I have been wondering for a while how much "counting the vaxxed as those 14 days past the jab" is hurting the unvaxxed numbers. This article is shocking. It's grievous how much Pharma and govt agencies are withholding and twisting information.
I don't usually post but thank you El Gato Malo for writing all of your articles. You have done so much work and there are many of us who greatly appreciate it. And I like the cats pics. ;)
Anyone 12-14 days from their 2nd vax or booster w/ an adverse event or death were counted as UNvaxed, to skew unvax’d figures to “prove” the unvax’d were leading cases/ hospitalizations/ deaths when it is really the vax’d who are the leading numbers
Can't say I agree with you on the cat pics Nicole, but I really agree with you thanking Gato for all the effort he has put into producing some great information. Cheers.
Whilst we endeavor to make our products toxic, we make no representations or warranties of any kind, express or implied about their efficacy and safety.
We cannot guarantee that your gene 144 won’t be deleted, your X / Y Chromosome won’t be inverted, your gene 69-70 won’t be deleted or mutated, that you may experience loss-of-function due to protein folding, that your gene E1, E3, E4 won’t be deleted, that you won’t receive shots full of magnetic graphene oxides and nano-biosensors (motherboards, transistors, routers, antennas).
We do not guarantee that you won’t be MAC Addressed as per Lord Schwab’s instructions (COVID -19 is a rare but narrow window of opportunity to rethink, reinvent, reset our world).
By using our products you agree that you automatically become legally a trans-human and therefore our property since you are GM-modified using our patented mRNAs (CERTIORARI 12–398).
Trans-humans do not enjoy any human or other rights of a state and this applies worldwide. Our patents are under US jurisdiction and law, where they were registered.
Any reliance you place on our products is therefore strictly at your own risk.
I would actually rather prefer to think the lies were to keep those of us awake & courageous from knowing & revolting. Otherwise lulling the masses w/ lullaby lies
It's well presented in the Rockfeller Locktep 2010 report - the master plan for the ongoing scam. The plan said clearly that the virus to be released in Wuhan in 2019 will not be very dangerous and will be used only to force people to get quackcinated...The real bioweapon is not SARS-Cov-2, it's the "vaccine" designed to reduce the population. These are pre-meditated crimes.
The only logical reason for defining an "early post-booster" category of day 3-7 is to conceal the effects on their numbers of the entire post-booster period. Don't we know, for instance, that the worst adverse effects happen in the first 48 hours post vaccination? In doing so, they can dismiss analyses like yours that are forced to make assumptions based on their purposefully incomplete data. They know few are going to see your analysis let along attempt to follow your logic. Pure obfuscation at its worst.
Good work. Rigging studies is of course de rigueur and has been going on decades, which is why we are at the edge of the failure of so many systems that we’re on the verge of either a revolution or total destruction. But of course that is the story of central authority for 10k years. Hopefully we can do it peacefully. Sometimes the fraud is methodological, sometimes analytical. In my own particular line of work, it generally comes under methodology. e.g. "Let's assess the effectiveness of a fever vaccine by letting people in the trial self-dose with anti-pyretics to suppress their fever." haha
There are peer-reviewed publications since early 2020 that proved that 95% efficacy claimed by Schizer was useless. Manufacturers are using relative efficacy (~95%) instead of absolute efficacy ( < 0.7%) to fool the world. None of the transgenic jabs on the market has an absolute efficacy > 0.7% meaning that they were USELESS since day 1.
Yes, exactly. And plenty of smart people have constantly pointed out that all cause mortality was higher in the treatment group. I think there was something like a 400% increase in heart issues in the treatment group with all cause mortality being over 30% higher.
This by itself should have been disqualifying. But when the regulatory agency and big pharma are essentially the same organization you get what we have.
Yes. Ultimately the public is going to have to get smarter, and sometimes that can only happen with major crises like that give it a huge kick in the pants.
This is the kind of systemic collapse you get when the public thinks it can outsource its thinking to "regulators" and the rest of the pharma/medical/academic industrial complex.
The beatings will continue until morale improves. Until then, it's Darwin Doin Work.
What amazed me most was that MDs are getting quackcinated without asking real questions. I am not from the medical field background but I had gathered all scientific evidence that proved clearly to me that these were fakes before December 2020 EUA and I've since posted hundreds of messages on the internet about the ongoing global scam.
How do you fix a system where those who are supposed to lead are quacks?
You are 100% correct. It doesn't surprise me at all, though. Perhaps 1 in 20 doctors can think properly. Most are idiots. It's one of the most brainwashed professions on earth. Nurses refuse in high percentages, I'd bet, because they see real world evidence. The American Medical Association is a sort of a cult, really. If you want to read really good medical writing, go for instance, to Colleen Huber's substack, The Defeat of COVID. She is NMD. Very few physicians (MDs) have the ability to break free from their training (brainwashing), rote textbook memorization, and techician type robot training to really think. The type of thinking done by HouseMD just isn't really done by most doctors. It's a nice mythology.
This is, in my not so humble opinion, one way to fix a system run by quacks. (Hopefully the complete collapse of the system and emergence of decentralized solutions will help to accomplish it):
I got a very similar opinion from Dr TenPenny. For her, the only way out of this mess is to scrap the whole system and start from scratch. Rockfeller Foundation turned medical schools in the US into Madrassas.
I also got the same feeling from a British musician who complains that when he visits a doctor he spends 95% of the time watching his computer screen instead of asking him questions. What's the point of visiting a doctor who cannot even observe you physically to see if external signs of health issues can be detected?
i just think back to people I knew in high school who i thought were idiots and at a reunion years later i found out where now doctors. i simply thought, "really?!?!" they did not give me confidence in the medical profession.
According to the Slovenian nurse who revealed the tricks behind these injections, saline is mostly used for politicians who get jabbed in public. She was fired.
I've seen pictures of many dead/disabled doctors online - one died in Eastern Canada shortly after his booster shot. One in the US was a surgeon and can no longer make use of his right hand after his injection. He used to perform 800+ surgeries per year - not anymore after Fauci convinced him that poisons were safe and effective.
gato, you're wonderful, but I think there is a big mistake here.
