Love your analysis of an analysis. A couple questions:
Do we know how many vials are in a lot number and does this vary? Could it be that the toxic VLs simply had more vials produced and deployed than the less toxic VLs?
How could a manufacturer vary the “payload” or other attributes across VLs? Doesn’t the EUA have required specs?! I.e., what product was actually authorized if the mfg is allowed to alter the authorized spec?
Do we know if the VLs deployed in the US all come from the same mfg plant? The use of letters in the nomenclature suggests to me different plants. And shouldn’t the numbering/lettering be part of the EUA spec?
Thank you and these are all amazing questions. I don't have any answers. You could write to Pfizer. They would be more than willing to ignore, I mean, help you. ;) I am sure they are made at different geographic locations and as for the intentional payload variation, I don't believe in this idea. I believe that if the payload is modified from lot to lot then this is due to distribution and storage inconsistencies.
Thanks for replying. I just read another theory that the “safer” VLs may appear so because the # of VAERS reports have become suppressed over time. Who knows what to think in these crazy times! Keep up the great work!!
It’s true that all aspects of manufacturing are subject to tests & those tests will have results for which there’s an acceptable range. Under normal conditions, the manufacturers & regulators keep the former honest.
But forget normal times. Imo all institutions are dead including FDA.
There’s not a chance these products would get authorised if usual considerations applied.
A healthy 40 year old is far more likely to be injured or even killed by these “vaccines” than the virus, no question.
That ends any consideration of their use in healthy 40 year olds. Or anyone else as it turns out.
As FDA is not doing its basic job on safety, it’s not likely to tapping them on the shoulder about manufacturing consistency.
In U.K., a QP I know told me that he couldn’t do his job, because masses of product were disappearing from where they were supposed to be for periods of time (a Qualified Person checks & verifies just the sorts of things you asked).
When they reported this, the response was more or less “Don’t you know there’s a pandemic on?” (During WW2, quite a lot of irregularity occurred all over the place, presumably because corners were being cut, usually to get the job done rather than for any other reason, though of course that allowed small time crooks to exploit the chaos, and if anyone questioned why proper procedure wasn’t being followed, the usual remark was “Don’t you know there’s a war on?”)
Thanks so much for this insight. And I am not surprised to hear about the product disappearances. I wouldn't be surprised to hear much these days. There's absolutely nothing right with any of this. It's like the world of people entered a Cuckoo clock and we are all stuck inside with the incessant bird squawking 'safe and effective' 24/7. If I didn't have these analyses to keep me busy and the new and wonderful substack medium to keep me writing, I would probably lose my mind over this. It's completely bonker doodles.
I concur with Dr Yeadon. I'm retired pharma (25 years) in all aspects of drug development. Your analysis, along with the original video, proves beyond a shadow of a doubt, that there is no manufacturing control. This alone should have halted the jabs (along with so many other obvious violations of medical and manufacturing reasons).
From day 1, no animal studies meant that those who are taking the jab are the animals in this study. I have no doubt they are monitoring it all and know the issues. If they had manufacturing control, including all of the requisite stability studies for product, the AEs would be evenly distributed statistically across all lots.
There are additional factors as well such as differences in distribution of the LNP, translation of mRNA output (effective dose), post-translational modification, and release of spike among a host of other factors such as immune response differences in cohorts. This is a combination product and the complexity of this system would take years to study properly before ever being approved properly according to the FDAs own guidances. However, thanks to 'Emergency Authorizations' being abused in many countries, they are getting away with harm and murder. There is no other way to put it. I've been following your work since your first video - its invaluable analysis.
There is no other way to say this, but its one big clusterf&ck.
The FDA undertook to rigorously monitor quality control of this EUA biologic (along with an undertaking to rigorously monitor adverse events). Two “r” words that have changed their definitions during the pandemic- rare and rigorous!
The EMA approval of Pfizer included five specific obligations that were to be met by specified dates.
Have these been satisfied?
Is anyone following up?
These form part of the approval and as such, must be met or formally waived by EMA.
Also, to date 8bn doses have been administered (1.3bn vials).
This is a novel mRNA product that has never been produced for human application before, let alone on this scale.
MRNA and it’s delivery mechanism via LNP’s are novel and also notoriously fragile and complex to manufacture.
Has any one ie drug development, engineer, Pharma etc sat down and analysed if this 8bn dose volume is even remotely feasible given the technical expertise required at all levels and at every manufacturing facility; retooling of manufacturing plants; manufacturing plant capacity; supply chain ie availability of raw materials incl vials etc and every other step of the process?
This was raised by a 30-year chemical and Pharma professional recently.
I tried but was unable to attach the screenshot of his post.
