Official data suggests certain batches of Covid-19 Vaccine were intentionally poisoned as just 5% of batches are responsible for 100% of Vaccine Deaths [Denninger stat analysis]

theexpose.uk ^ | NOVEMBER 3, 2021 | The Expose, Karl Denninger

[ransomnote]

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There is an article floating around from The Expose that makes an explosive claim: There is a wildly statistically-significant skew in the death rate from Covid-19 vaccines by lot number.

What originally got my attention was the tinfoil hat crowd screaming about lots being intentionally distributed to certain people to kill them — in other words certain Covid-19 vaccine lots were for all intents and purposes poisoned.  That was wildly unlikely so I set out to disprove it and apply some broom handles to the tinfoil hatters heads.  What I found, however, was both interesting and deeply disturbing.

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By Karl Denninger

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Lots are quite large, especially when you’re dealing with 200 million people and 400 million doses.  Assuming the lots are not preferentially assigned to certain cohorts (e.g. one goes to all nursing homes, etc) adverse reactions should thus be normally distributed between lots; if they’re not one of these things is almost-certainly true:

• There is a serious manufacturing quality problem or you produced something without understanding how it would work in the body and thus failed to control for something you had to in order to wind up with reproduceable results.  That is, some lots are ok, others are contaminated, have too much or too little of the active ingredient in them, some produce wildly more spike-protein than others in the body when injected, etc.
  
  OR
• Much worse, the lots are intentionally segregated to produce different results. This implies some sort of nefarious intent such as killing people on a differential basis or that the manufacturers are running unsanctioned experiments on a mass basis among the population at-large, since they know what is in each lot and intentionally varied the contents.
  
  OR
• Perhaps worst of all, reports are now being intentionally suppressed, the injury and death rate hasn’t changed and there are lots with one of the two above problems but it is being intentionally not reported, having been detected almost-instantly and health providers were directed to not report anything serious (e.g. death) associated with the jabs.

Now let’s talk about VAERS.  You can grab the public data from it, but VAERS intentionally makes it difficult to discern differences in lot outcomes.  Why?  Because they separate out the specifics of the vax (the manufacturer, lot number, etc.) into a different file.  This means that simply loading it into Excel does you no good and attempting to correlate and match the two tables in Excel itself is problematic due to the extreme size of the files — in fact, it blew Excel up here when I tried to do it.  But that’s an external data-export problem; internally, within HHS, it is certainly not hard for them to run correlations.

Indeed the entire point of VAERS is to find said correlations before people get screwed in size and stop it from happening.

Let’s step back a bit in history. VAERS came into being because back in the 1970s the producers of the DTP shot had a quality control problem.  Some lots had way too much active ingredient in them and others had nearly none.  This caused a crap ton of bad reactions by kids who got the jabs and parents sued.  Liability insurance threatened to become unobtanium (gee, you figure, after you screw a bunch of kids who had to take mandatory shots?) and thus the manufacturers pulled the DTP jab and threatened to pull all vaccines from the market.

Congress responded to this threat of intentional panic sown by the pharmaceutical industry by giving the vaccine firms immunity and setting up a tax and arbitration system, basically, to pay families if they got screwed by vaccines.  Rather than force the guilty parties to eat the injuries and deaths they caused Congress instead exempted the manufacturers from the consequences of their own negligence and socialized the losses with a small tax on each shot.

Part of this was VAERS.  We know VAERS understates adverse events because it while it is allegedly “mandatory” it is subject to clinical judgment and there is a wild bias against believing that these jabs, or any jab for that matter, has bad side effects.  In addition there is neither a civil or criminal penalty of any kind for failure to report.  We now know some people who have had bad side effects from the Covid-19 jabs have shown up on social media after going to the doctor and then tried to find their own record, which is quite easy to do if you know the lot number from your card, what happened and the date the event happened — their doctor never filed it.  This does not really surprise me since filing those reports takes quite a bit of time and the doctor isn’t paid for it by the government or anyone else, so even without bias there will be those who simply won’t do the work unless there are severe penalties for not doing so.  There are in fact no penalties whatsoever.  The under-reporting does not have a reliable boundary on it, but estimates are that only somewhere between 3% and 10% of actual adverse events get into the database.  That’s right — at best the adverse event rate is ten times that of what you find in VAERS.