Let:
a = number of infections in booster group
b = number of person-days in booster group
c = number of infections in early postbooster group
d = number of person-days in early postbooster group
I think to properly combine the risks from the "early postbooster" and "boosted" groups, you need to do (a + c) / (b + d), whereas what you've done is a / b + c / d.
As a toy example to demonstrate this, imagine the booster were just a placebo, and neither increased nor decreased your chance of being infected. Then the rate of infection in each of the three groups (unboosted, early postbooster, booster) would be exactly the same number. Let's say, 30,000 infections per 100,000 population per year. (This is because the paper divides by the number of person-days at risk instead of merely the population.)
I think what you're doing is tantamount to combining the 30,000 infections per 100k per year from the boosted group and the 30,000 infections per 100k per year from the early postbooster group and concluding that the booster doubles your infection rate per year to 60,000 per 100k, when in reality it merely did nothing at all.
I was thinking something similar - is it appropriate to pro-rata the 5 day early booster period up to 12 days (2.4x increase) if it's already represented as a rate per 100k per year? As a very rough assumption we could expect 2.4x the number of infections during a period 2.4x as long, so the math of infections / person years would come out the same when looking at just that group instead of 2.4x larger.
I think the solution is similar to your method (if you were to choose to pro-rata it at all):
(booster infections + early booster infections x 2.4) / (booster person-years + early booster person years x 2.4)
edit: by my math, this puts it in the 70-75% effectiveness ballpark, which is still higher than any other source I've seen on effectiveness against infection (particularly when it's meant to be a comparison to people with 2 doses, not unvaccinated)
You're correct, the math is very wrong. To a close approximation, the early post booster rate is equivalent to 5 more days at the original double vaxed rate. Adding it in properly approximately doubles the rate of infection for the boosted category, but it's still well below double vaxed.
He's onto something about the weird keyhole they selected, that happens to be exactly the same rate as the double vaxed rate. Maybe the other days had higher levels? Who knows. Even so it's unlikely that it is so bad that it would produce negative efficacy vs. the double vaxed rate, it would need to be 10x worse.
Working through the numbers for 60+ age group per 100k/y - whereas Gato’s approach (simply adding boost & early boost figures for 100k/y) results in combined boost figure of 17,307 (before 2.4 adjustment), the alternate approach gives a combined boost figure of 3,259 per 100k/y, before 2.4 adjustment. That’s a big difference- 17,307 versus 3,259- and I’d like to know which is correct.
The calculation of risk for each separate category (boosted and early-pre-booster) is correct. That is, it tells you your risk per 100k person-years for time spent in that category. To use that kind of metric to assess your own risk, you would multiply it by the amount of time (in years) you're in that category. For example, Risk/p/y * 1 year would tell you your risk, being in that category for 1 year (in units of per-100k). Does that make sense?
But here's the problem: you can't just add these risk numbers to get an aggregate. The reason is that the amount of time spent in each category must be taken into account. If you spend 1 week in prebooster and 51 weeks in boosted, then the aggregate needs to be (Rp * 1 + Rb * 51) / 52, in order to correctly account for the fraction of time spent in each risk category (where Rp and Rb are the risk values).
In this case, the original data included the amount of person-years the cohort spent in each category, so its easy to aggregate correctly by summing the event counts, and dividing by the total person-years. This would give you an aggregate risk for the population, having spent some time in preboosted and a lot more time in boosted.
Here's a simple example to explain:
Suppose we have data over 10 days. The events occur as follows, starting from day 1, the event counts observed are: 2,0,1,1,1,1,1,1,1,1,1.
That is, 2 events on day 1, none on day 2, and 1 on each of day 3-10.
The correct way to compute the rate here is total events / total days: 10 events over 10 days = 1 event per day on average.
But we want to compare early and late rates because they are different: so now we calculate the rate on the first day, and the rate on the following 9 days separately.
The first day has 2 events on 1 day, so 2/1 = 2 events per day.
The following 9 days have 8 events over 9 days, so 8/9 = 0.88 events per day on average.
Thus we see two different rates, 2 vs. 0.88. This correctly expresses a higher rate of events at the start of the dataset.
But if we now try to create an aggregate by just adding those rates we get 2 + 0.88 = 2.88 events per day as the aggregate rate. But we know from the start that the real aggregate rate is 1/day - and 2.88/day is clearly wrong because if we multiplied that out by 10 days we would get 28.8 events over the 10 days, not 10.
The correct way to combine the rates we would need to weight them by the amount of time in each:
(2*1 + 0.88*9)/10 = (2+8)/10 = 10/10 = 1.
There we got the correct answer back again.
Or, ignore the rates and use our original formula of dividing total events by total time:
Thank you, that is very clear. I’ve been tossing this around in my mind, every time Gato posts I think it’s going to be about correcting this, but it isn’t (and sadly isn’t looking like it will be at this point). As described, this is a gross mathematical error. Imagine a baseball player had an average of .300 for their first ten games and then .250 for the next 152. It would be wrong enough to say that they’re a .275 hitter, but what Gato has done is equivalent to saying they’re a .550 hitter!
Funny you say this because I kept having the same hopeful expectation. When the next post was entitled "Burnout" I thought it would be a mea culpa saying, sorry guys I'm a bit burned out and I got it wrong on the last post. But sadly, no. It's a real shame because this post has been reposted uncritically in at least a few places I have seen. Shoutout to Brian Mowrey who caught this https://unglossed.substack.com/p/norcal-pregnancy-study-etc?s=r and I *highly* recommend subscribing. He has been consistently accurate and honest, and very light on the confirmation bias.
In any case, the error in this post is egregious, no other way to put it.
Hehe, that’s exactly what I thought the “Burnout” article was going to say too!
