very close.
Introduction
I thought my May 13 survey would be important. I was right. I hit the jackpot on this one. Even if the effects are 100X smaller than what we found, it’s still 10X more than any reasonable stopping condition for a vaccine (>1 death per million vaccinated).
Everyone I know has reported more deaths after vaccination than the number of deaths right before they were going to be vaccinated. That’s impossible if the vaccines are safe.
If the vaccines are perfectly safe:
- The death rates immediately prior to any dose should be exactly the same as the death rate immediately after the dose.
- The death rate should not be dose dependent. It should be 1:1 on every single dose (for the death rate before:after).
Guess what? Both of these “rules” are violated. Not by a little. By a lot. Like a factor of 5X to 8X increase in ACM in the month after the shot compared to the month before the shot according to 400 independent investigators.
And this is a VERY statistically significant result just 11 hours after I posted my Substack article.
P-value calculation on the Dose 1 ACM change shows it is very unlikely it happened by chance.
The CDC had 18 months to do this sort of survey and still hasn’t done it. They probably never will.
It’s a valid study. It just needs to be re-done just a bit more carefully.
The data
You can download the survey results here (xlsx file).
This is the first 400 form submissions.
People may try to game the system after this point so subsequent data may be unreliable.
But these first 400 responses were made under the radar and I have the email address of the person who submitted each row so that PolitiFact can verify every line. Of course, they won’t fact check me because if they verify it, it’s game over. Fact checkers can do their own survey and report the results. If they game the outcome, it will be very clear that they are not credible.
Eventually the NY Times will do the same survey and validate the results. It may be several years before they attempt do that though.
The back of the envelope quick analysis
What this means is devastating to the “safe and effective” narrative.
It also DESTROYS the CDC argument that there is no link between vaccines and death. It would be hard for them to explain this away: the ACM effect is huge, it is statistically significant, and it is dose dependent.
So let’s do the math. I’m just going to use round numbers because this is just an estimate. To do it right, we’d stratify by age, but we’re going to use average death rates, etc.
Around 3M people die a year in the US which is roughly a 0.86% death rate.
They don’t die evenly throughout the year, so like I said, this is just a rough estimate just to find the ballpark number.
According to Google (which uses Our World in Data):
250M got dose 1. The monthly death rate is 250M/12*.0086 = 179K. So if ACM is elevated to 5X normal, we’d expect 4*179K= 716K excess deaths. Just from the dose 1 effect. Whoa! That’s way higher than I expected and higher than the 610K available to us. So I believe our survey is overstating the effect.
220M got dose 2. So we’d do the same math as before. Our spreadsheet shows a 8X normal death rate in the following month so (8-1)*(220/12*.0086)= 1.1M excess deaths. Whoa! One shot does it all!
100M got booster which shows a 2.3X increase so (2.3-1)*(100/12*.0086)=93K excess deaths.
So 716+1100+93 = 1.9M excess deaths clearly caused by the vaccines.
Is 1.9M excess deaths too high? That’s equivalent to a 40% ACM increase over the entire 18 month period (not just in a few quarters)
So based on our very simple survey, we’d predict the vaccines caused 1.9M excess deaths total so far due to the all-cause mortality impacts. Whoa. I wasn’t expecting that. That seems way too high. We can’t see that in the CDC or Medicare numbers and those look consistent with each other. The most we can find is 1M excess deaths. So this is 2X too high.
If our calculations are right, it would mean 31% of all deaths over 18 months (1.9/(1.9+2.8*1.5)) are from the vaccine. What is interesting is that we’ve talked to embalmers who are seeing well over 60% of the deaths they do have these strange clots, only found in vaccinated people, that likely precipitated the death. So our survey is actually very consistent with the embalmer data; in fact we undershoot that data point. If we go lower, how do we explain the high rate of these tell-tale clots?
Our VAERS excess death estimate used 12,000 US deaths in VAERS (subtracting out background deaths)*41 (the URF) = 492,000 estimated excess deaths caused by the vaccine. But the VAERS estimate should be conservative since the URF was calculated for the “very best case” event, so any practical URF should be higher than 41. So we have consistency in our prediction (since the VAERS estimate is a minimum).
In Feb '22, Matthew Crawford wrote about a German researcher who found 1 vax death per 2,300 jabs. In the US, there are over 580M jabs, so that would now be over 230K vax deaths.
CDC death data shows a population-adjusted increase in US ACM of 1.3 million since Jan 2020. If the causes of death are 1/3 Covid, 1/3 lockdowns, and 1/3 vaxes, that's more than 400K from each cause.
So we have:
- Based on the CDC numbers, we’re too high (less than 1M to allocate in 2021 and 2022) by at least a factor of 2
- Based on VAERS, we’re very believable (since VAERS is at least 480K)
- Based on independent methods (Crawford’s work), we could be a factor of 8 too high
In situations like this, it is best to be conservative and believe that we are overshooting the target here because our data is biased, which we expected might happen.
Limitation: Biases
There are a couple of obvious biases in this survey:
- The survey went to my followers who believe the vaccines are dangerous and are thus more likely to notice and remember what they are looking for which is deaths post vax. This doesn’t mean they are lying. It’s simply that you are going to notice things that you are looking for (watch this video).
- Even if you are completely unbiased, there will be selective recall. You are much more likely to know that Uncle Max died a week AFTER his vaccine than a week BEFORE he was SUPPOSED to get his vaccine.
My readers could be more “attuned” to hearing about deaths AFTER the vax than BEFORE the vax.
The survey could be tweaked to limit the results to immediate family members to eliminate this “reach” bias.
And secondly, the survey should be taken using an unbiased list by a third-party survey organization.