But now it gets interesting because VAERS exports, it appears, were also set up, whether deliberately or by coincidink, to make it hard for ordinary people to find a future correlation between injury or death and vaccine lot number.

NOTE THAT THIS EXACT CIRCUMSTANCE — THAT MANUFACTURERS HAD QUALITY CONTROL PROBLEMS ORIGINALLY — IS WHY VAERS EXISTS.  YOU WOULD THINK THAT IF CONGRESS WAS ACTUALLY INTERESTED IN SOLVING THE PROBLEM THIS WOULD BE THE EASIEST SORT OF THING TO MONITOR AND WOULD BE REGULARLY REPORTED.  YOU’D ALSO THINK THERE WERE STRONG CIVIL AND EVEN CRIMINAL PENALTIES FOR NOT REPORTING ADVERSE EVENTS.

You’d be wrong; the data is across two tables and uncorrelated as VAERS releases it and there is no quick-and-easy reporting on their site that groups events on a comparative basis by lot number.  While it is possible to do this sort of analysis from their web page it’s not easy.

(Further, and this also intentionally frustrates analysis, VAERS keeps no record nor reports on the number of shots administered per lot, making norming to some stable denominator literally impossible.  If you think that’s an accident I have a bridge for sale.  It’s a very nice bridge.)

But, grasshopper, I have Postgres.  Indeed if you’re reading this article it is because I both have it and know how to program against it; this blog is, in fact, stored in Postgres.

Postgres, like all databases, is very good at taking something that can be foreign-key related and correlating it.  In fact that’s one of a database’s prime strengths.  Isn’t SQL, which I assume VAERS uses as well, wonderful?

So I did exactly that with the data found here for 2021.

And….. you aren’t going to like it.

Having loaded the base table and manufacturer tables related by the VAERS-ID I ran this query:

karl=> select vax_lot(vaers_vax), count(vax_lot(vaers_vax)) from vaers, vaers_vax where vaers_id(vaers) = vaers_id(vaers_vax) and died=’Y’ and vax_type=’COVID19′ and vax_manu(vaers_vax)=’MODERNA’ group by vax_lot(vaers_vax) order by count(vax_lot(vaers_vax)) desc;

This says:

Select the lot, and count the instances of that lot, from the VAERS data where the report ID is in the table of persons who had a bad reaction, said bad reaction was that they died, where the vaccine is a Covid-19 vaccine and where the manufacturer is MODERNA.  Order the results by the count of the deaths per lot in descending order.

