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2021-11-02 07:40 by Karl Denninger
in Corruption , 41429 references Ignore this thread
Uh, That's Not A Conspiracy Theory
[Comments enabled]

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.

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 evenly 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.

Evenly 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, evenly 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.)

What's worse is that the "hot" lots for deaths also are "hot" for total adverse events.  If the deaths were not related to general pathology from a given lot there would be no correlation -- but there is.  Oops.

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 evenly-distributed with a reasonable bump for the original huge uptake rate?  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 reasonably-even, 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 an even 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 or evenly 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 coronavirus jab 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.

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User Info Uh, That's Not A Conspiracy Theory in forum [Market-Ticker-Nad]
Jpg
Posts: 563
Incept: 2009-03-23

MI
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You did some calculations of "average" age of those with adverse events.

Is there any meaningful difference in the result if you compute "median" age instead?
Fog
Posts: 7
Incept: 2021-09-16

Florida
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Thanks Karl, This is great info. Looks like I will be unemployed by the end of the Month. **** this Clot Shot. There is NO WAY in Hell I would get it.
And at 56 why bother looking for another job.... I'm Done!
Tonythetiger
Posts: 426
Incept: 2019-01-27

Fort Walton
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This is the ignored cost of ****ing with the body's RNA/DNA replication process.

Just because we figured out how, doesn't mean we should.

Even if it can be proved that the results were unexpected, the data is what it is and the experimentation needs to be stopped immediately, before the next generation of kids gets the same treatment.

Heads should roll. Lots of them.

smiley




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― Thomas Paine
Hilbertspace
Posts: 17
Incept: 2021-08-18

Canada
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This an interesting puzzle with insane consequences.

The only thing I can think of is that the shots degrade quickly with temperature, and that the bad lots (severe outcomes) were ones that had better cold storage during transport and administration.

I do not think the converse would be true; poor storage temperatures make them more deadly, as heat generally messes things up. How stable are these lipid nano particles and adenovirus vector vaccines?

I guess the Janssen one only needs refrigerator temperatures; so my theory does not work for that one. Could there be another mechanism for degradation of effectiveness?
Tickerguy
Posts: 178840
Incept: 2007-06-26
A True American Patriot!
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@Hilbertspace - I doubt it.

My suspicion is that since ZERO of these jabs actually contain spike, but all cause the body to make it, there is an uncontrolled element in the production of the lot that causes some of them to do so on a wildly more-prolific basis.

Thus if you draw the short straw on the lot you get you're ****ed but there is no way to know in advance because by the time the reports show up the lot has been expended.

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Dnomsed
Posts: 329
Incept: 2021-05-18

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Bravo. Awesome ticker. Good science - what a breath of fresh air.
Bluto
Posts: 671
Incept: 2021-07-10

Florida
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Don't all the adverse effects per lot need to be normalized (i.e., divided) by lot size, which I'm sure they make nearly impossible to obtain from the suppliers?

But the fact alone that some lots produce worse outcomes in younger people is a massive red flag about the dangers of these clot shots.

Also, I remember reading that Japan did testing, and pulled several lots due to "contamination". Since the US has about 3X the number of people as Japan, it would make sense for the US to have pulled about 3X the number of lots. But I don't think they have pulled any. Maybe because they simply didn't care to test? Warp speed, and all.... What a cluster.

The other really interesting thing to tie together would be number of Fauci flu cases and/or antibodies in people organized by lot number. But the gov't is not collecting that data. I wonder why?? The whole system is rotten to the core.

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Lulubell
Posts: 23
Incept: 2021-03-15

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I find this more terrifying than anything else you've written. I saw the video yesterday, I didn't watch it, I just turned away from it. But this morning I thought about it and thought maybe I should go watch that. But now I don't have to.

So when the time comes and they've rounded us all up into camps for not getting the jab and then they force it on us, I wonder which lot we will get?
Motorelay
Posts: 48
Incept: 2021-09-20

Connecticut
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Yet another nail in the coffin that we here have been givig a wide berth to for a long time now.

The bad news is that no, they won't be stopping the vax program soon, or lining up the perps for the firing squad.

The good news is that anybody who wanted the jab got one long ago, leaving only employer- coerced stragglers and dropping the vaccine uptake rate to lowest levels.

The sad news is that now the gov is targeting young kids to take up the slack. Parents need to be vigilant for their kids. They will try to jab them at school, without parental consent.
Maddmaxx
Posts: 484
Incept: 2021-05-31

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Just getting into it and noticed this typo: they caused they instead exempted. Seems you were caught between two choices but left both in.
Tickerguy
Posts: 178840
Incept: 2007-06-26
A True American Patriot!
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No, just poorly-worded. Fixed.

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Mikpaq
Posts: 611
Incept: 2009-02-26

Behind enemy lines
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Awesome Ticker.

@Tickerguy, I think your conclusion is the most likely.."since ZERO of these jabs actually contain spike, but all cause the body to make it, there is an uncontrolled element in the production of the lot that causes some of them to do so on a wildly more-prolific basis..

If it were one company you could argue quality control, but not with 3 separate companies having the same outcomes.