I’m actually hoping correcting these biases will reduce the effect observed by a factor of 4X or more. That will make the results of this survey more believable.
Sanity check with the CDC ACM data
Someone could point out that the CDC January to March ACM numbers (or the more detailed weekly numbers here for 2020-2022 and here for 2014-2019) weren’t 5X higher than the normal monthly numbers.
But that’s to be expected since everyone didn’t get their first dose every month!! It was a one time event that would effectively boost the annual ACM by 1.3X (which is (11+5)/12 since 11 months we have 1 death and 1 month we have 5 deaths which is 5x a normal month).
So if Dose 1 elevates the total annual ACM by 1.3X, if Dose 1 is given over 6 months, we’d expect a given month to be elevated by 1.6X (since 12*1.3X = 6*1.6+6*1)
ACM in Jan 2020: 60K
ACM in Jan 2021: 87K
So it only went up 1.6X which is what we expected.
Sanity check with the Medicare ACM numbers
The CDC ACM numbers could be wrong. How would anyone even know?
So let’s double check with the Medicare numbers. We have a friend on the inside who provided this graph.
We see ACM went up from around 200,000 per month to over 300,000 per month.
So that was a good sanity check on the CDC numbers that they went up just like the Medicare numbers did. Otherwise, we’d suspect that someone is cooking the books.
Sanity check with excess deaths
Let’s do a simple excess death calculation in 2019 vs. 2021 and 2022 to see how many excess deaths we’ve generated (approximately).
Using those CDC links, we compute the ACM for 2019 which we’ll use as our standard for simplicity (we are just trying to get a ballpark number here).
2019 ACM: 2,845,957 (baseline)
2019 ACM (first 7 weeks): 407,480
2021 ACM: 3,455,074
2022 ACM (first 7 weeks): 557,103
So approx excess ACM in 2021: 610K
Excess in 2022 (first 7 weeks): 150K
Extrapolate to week 19: 400K (this is because the CDC numbers aren’t fully baked the closer you get to the current date)
Total excess deaths available to allocated to various causes (COVID, lockdowns, vaccines) is approximately: ~1M
Sanity check with Dose 1, 2, 3 timing
Because the numbers were so large, I didn’t do an analysis by timing, looking at the rollout number of each of the doses and comparing that to the excess deaths available to be claimed within a given month.
Once the numbers are more “in line” with the CDC death data, we can make those sanity checks.
The Bradford-Hill Criteria
See this article which lists the five criteria.
The five Bradford-Hill criteria applicable to vaccines
Trust me on the biological plausibility. Otherwise, watch me on the classic Darkhorse Podcast with Robert Malone that was censored from YouTube after 1M views and got Bret Weinstein banned from YouTube (original 3 hour version and 1 hour short version).
We have causality. There is no way the CDC can deny this.
But the CDC refuses to talk to any of us so that way they can claim plausible deniability in case anyone asks.
I’ve emailed
Even if we got it wrong by 1,000X, the vaccine should still be halted for everyone NOW
Even if we are super biased and got it wrong by 1,000X and the “correct” number is just 2,000 deaths, that is FAR beyond the safety stopping condition of a vaccine which should be fewer than 1 person per million dosed according to Paul Offit who is a recognized authority on the matter. Which means our stopping condition is 250 deaths. 2,000 vaccine caused deaths is 8X the stopping condition.
As I pointed out earlier, Mathew Crawford arrived at 1 death per 2,300 doses using two completely different methods. Whoa. He made the excellent point that that is 434 deaths per million doses which is well above the stopping condition of 1 death per million doses. He pointed this out which is very important:
… but the exact number is less the point than the observation: we need to immediately halt the experimental mass injection campaign.
Is the vaccine useful for those over 80? I seriously doubt it, but where is the risk benefit analysis to prove it? Until we have that, you cannot take the chance (especially since we have abundant very credible anecdotal data that the vaccines are a menace to the elderly).
We have no credible risk benefit analysis for any age group. We should be getting these monthly since vaccine efficacy changes over time and variants. The CDC’s VSD analysis was garbage and the Pfizer trial showed we kill around 7 people from the vaccine for every person we save. That was the best point estimate from the data, even though it wasn’t statistically significant. See my Elephant in the Room presentation.
Long term effects
This survey only considered the impact of a single month post-vaccine.
What it didn’t consider is anything beyond that.
We still have to see the long-term side-effects of these experimental injections. I estimate that these will be at least as much, but harder to spot. Many others will see a reduction of their life span.
Long term effects that are deadly and seem very common: (1) Sticky blood clots (as reported by coroners, most people are dying from them or with them). (2) Hidden damage to brain, heart or other vital organs. (3) Cancer. (4) Auto-immunity (5) VAIDS. Other life-reducing factors: (6) infertility (7) prion diseases (8) long term disabilities.
Are you feeling lucky?
You don’t have to take my word for it
I’m not asking you to believe me. After all, I am one of the world’s top misinformation spreaders.
All I’m saying is you can do your own survey and replicate this result yourself.
Feel free to tighten the time window too for even more dramatic numbers.
You can replicate my Google survey or you can do a simple Gab or Twitter survey. I can’t do a Twitter survey myself since I’m permanently banned.
A simplified survey on Gab is all it takes to replicate the result youself. On Gab, the results just one hour later tell the story: a 9X difference between the number of events BEFORE and AFTER the shot (2 week time window in this case). Click the image to get the final result (24 hour survey window).
Summary
Our estimate of 2M deaths seems too high based on the CDC numbers, but too low based on the embalmer death data. But even if we got it wrong by a factor of 1,000 (which I doubt), the vaccines should be halted now.
This survey (along with biological plausibility) meets all five Bradford-Hill causality criteria and shows a number of deaths too large to ignore.”