vax_lot | count
-----------------+-------
039K20A | 87
013L20A | 66
012L20A | 64
010M20A | 62
037K20A | 49
029L20A | 48
012M20A | 46
024M20A | 44
027L20A | 44
015M20A | 43
025L20A | 42
026A21A | 41
013M20A | 41
016M20A | 41
022M20A | 41
030L20A | 40
026L20A | 39
007M20A | 39
013A21A | 36
011A21A | 36
031M20A | 35
032L20A | 35
010A21A | 33
011J20A | 33
030A21A | 33
028L20A | 32
011L20A | 32
004M20A | 32
025J20-2A | 31 << — What’s this? (see below)
041L20A | 31
011M20A | 31
031L20A | 30
032H20A | 29
030M20A | 28
042L20A | 27
Unknown | 27
006M20A | 27
012A21A | 25
002A21A | 25
043L20A | 24
032M20A | 24
023M20A | 23
040A21A | 23
027A21A | 23
017B21A | 22
036A21A | 20
unknown | 19
020B21A | 19
047A21A | 19
006B21A | 18
044A21A | 17
038K20A | 17
048A21A | 15
003A21A | 15
014M20A | 15
031A21A | 15
031B21A | 15
021B21A | 15
025A21A | 14
007B21A | 14
003B21A | 14
001A21A | 13
038A21A | 13
025B21A | 13
001B21A | 12
046A21A | 12
027B21A | 11
045A21A | 11
038B21A | 11
025J20A | 11
002C21A | 11
016B21A | 11
036B21A | 11
039B21A | 10
002B21A | 10
018B21A | 10
019B21A | 10
008B21A | 10
029K20A | 10
029A21A | 10
028A21A | 9
047B21A | 9
001C21A | 9
044B21A | 8
045B21A | 8
009C21A | 8
048B21A | 8
026B21A | 8
UNKNOWN | 7
039A21A | 7
040B21A | 7
046B21A | 7
032B21A | 7
038C21A | 6
030m20a | 6
027C21A | 6
008C21A | 6
006C21A | 6
004C21A | 6
047C21A | 6
007C21A | 5
025C21A | 5
042B21A | 5
043B21A | 5
025J202A | 5  << — Same as the above one?
052E21A | 5
003C21A | 5
030B21A | 5
030a21a | 5
016C21A | 5
017C21A | 5
N/A | 5
NO LOT # AVAILA | 5
037A21B | 5
037B21A | 5
024m20a | 4
031l20a | 4
003b21a | 4
026a21a | 4
041B21A | 4
005C21A | 4
033C21A | 4
035C21A | 4
021C21A | 4
040a21a | 4
041C21A | 4
006D21A | 4
022C21A | 4
037k20a | 4
048C21A | 4
03M20A | 3
008B212A | 3
039k20a | 3
024C21A | 3
016m20a | 3
038k20a | 3
025b21a | 3
033B21A | 3
026C21A | 3
Moderna | 3
033c21a | 3
014C21A | 3
…..

There are 547 unique lot entries that have one or more deaths associated with them.  Some of the lot numbers are in the wrong format or missing, as you can also see.  That’s not unusual and in fact implicates the ordinary failure to get things right when people fill out the input.  For example “Moderna” in the above results is clearly not a lot number.  I’ve made no attempt to “sanitize” the data set in this regard and, quite-clearly, neither has VAERS even months after the fact with their “alleged” follow-up on reports.

But there is a wild over-representation in deaths of just a few lots; in fact fewer than 50 lots account for all lots where more than 20 associated deaths accumulated and out of the 547 unique entries fewer than 100 account for all those with more than 10 deaths.

Normal distribution my ass.

How about Pfizer?

vax_lot | count
-----------------+-------
EN6201 | 117
EN5318 | 99
EN6200 | 97
EN6198 | 89
EL3248 | 86
EL9261 | 84
EM9810 | 82
EN6202 | 75
EL9269 | 75
EL3302 | 69
EL3249 | 67
EL8982 | 67
EN6208 | 59
EL9267 | 58
EL9264 | 57
EL0140 | 54
EN6199 | 54
EJ1686 | 51
EL9265 | 50
EL1283 | 48
ER2613 | 48
EN6204 | 47
EN6205 | 45
EK9231 | 43
EL3246 | 43
EN6207 | 41
EN6203 | 41
ER8732 | 40
EL1284 | 39
EL0142 | 38
EJ1685 | 38
ER8737 | 37
EN9581 | 36
EN6206 | 35
EP7533 | 35
EL9262 | 34
EL9266 | 33
EL3247 | 32
ER8727 | 28
EP6955 | 27
ER8730 | 26
EW0150 | 25
EK5730 | 24
EP7534 | 24
EM9809 | 22
EK4176 | 22
EH9899 | 21
EW0171 | 21
unknown | 20
ER8731 | 19
ER8735 | 18
EW0172 | 18
EL9263 | 17
EW0151 | 15
ER8733 | 15
EW0158 | 14
EW0164 | 14
EW0162 | 14
EW0169 | 14
ER8729 | 13
ER8734 | 13
Unknown | 13
EW0153 | 13
EW0167 | 12
EW0168 | 10
EW0161 | 10
EW0182 | 9
NO LOT # AVAILA | 8
EW0181 | 8
EW0186 | 8
ER8736 | 8
EW0191 | 8
FF2589 | 7
EW0173 | 6
EW0175 | 6
FA7485 | 6
EW0177 | 6
FD0809 | 6
301308A | 6
EW0170 | 6
FC3182 | 6
EW0217 | 6
EK41765 | 5
EW0196 | 5
EW0176 | 5
EW0183 | 4
EN 5318 | 4
el3249 | 4
EW0178 | 4
EW0179 | 4
EW0187 | 4
FA6780 | 4
FA7484 | 4
EN 6207 | 4