It is unfortunate that this has already been fairly widely disseminated, as we know from the mainstream, even later corrections never carry the same weight as the initial claim. I know Gato is just a kitty and we all make mistakes… and it’s totally unfair that us questioning the narrative need to be completely accurate at all times or else we’re thrown out with the bathwater, but that’s the reality. We don’t get the same benefit given to CNN, Fauci, and the rest. Personally though, most of the reason I read these substacks IS for data breakdown and analysis, not for waxing poetic. I can form my own opinions with little effort, doing the math myself is a bit more time consuming. I’m no statistician, but I’ve done enough number crunching at various jobs that this error is so profound that it just didn’t feel right immediately, and on further review, it’s such an “entry-level” mistake that it really makes me doubt Gato’s math acumen entirely. Maybe that’s unfair, but there’s a lot of people writing out there and only so many hours in the day, so the longer this goes unaddressed, the more I think I should just check out on this substack.
Thanks for the link to Brian Mowrey! Looks good so far!
Also, the study does use "daily exposure risk" as a covariate, which means that it does account, at least indirectly, for pre-existing immunity. (Not very well, because it uses a multivariate linear model and the differential effect of pre-existing immunity probably depends on all sorts of things, but at least a little.)
I agree with your assessment that this study is questionable, but I disagree with your assessment that it actually proves boosters have negative efficacy.
Thanks for laying that out. I didn’t go and run the numbers myself but it seems like the adjustments Gato made were far too large on first read. Hopefully this is addressed.
Gato, you have a gross mathematical error in your calculations above.
Yes, the absolute number of infections in the first 12 days is probably ~2.4 times higher than the number given in the day 3-7 category. However, so is the number of person years.
As soon as you convert to the relative measure, you can no longer argue about hidden risk in the early booster group.
2,500 infections in 5 million person days lead to the same rate as 6,000 infections in 12 million person days. The rate stays the same.
Even worse, you seem to have applied the correction factor of ~2.4 to the sum of the relative risk (boosted + early boosted). So not only are you correcting an already corrected (relative) number, you are even correcting the part of that number that doesn't need correction - the boosted group.
As much as I agree with you on the point of data manipulation by definition of vaxxed/boosted, this post is simply teeming with errors and I'm afraid the majority of your readers will lack the mathematical/statistical prowess to realise it.
Agree with your first point but not the second- when I first looked at Gato’s table last night I thought, like you, that the 2.4 adjustment had been applied to both groups, but in the lines I checked it was applied to early boosted group only, with boosted group then added on.
Hate to be bearer of bad news but the initial analyses is flawed. You cannot add the per 100k/yr data in this way. When you divided the infections by person years the data was already normalized for time. Changing from 5 days to 12 days adjusts both denominator and numerator by the same factor which divides out. Instead what should been done is to multiple the infections and the days at risk by the 12/5 factor. Then add these amounts to the booster days at risk and infections. Then calculated the adjusted infections for 100k/yr from these totals. Unfortunately everything that follows from these calculations is flawed. Sorry gato.
Jalawaco is absolutely correct. Gato is adding rates that have different denominators. If you look at the raw rate in Gato's table for the early prebooster category, the rate is slightly smaller than the rate for double vaxed. In other words, being prebooster for 5 days is pretty much the same as just being double vaxed for 5 more days. This has a negligible effect on the outcome - it's like delaying the booster 5 days. But adding the rates like he did causes a very wrong answer.
It's definitely fishy that they selected those 5 days - but to cause negative efficacy you would need to have 10x the rate of infection in those extra days, which is probably unlikely. I'm sure it's bad, but honestly probably not that bad.
50% of the FDA budget comes from pharmaceutical companies. Many people in the CDC, NIAID, NIH get royalties from pharma products that are rubber stamped for the plebs.
Back during the OxyContin disaster Perdue was funding the AMA, I think at least half of the AMA budget came from Perdue. You buy the regulators and there are no “regulators”.
If only it were limited to this situation and Pfizer but Enron accounting and definition loopholes are where lobbyists secure their bespoke Turnbull & Asser style!
Very good. I wrote a little thought experiment how the way we judge the vaccines would indeed show objectively crappy vaccines to be effective. The whole thing is a giant con.
Actually, you even went so far as accepting their proposition that a bioweapon was a "vaccine" to be tested for efficacy.
After reading the plan elaborated by Rockfeller Foundation in 2010, I understood in late 2020 that SARS-Cov-2 released in Wuhan was just a bait and that the real bioweapon was going to be sold to the public as "vaccines". SARS-Cov-2 has been shown to have HIV inserts as specified in the 2010 plan and the HIV inserts were patented by Fauci himself.
The entire plan was detailed in the lockstep 2010 report below:
You know who was wise enough not to? Novak Djokovic
You know who just got blown out of a match and complained of it feeling like "Needles" in his chest with every breath? Rafael Nadal, the same Rafael Nadal who said:
"He made his own decisions, and everybody is free to take their own decisions, but then there are some consequences,"
"From my point of view, that's the only thing that I can say is I believe in what the people who know about medicine say, and if the people say that we need to get vaccinated, we need to get the vaccine."
We know these are not really "vaccines." Instead of using the words "unvaccinated" or "boosted" or "fully vaccinated," from now on I will substitute variations on the word "poisoned."
I.e., "no, thankfully I have not been poisoned and I will do my utmost to avoid doing so."
"You are saying that you only feel safe when you are surrounded by other poisoned people such as yourself, and you are afraid of being around my high level of health?"
"You have received two doses of poison, in other words you are apparently fully poisoned."
"Perhaps you would like to be boosted with some more of the same poison you had previously, since you are not satisfied yet with the cumulative damage already done?"
"You are not 'up to date' on the level of poison in your system. Better keep it topped off and levels high for maximum damage."
Many of us are concerned with toxins in our environment, or that of our children. We try to eat organic, whole foods and avoid junk food. We use safe and natural cleaning products. This is like the junk food of medicine. It's fake, it is full of chemicals, you don't know exactly what it's doing to you, but it can't be anything good. All of your friends are taking it and you don't want to feel left out; you'd rather be a part of the cool kid group, even if they are a bunch of crackheads. You might be addicted to it, but you would be better off if you quit and find some better influences.