I also believe one could argue, incorrectly, that VAERS is now being over reported due to all of the notoriety. However if you look up recent flu vaccine deaths, 2021, it hasn't really changed at all. So that's bull**** too.

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Handyone55
Posts: 323
Incept: 2010-07-06

Ceciltucky, Maryland
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Possible tinfoil but here goes: What if you wanted a certain predictable kill rate from the shot? The only way to get solid data is to test the kill shot on a broad sample of the population and observe the results. Mixing the kill shots with placebo shots spreads the deaths out enough so most will not notice them.

Once you know the kill shot produces predictable results, roll out the mandatory boosters that the sheep must take to work, buy food, get medical care, even go outdoors. The booster will contain the percent of kill shot for the death rate desired.

If you were to release a bio weapon with a 10 percent kill rate, the sheep would trample each other getting in line for a booster
Cmoledor
Posts: 412
Incept: 2021-04-13

Akron Ohio FEMA region 5
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And here the master does the work that I would have clue on how to do. Gratitude in massive amounts Karl. Sending out to my peeps.

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Jwm_in_sb
Posts: 3827
Incept: 2009-04-16

California Desert
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Hmm, this would seem ripe foe hanging around Trumps neck which the Regime needs heading into 2022. Watch for that to happen and that would be their exit ramp foe both the vaxx itself and the mandates.
Uwe
Posts: 10085
Incept: 2009-01-03
A True American Patriot!
USA
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KD wrote..
by the time the reports show up the lot has been expended.

Given that VAERS and manufacturer immunity came about due to QC problems, I'm surprised manufacturers aren't required to retain a few sample vials from each lot produced for a period of time, say at least one year.

Do we have any idea how big these lots are? I.e. how many doses or vials there are in a lot, or how many lots have been produced? Obviously the manufacturers have this data, and I'd think the FDA does too, so it might be available via a FOIA request.

Lastly, are you aware that Pfizer has changed the formulation of the shots they will be making available to the 5-11 age group? No, not just the dosage, but the formulation of the carrier. I have details on my real computer, but not the tablet I'm using at the moment.

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"Corona Virus will come and go, but government will NEVER forget how easy it was to take control of everyone's life; to control every sporting event, classroom, restaurant table, church pew, and even whether you are allowed to leave your house.
Bzelbob
Posts: 110
Incept: 2021-09-12

Jacksonville
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@Tickerguy - Good detective work and fantastic article. (Nice SQL too.)

Was gonna make the same comment as Bluto, in that we know Japan found contamination (stainless steel particulate from manufacturing process if memory serves.)
Not sure how that would make this kind of difference...

I can't think of an explanation for this data other than what you said that somehow the reporting *instructions* changed so that they somehow changed or stopped reporting the adverse effects.
If that's true, then yeah it's a huge **** sandwich.

My money's on the fact that they DID know early on and took the decision to conceal the truth anyway because of panic.
(And why they can't admit to being wrong = maximum culpability.)

Who said it's not the crime that gets you it's the coverup?

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"Threats are illogical. And payment is usually expensive." - Sarek of Vulcan
Ring_main
Posts: 48
Incept: 2012-01-16

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I may have missed it but is there any way to estimate lot sizes? Normalizing reactions based on lot size would confirm skew. That said the number of reactions for some lots are so out of wack it would be exceptionally unlikely for a lot size to be big enough relative to the others for it to come close to evening out (20-30x or more lot size for biggest to smallest.)
Maddmaxx
Posts: 484
Incept: 2021-05-31

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@TG, yes, sorry, jumped the gun. On second read I realized my mistake. Great article!
Quantum
Posts: 294
Incept: 2021-05-18

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@Tickerguy Awesome work. Thanks for doing this.

@Tonythetiger ACIP is meeting today to consider recommendations to vaccinate 5 to 11 year olds. If they go forward at this point (which they will)...

@Bluto I expect that if they address this at all, they'll say it doesn't control for lot size and that lot size is variable. One could do some number-crunching to see what variation would be needed to put this into the realm of normal statistical variation, but unless some lots are tiny and others tens or hundreds of thousands, it would be tough. Nonetheless, a dismissive comeback is probably what they'll try (if anything).


Asimov
Posts: 131182
Incept: 2007-08-26

East Tennessee
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Quote:
there is an uncontrolled element in the production of the lot that causes some of them to do so on a wildly more-prolific basis.


This is probably the key reason MRNA vaccines were held in reserve for possible biological weapon attack where we needed a vaccine *NOW* because the weapon was killing a huge percentage of the infected.

They've known and they know now. There would be no reason to hide it if they didn't.

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Festina lente.
Capcomp
Posts: 159
Incept: 2009-09-10

Virginia
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Given the high level of automation in the manufacturing process of the jabs I just can't see how this was not intentional.

As @Bluto mentioned Japan pulled some Moderna after finding contamination. Would sure be interesting to see what lot # that was.
Snowmizuh
Posts: 1990
Incept: 2009-03-18

Alabama
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Stupid question: is the denominator of the lots numbers all roughly the same? My first thought, since you are plotting absolute counts...

Perhaps looking at distribution of (adverse event)/(lot count) by lotID would be useful.
Spanky
Posts: 148
Incept: 2011-03-22

United States
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It's a Clottery good luck everybody.
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