Pfizer has 395 unique lot numbers associated with at least one death and, again, there are a few that are obviously bogus.  But again, normal distribution my ass; there is a wild over-representation with one lot, EN6201, being associated with 117 deaths and fewer than 20 are associated with more than 50.

For grins and giggles let’s look at the age distribution for 039K20A — the worst Moderna lot.

karl=> select avg(age_yrs) from vaers, vaers_vax where vaers_id(vaers) = vaers_id(vaers_vax) and vax_type=’COVID19′ and vax_manu(vaers_vax)=’MODERNA’ and vax_lot(vaers_vax)=’039K20A’ and age_yrs is not null;
      avg
———————
 51.4922202119410700
(1 row)

Ok, so the average age of people who got that shot, had a bad reaction (and had a valid age in the table) is 51.

How about for 030A21A which had 33 deaths?

karl=> select avg(age_yrs) from vaers, vaers_vax where vaers_id(vaers) = vaers_id(vaers_vax) and vax_type=’COVID19′ and vax_manu(vaers_vax)=’MODERNA’ and vax_lot(vaers_vax)=’030A21A’ and age_yrs is not null;

       avg
———————
 61.1097014925373134
(1 row)

Well there goes the argument that we jabbed all the old people in nursing homes with the really nasty outcome lot and they died but it not caused by the jab and the second lot, which had a much lower rate, all went into younger people’s arms and that’s why they didn’t die.  Uh, no, actually when it comes to the age of the people who got jabbed in these two instances its the other way around; the second lot, which was less deadly, had bad reactions in older people on average yet fewer died — and significantly so too (by 10 years.)

In addition there is no solid correlation between the “bad” lots and first report of trouble.  The absolute worst of Moderna had a bad report in the first days of January.  But — another lot of their vaccine with only 172 reports against it (1/20th the rate of the worst for total adverse events) had its first adverse event report on January 6th.

What is normally-distributed?  When people died.

What the actual **** is going on here?  You’re going to try to tell me that the CDC, NIH and FDA don’t know about this?  I can suck this data into a database, run 30 seconds of queries against it and instantly identify a wildly-elevated death and hazard rate associated with certain lot numbers when the distribution of those associations should be normal, or at least something close to it, across all the lots produced and used?  Then I look to try to find the obvious potential “clean” explanation (the higher death rate lot could have gone into older people) and it’s simply not there when one looks at all adverse event reports.  I have Moderna lots with the same average age of persons who died but ten times times the number of associated deaths.

Then I look at reported date of death and…. its reasonably close to a normal distribution.  So no, it wasn’t all those old people getting killed at once in the first month.  So much for that attempted explanation.

Oh if you’re interested the nastiest lot was literally everywhere in terms of states reporting adverse events against it; no, they didn’t concentrate them in one state or region either.

The outcome distribution isn’t “sort of close” when most of the lots have a single-digit number of associated deaths.