This has been the theme throughout these studies, most of which are published in the NEJM (which published surgisphere and whose chief editor is the one that wanted to experiment on children with the vaccine rollout). There is an inate survival bias in this per-protocol analysis instead of using intention-to-treat, which is what should have been done. The allocation of anyone who has received the treatment but when they die or are hospitalised to be counted in the non-treatment arm is scientific fraud. It's actually easy to tell that they have misrepresented the data because the hospitalisation and death rate for the "2-dose" group in the booster paper is the same as the "unvaccinated" in the original paper. So either the vaccine didn't work or they just use the miscategorisation trick against whichever group they are comparing their wonder drug to. Great stuff
Good article, but some points of critisism, some of which you already mention:
1) Two years in, any data that doesn't take natural immunity into account is close to useless. You already state "thus got more advantage from greater pre-existing immunity". That is key. There are huge behavioural differences between vaxed, unvaxed and boosted, and as one aspect of that differences in if they 'had it'. natural immunity has been shown now definitive to be far supperiour to being vaxed and/or boosted.
2) Omiron became an upper respiratory illness, so humoral vaccines by definition do nothing. So any large difference in infections make me suspicious in general. It shows me that the data cohorts are not equal. An virus that can replicate in the throat outside reach of anything good or bad in the humoral parts of the body, shouldn't affect infection. Outcome yes, not infection. So either we have hit a revolutionary bad mechanism, or we are looking at exceptionally bad data. I know the first one is a popular topic on skeptic websites, but my money is on the first. Especially since the poor data, as explained in the first part of the article. Cohorts are not euql and not even stable unequal.
E.g. Two examples of where behaviour issues also play a role.
First, many of the boosted crowd have been the ones that also worked from home, hunkered down, avoided groups, etc. Now the restrictions are being lifted they are all getting infected in massive numbers. If you were unvaxed, your probably also the personality that didn't avoid large crowds, etc in the first place. That matters in terms of natural immunity.
Also for elderly who live in nursing homes they are all (forced/encouraged) vaxed, but if one of them or one of the caregiver gets omicron, the entire nursing home gets it. So hence you get huge waves. The living at home (more likely to be unvaxed or just double double vaxed) will benefit from these statistics.
And last, testing behaviour is non-symmetrical. Neurotic boosted are far more likely to get tested. So do people in nursing homes. Various studies showed a strong causality (which inherently is not just correlation) between testing quantity and testing positive quantity. So the testing rate must be equal to not get inherent higher infection quantity. In reverse if the testing rates are hence not equal between cohorts, you get different infection rates outcome.
If the test mechanism is crap (and it is), then all test results are crap.
More importantly, this retreat to 'cohorts not equal' is a game that can be played by both sides of the issue, forever. There's always some previously unknown factor that any shyster can throw into the apple cart in an attempt to upset it. Since you're not doing your own side (whatever that is) any good with this approach, then my question is, why use it?
Yes, it can be played by both sides. That is my point - don't play that game. The CDC and other governments played it until the results did not favor them. Now they start hiding the data. We did not play the game, but it seems some of us to now step into the game as we are 'winning'. I just don't like that from 'our' team.
As this article says, "what they SHOULD have done was cohort match 2 groups by risk at one point in time and compare them across the same temporal interval counting all outcomes from the moment you got a booster in the boosted group. tellingly, no one seems to do this."
No-one on their side indeed. But we don't either. Granted we don't have access to their data, so we cannot really be blamed. But we shouldn't just either. Here kind of do it too a bit at the end, suggesting the negative efficacy is real, even though we cannot say that either due to the excellent explanation given at the start.
I'm truly interested in the results, wherever they fall. I just warn for implausible (from immunologic point of view) theories based on crappy data just because they sound good.
Just to explain where I stand: I personally expect the vax to have severe side effects, making them not worth it for pretty much any health person under roughly 50, maybe even higher. And I expect efficacy to be around maximum 25% against death for others but varying (shrinking towards zero) over time due to decreasing antibodies and changing variants. But that is obviously a rough estimate based on very global data of cases vs deaths vs vaccine uptake. So more a very ballpark guess from me to stake out the field.
I'd love to peek 10 years into the future when more of the hidden and manipulated data is made visible, politics perhaps have faded a bit, etc.
I have been wondering for a while how much "counting the vaxxed as those 14 days past the jab" is hurting the unvaxxed numbers. This article is shocking. It's grievous how much Pharma and govt agencies are withholding and twisting information.
I don't usually post but thank you El Gato Malo for writing all of your articles. You have done so much work and there are many of us who greatly appreciate it. And I like the cats pics. ;)
Anyone 12-14 days from their 2nd vax or booster w/ an adverse event or death were counted as UNvaxed, to skew unvax’d figures to “prove” the unvax’d were leading cases/ hospitalizations/ deaths when it is really the vax’d who are the leading numbers
Can't say I agree with you on the cat pics Nicole, but I really agree with you thanking Gato for all the effort he has put into producing some great information. Cheers.
This is a feline-friendly zone, Craig. Denigrate them at your peril! Fur may fly... 😉
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Whilst we endeavor to make our products toxic, we make no representations or warranties of any kind, express or implied about their efficacy and safety.
We cannot guarantee that your gene 144 won’t be deleted, your X / Y Chromosome won’t be inverted, your gene 69-70 won’t be deleted or mutated, that you may experience loss-of-function due to protein folding, that your gene E1, E3, E4 won’t be deleted, that you won’t receive shots full of magnetic graphene oxides and nano-biosensors (motherboards, transistors, routers, antennas).
We do not guarantee that you won’t be MAC Addressed as per Lord Schwab’s instructions (COVID -19 is a rare but narrow window of opportunity to rethink, reinvent, reset our world).
By using our products you agree that you automatically become legally a trans-human and therefore our property since you are GM-modified using our patented mRNAs (CERTIORARI 12–398).
Trans-humans do not enjoy any human or other rights of a state and this applies worldwide. Our patents are under US jurisdiction and law, where they were registered.
Any reliance you place on our products is therefore strictly at your own risk.
...
Fact Checker: We make sh$t!
https://librti.com/page/view-video?id=1438
lol!
Awesome
They are profit boosters with negative medical benefit.
The worst thing about
being lied to is
knowing you weren’t
worth the truth.
Well, on the other hand, we're 'worth' the effort of them trying to cover things up.
I would actually rather prefer to think the lies were to keep those of us awake & courageous from knowing & revolting. Otherwise lulling the masses w/ lullaby lies
You're right.