Thank you for your valuable contribution, analysis and insight. 💫
Re the VAERS batch analysis:
from casual observation, EUdravigilance, WHO Vigibase, Yellow Card, DAENS (Aust) and VAERS seem consistent in the number of AE, SAE and deaths recorded on a per capita basis (Yellow Card is massively under reported as most don't know of its existence and NHS doctors appear disinterested).
Plus the recently released Pfizer 90-day post authorisation data of 42,086 case reports containing 158,893 events incl. 1,223 deaths.
These observations cast some doubt in the deliberate release of toxic batches hypothesis for me.
What is evident is that there is no QC and as you said “there’s nothing right with any of this.”
I would highly recommend reading the legislation around EUAs. You will find all kinds of golden nuggets inside it...
One particular point is §E(3): the FDA can "waive requirements regarding current good manufacturing practice otherwise applicable to the manufacture, processing, [and] packing..."
In other words, there is no QA required. They could potentially vary each individual lot to conduct unauthorised dose-finding and other 'interesting' studies...
If they bribed their way into subjecting the whole world to Phase 3 Trials - without informed consent - what wouldn't they do with QA waived for 'emergency reasons'?
(Ref: 21 USC §360bbb–3 | Authorization for Medical Products for Use in Emergencies
I have received a couple of comments from Craig Paardekooper. Like you I had conjectured that he derived the date of the deployment of the batches from the batch ID. But we are wrong. His account of what he did is as follows:
“Dear Andrew
perhaps this might explain the time sequence -
NOTE ON TIME SEQUENCE OF BATCHES
Note: The time sequence of all batches is determined by the order in which each batch first appears in VAERS. This inturn is determined by the order of the VAERS ID for the first report associated with that batch.
The VAERS ids are ALWAYS ascending, are completely numeric, and are unique. As each new report is made, the VAERS system generates the next successive numerical VAERS ID for that report.
Consequently, the resultant graph depicts the time sequence in which the batches were FIRST REPORTED for adverse reactions. Yes, there could be a delay between the deployment of a batch and the first report, HOWEVER this would be totally insignificant given the number of reports generated by batches, and the very high probability that some reports were generated within a day of taking the vaccine.”
A further comment is this.
“I have seen Jessica's post.
My time sequence for the batches is based on the sequence of VAERS Ids. As each report is added to VAERS it generates a new VAERS Id - which is a pure number, always ascending.
I count the number of adverse reactions for each batch in the order in which those batches appear in the VAERS database - in other words, the order in which a FIRST adverse report is made for each batch.
Now, if there was one report for a batch, then the whole batch must have been made prior to that time - so we have, in effect, the order in which the batches were reported, which equals the order in which the batches were deployed.
Consequently, my graph is sound.
Jessica may have assumed I was sequencing the batches based on batch lot numbers.
Regards
Craig”
These explanations make perfectly good sense to me. As far as I can see they support the whole analysis given in his video, including the temporal separation of the batches of the three manufacturers.
His analysis strikes me as being so extraordinarily significant that I would like to see attempts at disconfirming it from every possible angle, to see whether it still stands.
I thought you had his email address, but if not I am happy to act as go-between between you and him. If you would like me to send you his email address just email me at the address I used to subscribe here. In any case I will be most interested in any further consideration of his analysis.
On Dec 3, 2021 Craig Paardekooper responded to an email of mine, as follows:
“Andrew, Jessica was right. Excel reorderd the batches alpha numerically in order of the batch numbers, which caused the deployment pattern. So what the "deployment" pattern reveals is something very interesting - namely that with Pfizer when batches are sorted alphanumerically and counted, then they cluster into specific ranges of toxicity - because Pfizer was using batch code sequences for specific toxic ranges.
Moderna was more careful to avoid alphanumeric sequences, by putting the toxin level identifier at the end of the string instead of at the beginning. As a result when we do the same plot for Moderna it looks random. Yet on closer examination, we find that all batches in excess of 1780 x base toxicity end in 20A, and below 1780x level there is a sharp change in batch number ending - it changes from 20A to 21A”
Since then he has taken down the video linked in Jessica's post. In that video he had said that a temporal separation of clumps of adverse events made it look as if the 3 manufacturers had been allocated their own time periods. The temporal separation claim seems particularly implausible to me, and in her post here Jessica shows that it does not make sense.
The most recent (December 6, 2021) video Paardekooper has put out is titled MODERNA USED THE ALPHABET TO LABEL DIFFERENT TOXICITIES OF VACCINE, which can be found here: https://www.bitchute.com/video/vImdZ7WsV9iW/.