Isn’t it also interesting that when one removes the “dead” flag the same sort of correlation shows up?  That is, there are plenty of lots with nearly nothing reported against them.  For Moderna within the first page of results (~85 lots) there is more than a three times difference in total adverse events.  The worst lot, 039K20A with 87 deaths, is not only worst for deaths; it also has more than 4,000 total adverse event reports against it.  For context if you drill down a couple hundred entries in that report the number of total adverse events against another lot, 025C21A number 417 with five deaths.

Are you really going to try to tell me that a mass-produced and distributed jab has a roughly ten times adverse event rate between two lots and seventeen times the death rate between the same two, you can’t explain it by “older people getting one lot and not the other” and this is not a screaming indication that something that cannot be explained as random chance has occurred?

Here, in pictures, since some of you need to be hit upside the head with a ****ing railroad tie before you wake up:

That’s Pfizer deaths by lot, worst-to-best.  Look normal to you?  Remember, zero deaths in a given lot doesn’t come up since it’s not in the system.

How about adverse events of all sorts?

(Yes, there are invalid lot numbers, particularly in the second graph, with lots of “1s”.  The left side however is what it is.)

There’s a much-larger problem.  Have a look at Moderna’s chart of the same thing.  First, deaths:

And AE’s….

These are different companies!

Want even worse news?

JANSSEN, which is an entirely different technology, has the same curve.

and

What do we have here folks?

Is there something inherent in the production of the “instructions”, however they’re delivered, that results in a non-deterministic outcome within a batch of jabs which was not controlled for, perhaps because it isn’t understood SINCE WE HAVE NEVER DONE THIS BEFORE IN MAN OR BEAST and if it goes wrong you’re ****ed?

This is a power-law (exponential) distribution; it is not a step-function nor normally distributed.  Those don’t happen with allegedly consistent manufacturing processes and the potential confounding factor that could be an innocent explanation (all the bad ones were early and killed all the old people early who died of “something” but it wasn’t the vaccines since they all got the jab first) has been invalidated because the dates of death are in fact reasonably distributed.

Have doctors been told to stop reporting?  Note that HHS can issue such an order under the PREP Act and there is no judicial review if they do that.  Did they?

This demands an explanation.  Three different firms all using spike proteins, two using a different technology than the third, all three causing the body to produce the spike rather than deliver it directly and all three of them have a wild skew of some lots that hose people left and right while the others, statistically, do not screw people.

This data also eliminates the hypothesis put forward that lack of aspiration technique is responsible — that is, that occasional accidental penetration of a vein results in systemic distribution.  That would not be lot-specific.

Next question, which VAERS cannot answer: Is there an effectiveness difference between the lots that screw people and those that do not?

Are we done being stupid yet?  Statistically all of the adverse events of any sort are in a handful of lots irrespective of the brand.  The rest generate a few bad outcomes while a very, very small number of lots generate a huge percentage of the harm.  And no, that’s not tied to age bracketing (therefore who got it first either); some of the worst have average age distributions that are less than lots with lower adverse event rates.  It is also not tied to when used either since one of the “better” lots has a first-AE report right at the start of January — as do the “bad” lots.

The only thing all three of these vaccines have in common is that all three of them rely on the human body to produce the spike protein that is then attacked by the immune system and produces antibodies; none of them directly introduce the offending substance into the body.  The mechanism of induction is different between the J&J and Pfizer/Moderna formulations but all exhibit the same problem.  The differential shown in the data is wildly beyond reasonable explanation related to the cohort dosed and the reported person’s average age for the full set of events (not just deaths) does not correlate with elevated risk in a given lot either so it is clearly not related to the age of the person jabbed (e.g. “certain lots all went to nursing homes since they were first.”)  While the highest AE rate lots all have early use dates so do some of the low-AE rate lots so the attempt to explain the data away as “but the highest risk got it first” fails as well.

In other words the best-fit hypothesis is that causing the body to produce part of a pathogen when that part has pathological capacity (as we know is the case for the spike) cannot be controlled adequately through commercial manufacturing process at-scale.  This means that no vector-based, irrespective of how (e.g. viral vector or mRNA), not-directly-infused coronavirusjab will ever have an acceptable safety profile because some lots will be “hot” and harm crazy percentages of those they’re given to with no way to know in advance.  The basic premise used here — to have the body produce the agent the immune system identifies rather than directly introduce it where you can control the quantity, is a failure. 