It's well presented in the Rockfeller Locktep 2010 report - the master plan for the ongoing scam. The plan said clearly that the virus to be released in Wuhan in 2019 will not be very dangerous and will be used only to force people to get quackcinated...The real bioweapon is not SARS-Cov-2, it's the "vaccine" designed to reduce the population. These are pre-meditated crimes.
You can find the plan below:
https://themillenniumreport.com/2020/07/rockefeller-lockstep-2010-was-blueprint-for-2020-covid-19-pandemic/
And Fauci is the one who patented the HIV inserts found in SARS-Cov-2 as specified in the plan.
BOMBSHELL: Fauci owns patent on SARS-CoV-2 gp120 HIV insertion, which destroys the body’s cancer-killing T cells
https://www.planet-today.com/2022/03/bombshell-fauci-owns-patent-on-sars-cov.html
The only logical reason for defining an "early post-booster" category of day 3-7 is to conceal the effects on their numbers of the entire post-booster period. Don't we know, for instance, that the worst adverse effects happen in the first 48 hours post vaccination? In doing so, they can dismiss analyses like yours that are forced to make assumptions based on their purposefully incomplete data. They know few are going to see your analysis let along attempt to follow your logic. Pure obfuscation at its worst.
Good work. Rigging studies is of course de rigueur and has been going on decades, which is why we are at the edge of the failure of so many systems that we’re on the verge of either a revolution or total destruction. But of course that is the story of central authority for 10k years. Hopefully we can do it peacefully. Sometimes the fraud is methodological, sometimes analytical. In my own particular line of work, it generally comes under methodology. e.g. "Let's assess the effectiveness of a fever vaccine by letting people in the trial self-dose with anti-pyretics to suppress their fever." haha
There are peer-reviewed publications since early 2020 that proved that 95% efficacy claimed by Schizer was useless. Manufacturers are using relative efficacy (~95%) instead of absolute efficacy ( < 0.7%) to fool the world. None of the transgenic jabs on the market has an absolute efficacy > 0.7% meaning that they were USELESS since day 1.
Yes, exactly. And plenty of smart people have constantly pointed out that all cause mortality was higher in the treatment group. I think there was something like a 400% increase in heart issues in the treatment group with all cause mortality being over 30% higher.
This by itself should have been disqualifying. But when the regulatory agency and big pharma are essentially the same organization you get what we have.
Yes. Ultimately the public is going to have to get smarter, and sometimes that can only happen with major crises like that give it a huge kick in the pants.
This is the kind of systemic collapse you get when the public thinks it can outsource its thinking to "regulators" and the rest of the pharma/medical/academic industrial complex.
The beatings will continue until morale improves. Until then, it's Darwin Doin Work.
What amazed me most was that MDs are getting quackcinated without asking real questions. I am not from the medical field background but I had gathered all scientific evidence that proved clearly to me that these were fakes before December 2020 EUA and I've since posted hundreds of messages on the internet about the ongoing global scam.
How do you fix a system where those who are supposed to lead are quacks?
You are 100% correct. It doesn't surprise me at all, though. Perhaps 1 in 20 doctors can think properly. Most are idiots. It's one of the most brainwashed professions on earth. Nurses refuse in high percentages, I'd bet, because they see real world evidence. The American Medical Association is a sort of a cult, really. If you want to read really good medical writing, go for instance, to Colleen Huber's substack, The Defeat of COVID. She is NMD. Very few physicians (MDs) have the ability to break free from their training (brainwashing), rote textbook memorization, and techician type robot training to really think. The type of thinking done by HouseMD just isn't really done by most doctors. It's a nice mythology.
This is, in my not so humble opinion, one way to fix a system run by quacks. (Hopefully the complete collapse of the system and emergence of decentralized solutions will help to accomplish it):
https://www.lewrockwell.com/1970/01/hans-hermann-hoppe/a-four-step-health-care-solution/
I got a very similar opinion from Dr TenPenny. For her, the only way out of this mess is to scrap the whole system and start from scratch. Rockfeller Foundation turned medical schools in the US into Madrassas.
I also got the same feeling from a British musician who complains that when he visits a doctor he spends 95% of the time watching his computer screen instead of asking him questions. What's the point of visiting a doctor who cannot even observe you physically to see if external signs of health issues can be detected?
i just think back to people I knew in high school who i thought were idiots and at a reunion years later i found out where now doctors. i simply thought, "really?!?!" they did not give me confidence in the medical profession.
Are they really getting quackcinated? They would be some of the easiest ones to fake.
According to the Slovenian nurse who revealed the tricks behind these injections, saline is mostly used for politicians who get jabbed in public. She was fired.
I've seen pictures of many dead/disabled doctors online - one died in Eastern Canada shortly after his booster shot. One in the US was a surgeon and can no longer make use of his right hand after his injection. He used to perform 800+ surgeries per year - not anymore after Fauci convinced him that poisons were safe and effective.
short form... Trump tweet... "RIGGED!"
gato, you're wonderful, but I think there is a big mistake here.
Let:
a = number of infections in booster group
b = number of person-days in booster group
c = number of infections in early postbooster group
d = number of person-days in early postbooster group
I think to properly combine the risks from the "early postbooster" and "boosted" groups, you need to do (a + c) / (b + d), whereas what you've done is a / b + c / d.
As a toy example to demonstrate this, imagine the booster were just a placebo, and neither increased nor decreased your chance of being infected. Then the rate of infection in each of the three groups (unboosted, early postbooster, booster) would be exactly the same number. Let's say, 30,000 infections per 100,000 population per year. (This is because the paper divides by the number of person-days at risk instead of merely the population.)
I think what you're doing is tantamount to combining the 30,000 infections per 100k per year from the boosted group and the 30,000 infections per 100k per year from the early postbooster group and concluding that the booster doubles your infection rate per year to 60,000 per 100k, when in reality it merely did nothing at all.
I was thinking something similar - is it appropriate to pro-rata the 5 day early booster period up to 12 days (2.4x increase) if it's already represented as a rate per 100k per year? As a very rough assumption we could expect 2.4x the number of infections during a period 2.4x as long, so the math of infections / person years would come out the same when looking at just that group instead of 2.4x larger.
I think the solution is similar to your method (if you were to choose to pro-rata it at all):
(booster infections + early booster infections x 2.4) / (booster person-years + early booster person years x 2.4)
edit: by my math, this puts it in the 70-75% effectiveness ballpark, which is still higher than any other source I've seen on effectiveness against infection (particularly when it's meant to be a comparison to people with 2 doses, not unvaccinated)
You're correct, the math is very wrong. To a close approximation, the early post booster rate is equivalent to 5 more days at the original double vaxed rate. Adding it in properly approximately doubles the rate of infection for the boosted category, but it's still well below double vaxed.
He's onto something about the weird keyhole they selected, that happens to be exactly the same rate as the double vaxed rate. Maybe the other days had higher levels? Who knows. Even so it's unlikely that it is so bad that it would produce negative efficacy vs. the double vaxed rate, it would need to be 10x worse.
Gato... FIX THIS PLEASE!
Working through the numbers for 60+ age group per 100k/y - whereas Gato’s approach (simply adding boost & early boost figures for 100k/y) results in combined boost figure of 17,307 (before 2.4 adjustment), the alternate approach gives a combined boost figure of 3,259 per 100k/y, before 2.4 adjustment. That’s a big difference- 17,307 versus 3,259- and I’d like to know which is correct.
Gato's method is not correct.
The calculation of risk for each separate category (boosted and early-pre-booster) is correct. That is, it tells you your risk per 100k person-years for time spent in that category. To use that kind of metric to assess your own risk, you would multiply it by the amount of time (in years) you're in that category. For example, Risk/p/y * 1 year would tell you your risk, being in that category for 1 year (in units of per-100k). Does that make sense?
But here's the problem: you can't just add these risk numbers to get an aggregate. The reason is that the amount of time spent in each category must be taken into account. If you spend 1 week in prebooster and 51 weeks in boosted, then the aggregate needs to be (Rp * 1 + Rb * 51) / 52, in order to correctly account for the fraction of time spent in each risk category (where Rp and Rb are the risk values).
In this case, the original data included the amount of person-years the cohort spent in each category, so its easy to aggregate correctly by summing the event counts, and dividing by the total person-years. This would give you an aggregate risk for the population, having spent some time in preboosted and a lot more time in boosted.
Here's a simple example to explain:
Suppose we have data over 10 days. The events occur as follows, starting from day 1, the event counts observed are: 2,0,1,1,1,1,1,1,1,1,1.
That is, 2 events on day 1, none on day 2, and 1 on each of day 3-10.
The correct way to compute the rate here is total events / total days: 10 events over 10 days = 1 event per day on average.
But we want to compare early and late rates because they are different: so now we calculate the rate on the first day, and the rate on the following 9 days separately.
The first day has 2 events on 1 day, so 2/1 = 2 events per day.
The following 9 days have 8 events over 9 days, so 8/9 = 0.88 events per day on average.
Thus we see two different rates, 2 vs. 0.88. This correctly expresses a higher rate of events at the start of the dataset.
But if we now try to create an aggregate by just adding those rates we get 2 + 0.88 = 2.88 events per day as the aggregate rate. But we know from the start that the real aggregate rate is 1/day - and 2.88/day is clearly wrong because if we multiplied that out by 10 days we would get 28.8 events over the 10 days, not 10.
The correct way to combine the rates we would need to weight them by the amount of time in each:
(2*1 + 0.88*9)/10 = (2+8)/10 = 10/10 = 1.
There we got the correct answer back again.
Or, ignore the rates and use our original formula of dividing total events by total time:
10 events / 10 days = 1 event/day
Thank you, that is very clear. I’ve been tossing this around in my mind, every time Gato posts I think it’s going to be about correcting this, but it isn’t (and sadly isn’t looking like it will be at this point). As described, this is a gross mathematical error. Imagine a baseball player had an average of .300 for their first ten games and then .250 for the next 152. It would be wrong enough to say that they’re a .275 hitter, but what Gato has done is equivalent to saying they’re a .550 hitter!
Funny you say this because I kept having the same hopeful expectation. When the next post was entitled "Burnout" I thought it would be a mea culpa saying, sorry guys I'm a bit burned out and I got it wrong on the last post. But sadly, no. It's a real shame because this post has been reposted uncritically in at least a few places I have seen. Shoutout to Brian Mowrey who caught this https://unglossed.substack.com/p/norcal-pregnancy-study-etc?s=r and I *highly* recommend subscribing. He has been consistently accurate and honest, and very light on the confirmation bias.
In any case, the error in this post is egregious, no other way to put it.
Hehe, that’s exactly what I thought the “Burnout” article was going to say too!
It is unfortunate that this has already been fairly widely disseminated, as we know from the mainstream, even later corrections never carry the same weight as the initial claim. I know Gato is just a kitty and we all make mistakes… and it’s totally unfair that us questioning the narrative need to be completely accurate at all times or else we’re thrown out with the bathwater, but that’s the reality. We don’t get the same benefit given to CNN, Fauci, and the rest. Personally though, most of the reason I read these substacks IS for data breakdown and analysis, not for waxing poetic. I can form my own opinions with little effort, doing the math myself is a bit more time consuming. I’m no statistician, but I’ve done enough number crunching at various jobs that this error is so profound that it just didn’t feel right immediately, and on further review, it’s such an “entry-level” mistake that it really makes me doubt Gato’s math acumen entirely. Maybe that’s unfair, but there’s a lot of people writing out there and only so many hours in the day, so the longer this goes unaddressed, the more I think I should just check out on this substack.
Thanks for the link to Brian Mowrey! Looks good so far!
Also, the study does use "daily exposure risk" as a covariate, which means that it does account, at least indirectly, for pre-existing immunity. (Not very well, because it uses a multivariate linear model and the differential effect of pre-existing immunity probably depends on all sorts of things, but at least a little.)
I agree with your assessment that this study is questionable, but I disagree with your assessment that it actually proves boosters have negative efficacy.