The entire premise of calling something that does this a “vaccine” is bogus and in the context of a coronavirus this may never be able to be done safely.

Something is very wrong here folks and the people running VAERS either aren’t looking on purpose, know damn well its happening and are saying nothing about it on purpose — never mind segregating the data in such a fashion that casual perusal of their downloads won’t find it — or saw it immediately and suppressed reporting on purpose.

If these firms were not immune from civil and even criminal prosecution as a result of what Biden and Trump did the plaintiff’s bar would have been crawling up *******s months ago.

This ought to be rammed up every politician’s ass along with every single person at the CDC, NIH and FDA.  They know this is going on; it took me minutes to analyze and find this.

What the HELL is going on here?

THESE SHOTS MUST BE WITHDRAWN NOW until what has happened is fully explained and, if applicable, accountability is obtained for those injured or killed as a result.  If embargoing of reports is proved, and its entirely possible that is the case, everyone involved must go to prison now and the entire program must be permanently scrapped.

THERE IS NO REASONABLE EXPLANATION FOR THIS DATA THAT REDUCES TO RANDOM CHANCE.

[ransomnote]

It's intentional.

Note that Denninger mentions The Prep Act (George Bush) which allows the government to stop doctors from reporting deaths. He asks if it's in force (they don't have to tell us if it is).

Karl Denninger of Market-ticker.org has written repeatedly, waving the red flag and warning the public that 1.2 million adults are 'missing' from the job market. He's followed the stats for years and knows these people are truly missing, and not accounted for anywhere else.

I've posted his articles on the Forum but it seems only other statstics-minded people understand them, and the rest insist the data can't be true, accurate or understood.

I'll post a helpful comment from Cathi which clarifies the key point that arises when I post Denninger's articles warning us that over 1 million Americans have dropped silently out of the demographics in a relatively impossible way. I'll post an excerpt of Cathi's helpful explanatory email below, and then the link to Denninger's related article at the bottom.  Thank you, Cathi!

 

From Cathi | 10/31/2021 6:32:39 PM PDT new

......after the CDC came out with a report that they had reviewed the first 1,400 or so after vax deaths and determined that the vax was not implicated in ANY OF THEM I began to fully understand that no amount of data would ever get the government regulators to admit anything!

It apparently annoyed some independent scientific group and they investigated each of those deaths. Their conclusion was that the vax was solely responsible for approximately 30% of them and may be implicated in some other percentage (which I can’t remember...:-)

Naturally that was no surprise to any of us; but what was a HUGE surprise is that this group found that the CDC had entered COVID as the cause of death of every one of them despite that fact that most had no positive covid test.

So not only did they ignore and mislead about the cause of death of the unfortunately vaxed patients; but they had the nerve to increase the covid fatality count by categorizing ALL of them as covid deaths instead.

And I read the thread you sent and saw that someone was trying to come up with an explanation for Denninger’s high “unemployment” figures. Obviously they do not understand.

Denningers numbers were not about unemployment...they were the number of people in the non-institutional workforce population. “But that’s not the real trouble sign here. No, that’s the annual run rate of non-institutional population over the last 12 months. That is the total number of not-institutionalized people in the United States over the age of 16. The only ways to leave that count once you join it on your 16th birthday are to:

Expatriate yourself and leave the US permanently.

Go to prison (you come back on it when you get out.)

Go to a nursing home (Reminder: The median life expectancy on admission to one is six months, after which you do the next.)

DIE.

The last two are basically the same thing since most people, once they go to a nursing home and come off the rolls for that reason never go back onto them, although you certainly could.