Thanks for laying that out. I didn’t go and run the numbers myself but it seems like the adjustments Gato made were far too large on first read. Hopefully this is addressed.
Gato, you have a gross mathematical error in your calculations above.
Yes, the absolute number of infections in the first 12 days is probably ~2.4 times higher than the number given in the day 3-7 category. However, so is the number of person years.
As soon as you convert to the relative measure, you can no longer argue about hidden risk in the early booster group.
2,500 infections in 5 million person days lead to the same rate as 6,000 infections in 12 million person days. The rate stays the same.
Even worse, you seem to have applied the correction factor of ~2.4 to the sum of the relative risk (boosted + early boosted). So not only are you correcting an already corrected (relative) number, you are even correcting the part of that number that doesn't need correction - the boosted group.
As much as I agree with you on the point of data manipulation by definition of vaxxed/boosted, this post is simply teeming with errors and I'm afraid the majority of your readers will lack the mathematical/statistical prowess to realise it.
Agree with your first point but not the second- when I first looked at Gato’s table last night I thought, like you, that the 2.4 adjustment had been applied to both groups, but in the lines I checked it was applied to early boosted group only, with boosted group then added on.
Hate to be bearer of bad news but the initial analyses is flawed. You cannot add the per 100k/yr data in this way. When you divided the infections by person years the data was already normalized for time. Changing from 5 days to 12 days adjusts both denominator and numerator by the same factor which divides out. Instead what should been done is to multiple the infections and the days at risk by the 12/5 factor. Then add these amounts to the booster days at risk and infections. Then calculated the adjusted infections for 100k/yr from these totals. Unfortunately everything that follows from these calculations is flawed. Sorry gato.
Can someone respond to this? It sounds like this commenter has debunked Gatos analysis... No response?
Jalawaco is absolutely correct. Gato is adding rates that have different denominators. If you look at the raw rate in Gato's table for the early prebooster category, the rate is slightly smaller than the rate for double vaxed. In other words, being prebooster for 5 days is pretty much the same as just being double vaxed for 5 more days. This has a negligible effect on the outcome - it's like delaying the booster 5 days. But adding the rates like he did causes a very wrong answer.
It's definitely fishy that they selected those 5 days - but to cause negative efficacy you would need to have 10x the rate of infection in those extra days, which is probably unlikely. I'm sure it's bad, but honestly probably not that bad.
I hope Gato retracts this, it's not helpful.
It's disgusting how our health 'leaders' are willing to go along with Pfizer & Company's definitions.
It Takes a Village of Bureaucrats to Implement Medical Despotism
AMA = American Mafia Association
CDC = Center for Death and Corruption
FDA = Fraud and Death Association
HHS = Holistic Humanicide Services
MD = Moral Deficiency
NIH = Nihilism In Healthcare
It takes Pharmaceutical Predators to Corrupt the Bureaucrats
Schizer
https://librti.com/page/view-video?id=1438
Murderna
https://librti.com/page/view-video?id=1515
Joke & Joke
CastraZenca
It takes Corrupt Political Clowns (5 eyes) to Sing the Predators’ Mantra
Castrudeau
https://trudeauknows.ca/
Safe and Effective…
Brandon
Safe and Effective…
Buffoon Boris
Safe and Effective…
Liar from the Shire
Safe and Effective…
CovidArdern
Safe and Effective…
All clowns being dual citizens of Billgatestan with Diplomatic Immunity.
It Takes a Compliant Mediatic Clergy to Coordinate the Mass Formation Psychosis Assault for Fun and Profits – Masquerading Bioweapons as Vaccines
National
BBC = British Pravda - British Broadcast Castration
CBC = Canadian Pravda - Crown Broadcast Castration
CNN = American Pravda - Center for National Nullity
Fakebook = American Pravda - Fake Fact Checkers
Google Search = American Pravda - Search Torpedoes
NYT = American Pravda - New York Trancers
Twitter = American Pravda - Censorhip Birds
WaPo = American Pravda - Washington Popcat
Youtube = American Pravda – Your Censorhip Promised Land
Global
Agence France Presse – Globalistan Pravda
Associated Press – Globalistan Pravda
Reuters - Globalistan Pravda – Fake Fact Checkers
50% of the FDA budget comes from pharmaceutical companies. Many people in the CDC, NIAID, NIH get royalties from pharma products that are rubber stamped for the plebs.
Back during the OxyContin disaster Perdue was funding the AMA, I think at least half of the AMA budget came from Perdue. You buy the regulators and there are no “regulators”.
If only it were limited to this situation and Pfizer but Enron accounting and definition loopholes are where lobbyists secure their bespoke Turnbull & Asser style!
Very good. I wrote a little thought experiment how the way we judge the vaccines would indeed show objectively crappy vaccines to be effective. The whole thing is a giant con.
https://raggedlines.substack.com/p/crappy-vaccines-a-thought-experiment
Actually, you even went so far as accepting their proposition that a bioweapon was a "vaccine" to be tested for efficacy.
After reading the plan elaborated by Rockfeller Foundation in 2010, I understood in late 2020 that SARS-Cov-2 released in Wuhan was just a bait and that the real bioweapon was going to be sold to the public as "vaccines". SARS-Cov-2 has been shown to have HIV inserts as specified in the 2010 plan and the HIV inserts were patented by Fauci himself.
The entire plan was detailed in the lockstep 2010 report below:
https://themillenniumreport.com/2020/07/rockefeller-lockstep-2010-was-blueprint-for-2020-covid-19-pandemic/
BOMBSHELL: Fauci owns patent on SARS-CoV-2 gp120 HIV insertion, which destroys the body’s cancer-killing T cells.
https://www.planet-today.com/2022/03/bombshell-fauci-owns-patent-on-sars-cov.html
Several comments below claim that Gato made serious errors in this article. I think he owes us a response.
Indeed he did make an error, but I guess he's not reading the comments on this one?
Especially for readers like me who are not proficient in statistical analysis..It certainly would help if I can see EGM’s response
You know who bought the story? Rafael Nadal.