Deciding to hide in Mom’s basement, going on disability or otherwise choosing never to work again whether by circumstance or personal decision does not remove you from this group. It does take you out of the “workforce” number (and adds you to the “not in labor force” number) but not from this figure.”

~~~~~~Related article by Karl Denninger

Hiring Manager: 'I Can't Find Employees!' in [Market-Ticker] 

[AmericanInTokyo]

zzzzzzzz

[ransomnote]

“Houston, we have a problem.”

In the article, Karl Denninger crunches the numbers and proves that the 5% of batches responsible for 100% of deaths can’t be coincidental or otherwise explained away.

Post #1 on the thread includes Cathi’s explanation (from a prior email) of Denninger’s other article(s) in which he has been trying to alert the public that 1.2 million people are ‘missing’ from U.S. demographics, and I included a link to his article.

[patriot torch]

It’s a game of Russian roulette!

[kiryandil]

after the CDC came out with a report that they had reviewed the first 1,400 or so after vax deaths and determined that the vax was not implicated in ANY OF THEM I

Yeah, that's not statistically possible.

[kiryandil]

Any of the vaxxtrolls are welcome to sign up for Denninger's site and tell him off or prove him wrong, or both.

It's an open forum.

[Tom Tetroxide]

CV19 Injections Will Cause Massive Death – Dr. Elizabeth Eads
https://usawatchdog.com/cv19-injections-will-cause-massive-death-dr-elizabeth-eads/

By Greg Hunter’s USAWatchdog.com

Dr. Elizabeth Eads is on the front line of medicine treating patients who have been injected with the experimental CV19 so-called “vaccines.” Dr. Eads has 25 years of experience in North East Florida hospitals. Dr. Eads contends the injections (or jabs) are not vaccines. They are “bioweapons,” and the jabs are not medicine that is intended to help or cure people. Dr. Eads says, “We are seeing from the jabs all kinds of under-reported side effects. We are seeing infertility in women. We are seeing miscarriages. We are seeing myocarditis, pericarditis, pulmonary embolisms and blood clots everywhere in the body. We are seeing swollen lymph nodes and swollen testicles. Dr. Ryan Cole has reported an increase of cancers, and we are seeing that as well in the hospitals. We are seeing blood clots and strokes and hemorrhagic strokes, dementias and strokes and blood clots in young people too.”

Dr. Eads says the adverse reactions and deaths are way undercounted. Dr. Eads contends doctors are keeping quiet to keep their jobs just like Nazi Germany before WWII. Dr. Eads explains, “This is worse than Nazi camps and Dr. Mengele and his experimentation. MIT came out last week with an estimate of 500,000 deaths (because of CV19 injections). They looked at all of the reporting agencies . . . and their numbers are close to 500,000 deaths already, and we know that VAERS (Vaccine Adverse Event Reporting System) only reports one percent. . . . . We are looking at 500,000, and we are going into flu season now. These people who received the jab have no immune system left. There are going to be mass deaths this winter, and I bet we are going to reach number in the millions.”

Dr. Eads goes on to highlight how medically reckless the CV19 jabs and the mass experimental human drug trials really are. Dr. Eads says, “There are no control groups. This is completely out of control. There is no oversite. There is absolutely no FDA, no CDC, no review board oversite, nobody is following up on those that were in the study or following up on their progress, adverse reactions or antibody levels. . . . When this vaccine was rolled out, the boxes came with a completely blank package insert—completely blank. That is against all prescribing rules. Even as of this week, the package insert for ingredients is still blank. . . .This is completely out of control and completely dangerous. There is no informed consent being given. How can you give informed consent to a patient when you don’t know what’s in it? You can’t say because we don’t have any study on what the adverse effects are.”

There is much more in the 45 minute interview, including how much the hospital gets paid for getting you on a ventilator, which few survive.

Join Greg Hunter as he talks to 25 year veteran Dr. Elizabeth Eads, DO, exposing the lies that Big Pharma, CDC, FDA and NIH are telling the public. Dr. Eads will highlight the real unreported effects of the CV19 injections/jabs and how it’s all gone completely out of control in hospitals across the country.

[Rightwing Conspiratr1]