You know who was wise enough not to? Novak Djokovic
You know who just got blown out of a match and complained of it feeling like "Needles" in his chest with every breath? Rafael Nadal, the same Rafael Nadal who said:
"He made his own decisions, and everybody is free to take their own decisions, but then there are some consequences,"
"From my point of view, that's the only thing that I can say is I believe in what the people who know about medicine say, and if the people say that we need to get vaccinated, we need to get the vaccine."
Yes indeed, Rafael. There are consequences.
Nadal’s cogent analysis makes sense to me - don’t bother with facts ; just do whatever “ the people “ say to do.
Apparently, the strength of some champions is to not be encumbered by stray thoughts.
We know these are not really "vaccines." Instead of using the words "unvaccinated" or "boosted" or "fully vaccinated," from now on I will substitute variations on the word "poisoned."
I.e., "no, thankfully I have not been poisoned and I will do my utmost to avoid doing so."
"You are saying that you only feel safe when you are surrounded by other poisoned people such as yourself, and you are afraid of being around my high level of health?"
"You have received two doses of poison, in other words you are apparently fully poisoned."
"Perhaps you would like to be boosted with some more of the same poison you had previously, since you are not satisfied yet with the cumulative damage already done?"
"You are not 'up to date' on the level of poison in your system. Better keep it topped off and levels high for maximum damage."
Many of us are concerned with toxins in our environment, or that of our children. We try to eat organic, whole foods and avoid junk food. We use safe and natural cleaning products. This is like the junk food of medicine. It's fake, it is full of chemicals, you don't know exactly what it's doing to you, but it can't be anything good. All of your friends are taking it and you don't want to feel left out; you'd rather be a part of the cool kid group, even if they are a bunch of crackheads. You might be addicted to it, but you would be better off if you quit and find some better influences.
Just use the word quackcinated to please monster Fauci.
the Mafia are not going to like this cat, i seem to recall in the Sopranos they killed Pussy, don't go boating!
He lives on an island! Oy.
Me too
The cat is already out of the bag:
https://librti.com/page/view-video?id=1438
Me three.
This has been the theme throughout these studies, most of which are published in the NEJM (which published surgisphere and whose chief editor is the one that wanted to experiment on children with the vaccine rollout). There is an inate survival bias in this per-protocol analysis instead of using intention-to-treat, which is what should have been done. The allocation of anyone who has received the treatment but when they die or are hospitalised to be counted in the non-treatment arm is scientific fraud. It's actually easy to tell that they have misrepresented the data because the hospitalisation and death rate for the "2-dose" group in the booster paper is the same as the "unvaccinated" in the original paper. So either the vaccine didn't work or they just use the miscategorisation trick against whichever group they are comparing their wonder drug to. Great stuff
Good article, but some points of critisism, some of which you already mention:
1) Two years in, any data that doesn't take natural immunity into account is close to useless. You already state "thus got more advantage from greater pre-existing immunity". That is key. There are huge behavioural differences between vaxed, unvaxed and boosted, and as one aspect of that differences in if they 'had it'. natural immunity has been shown now definitive to be far supperiour to being vaxed and/or boosted.
2) Omiron became an upper respiratory illness, so humoral vaccines by definition do nothing. So any large difference in infections make me suspicious in general. It shows me that the data cohorts are not equal. An virus that can replicate in the throat outside reach of anything good or bad in the humoral parts of the body, shouldn't affect infection. Outcome yes, not infection. So either we have hit a revolutionary bad mechanism, or we are looking at exceptionally bad data. I know the first one is a popular topic on skeptic websites, but my money is on the first. Especially since the poor data, as explained in the first part of the article. Cohorts are not euql and not even stable unequal.
E.g. Two examples of where behaviour issues also play a role.
First, many of the boosted crowd have been the ones that also worked from home, hunkered down, avoided groups, etc. Now the restrictions are being lifted they are all getting infected in massive numbers. If you were unvaxed, your probably also the personality that didn't avoid large crowds, etc in the first place. That matters in terms of natural immunity.
Also for elderly who live in nursing homes they are all (forced/encouraged) vaxed, but if one of them or one of the caregiver gets omicron, the entire nursing home gets it. So hence you get huge waves. The living at home (more likely to be unvaxed or just double double vaxed) will benefit from these statistics.
And last, testing behaviour is non-symmetrical. Neurotic boosted are far more likely to get tested. So do people in nursing homes. Various studies showed a strong causality (which inherently is not just correlation) between testing quantity and testing positive quantity. So the testing rate must be equal to not get inherent higher infection quantity. In reverse if the testing rates are hence not equal between cohorts, you get different infection rates outcome.
If the test mechanism is crap (and it is), then all test results are crap.
More importantly, this retreat to 'cohorts not equal' is a game that can be played by both sides of the issue, forever. There's always some previously unknown factor that any shyster can throw into the apple cart in an attempt to upset it. Since you're not doing your own side (whatever that is) any good with this approach, then my question is, why use it?
Yes, it can be played by both sides. That is my point - don't play that game. The CDC and other governments played it until the results did not favor them. Now they start hiding the data. We did not play the game, but it seems some of us to now step into the game as we are 'winning'. I just don't like that from 'our' team.
As this article says, "what they SHOULD have done was cohort match 2 groups by risk at one point in time and compare them across the same temporal interval counting all outcomes from the moment you got a booster in the boosted group. tellingly, no one seems to do this."
No-one on their side indeed. But we don't either. Granted we don't have access to their data, so we cannot really be blamed. But we shouldn't just either. Here kind of do it too a bit at the end, suggesting the negative efficacy is real, even though we cannot say that either due to the excellent explanation given at the start.
I'm truly interested in the results, wherever they fall. I just warn for implausible (from immunologic point of view) theories based on crappy data just because they sound good.
Just to explain where I stand: I personally expect the vax to have severe side effects, making them not worth it for pretty much any health person under roughly 50, maybe even higher. And I expect efficacy to be around maximum 25% against death for others but varying (shrinking towards zero) over time due to decreasing antibodies and changing variants. But that is obviously a rough estimate based on very global data of cases vs deaths vs vaccine uptake. So more a very ballpark guess from me to stake out the field.
I'd love to peek 10 years into the future when more of the hidden and manipulated data is made visible, politics perhaps have faded a bit, etc.