Without knowing the actual sizes of the batches, the stats are meaningless.

[DavidThomas]

No, it’s not. Roughly 200,000 million Americans have gotten the vaccine. If it were anything like Russian roulette, tens of millions of Americans, including your friends, coworkers and neighbors, would be dead. Most people who have gotten the vaccine, including your friends, coworkers and neighbors, are doing fine.

[ransomnote]

I’m interested to know how many will insist your ‘meaningless’ post outweighs Karl Denninger’s analysis and expertise. Well I mean ‘your kind’ will definitely call him a quack, but I was referring to ordinary readers.

[Pete from Shawnee Mission]

Summed up here!

"In other words the best-fit hypothesis is that causing the body to produce part of a pathogen when that part has pathological capacity (as we know is the case for the spike) cannot be controlled adequately through commercial manufacturing process at-scale. This means that no vector-based, irrespective of how (e.g. viral vector or mRNA), not-directly-infused coronavirusjab will ever have an acceptable safety profile because some lots will be “hot” and harm crazy percentages of those they’re given to with no way to know in advance.

The basic premise used here — to have the body produce the agent the immune system identifies rather than directly introduce it where you can control the quantity, is a failure.

[patriot torch]

Roughly 200,000 million Americans have gotten the vaccine. If it were anything like Russian roulette, tens of millions of Americans, including your friends, coworkers and neighbors, would be dead. Most people who have gotten the vaccine, including your friends, coworkers and neighbors, are doing fine.

---

......and we know the long term outlet because of the years of testing right? And besides, even if tens of millions drop dead tomorrow, these clot shot killers walk away with tens of millions of tax dollars, without any liability, and the eugenicists get what they want. It sounds to me like a win, win, lose.

[semimojo]

Assuming the lots are not preferentially assigned to certain cohorts (e.g. one goes to all nursing homes, etc) adverse reactions should thus be normally distributed between lots;

Absolutely brain dead. He's ignoring the most obvious fact - the lots aren't the same size. Pfizer said their lots vary from 1 to 3 million doses. His analysis only has meaning if all lots are the same size.

This isn't tricky, it's elementary math.

[Rightwing Conspiratr1]

Clearly I’m way way smarter than Karl Denninger because I had the brains to ask the “What’s the size of each of the batches?” Without knowing this all of Mr. Denninger’s graphs and statistics are meaningless.

[Sequoyah101]

I and others have been saying for weeks, if not months, if VAERS is not precise it is at least directional and the direction it points is horribly bad for these vaccines. It pointed out more than three months ago that there is a systemic problem with these vaccines.

Not every lot may be poison but nobody knows what one is or why or how to prevent it.

Vaccinations need to stop immediately and until and if this can be sorted out with answers and process to assure it never happens again in such intensity.

The drug companies have manufactured poison. Don’t take it and certainly don’t let anyone jab your children with it.

[Sequoyah101]

The odds with a pistol may be better.

[Sequoyah101]

Then you take your chances but leave others out of it and free to make their own choice.

[zipper]

If it were anything like Russian roulette, tens of millions of Americans, including your friends, coworkers and neighbors, would be dead. Most people who have gotten the vaccine, including your friends, coworkers and neighbors, are doing fine.

You shouldn’t have to be reminded that immune system damages may not manifest in disease for many years. That’s why vaccines need long-term studies.

If you are “vaccinated”, you are part of the long-term study.

[Guenevere]

Bttt

[zipper]

Thanks for posting.

I can see that there might be more deaths from a given lot if the particular lot were contaminated, such as by being stored at an excessive temperature.

But for each manufacturer to have that same problem?

At some point there are too many lopsided results and coincidences for an innocuous explanation.

Of course the fact there are so many deaths to begin with, caused by an experimental formulation forced into our arms by bureaucrats and tyrants is profoundly unjust.

And now they’re after our children, with even thinner justification.