The patterns Paardekooper is uncovering are indeed remarkable and do lend credence to the hypothesis that deliberate testing for toxicity is taking place. However, we should also be looking for alternative hypotheses. Is there some way of reconciling the lot number patterns with a more accidental correlation with adverse events? Might there be some inadvertent failure within the manufacturing process that would explain the patterns? Might some groups of lots have been ruined in the shipping process (e.g., they were ruined by high temperature)? It would help a lot if someone who is familiar with these processes were to offer suggestions.
Andreas Oehler offers a plausible explanation. He says that the patterns could be a result of how the data is reported, and not that the vaccine lots are labelled according to toxicity:
Jessica, there was a discussion about the idea of "highly toxic lots" in the comments section to your Nov. 2 article "A Report on Myocarditis Adverse Events....". At that time, you said that the data was too sparse to support any conclusions or claims about significant patterns. You were especially concerned that many records have missing or obviously spurious VAX_LOT fields.
I'm glad to see that you're still looking at this. The distribution of events is very different from what I would expect from randomly distributed, sparsely sampled AE's. So, I was puzzled by your earlier dismissal.
Could you clarify how your thinking has changed, about the problem of sparse data?
Is it possible that reporting bias could be an important factor? That is, Steve Kirsch mentions one particular neurological practice with 20,000 patients that reported 2,000 AE's. Other clinics might have made zero VAERS reports even with similar actual AE rates. What if clinics with high reporting propensity, were somehow associated with shots from just a few lots?
THE EXPOSE (UK) noticed that AE reports from red states were coming in at a much greater rate than blue states. The rate from Kentucky was about 20x worse than from California. They thought perhaps the red states were being targeted with bad lots. But perhaps again it's a reporting bias, as red-state doctors are much more likely to report AE's?
I agree reporting bias has effects...however, as to this analysis, the data show a clear signal and that's what we're looking for. If we had systematic, independent lot testing that normally happens, we would know for sure - but bet your bottom dollar, that's by design.
It would be good to get Craig Paardekooper’s input on this, and I have been trying to find contact information for him. I haven’t been able to find an email address for him, but I have left messages in various places, such as this facebook page, https://www.facebook.com/craig.kooper.3. He has videos on bitchute: https://www.bitchute.com/Craig-Paardekooper/. I hope he will join in here.
Your hypothesis that Craig is taking the deployed date of the Vaccine Lot from its alphanumeric ID is plausible, and if this was done without taking into account the differing ID patterns used by the differing manufacturers, then this would indeed explain the apparent temporal separation of the batches by manufacturer. However, this seems to me too obvious an error for Craig to have made, though I grant he might have gotten excited about seeing a pattern which didn’t mean what he took it to mean, and so leapt too quickly to a mistaken interpretation. But we can ask him, if he will join in.
It is a reasonable conjecture that each manufacturer will be auto-generating its own Vaccine Lot ID, and that these will occur in ordinal sequence per manufacturer. It might be interesting to separate the data by manufacturer and then graph the AEs by Lot ID, and see what it shows.
I have read a story about a previous coverup in which bad batches were spread out geographically so as to conceal them. (I will look for a reference to that story, but I don’t have it right at my fingertips.) I think that Craig is suggesting that we are looking at an even more sinister scenario: namely that the data show the fingerprints of a deliberately designed medical experiment. It is important to note that if we are looking for confirmation of such a scenario then we are over-focussing on dates. All that matters is VL ID. Imagine, for example, that certain lots contain discrete amounts of graphene hydroxide, but most do not. The experimenters need not care about dates as long as they are able to calibrate the lethality by lot number. I do not myself believe that we are in such a scenario, but I do not discount the possibility, which is why I find Craig’s analysis so alarming.
Yes it would. But no one can find an email address and I don't have a phone. Everyone makes mistakes. Myself included. But I am 99% sure that this is what he did. I also share excitement. I am MORE than willing to do deeper into this with him. It would be loads of fun.
I have been looking at Craig's Data too..just a novice..Today my sister got her ....I asked her...What number did you receive..she said...Oh they have stopped that now because of the V passports..this is in NZ.. I was like OMG......watch this space people...
I come away from Craig’s and this analysis with a very bad smell lingering … clearly something is not right. Jessica, I love your critical eye! However, as Craig’s temporal ordering was not by alphanumeric sorting but by VAERS report date (very smart!) we are left again with something like his disturbing conclusion that batches are being varied to see what AE reports result. Which leaves us with two “certainties” and more questions:
1) VAERS is not the crappy unreliable system the CDC/FDA claim it to be. It is possibly serving as the platform for a massive trial on the general public? Thus would mean the big three are consuming this data as carefully as we are. I believe
the data quality is pretty good as far as large databases go … I have read new reports are managed and examined by a third party before being released weekly for consumption. Great care goes into identifying duplicate reports.
2) the appetite of Big 3 and FDA/CDC to willfully inflict harm on the public knows no end. If data shows ongoing toxicity in new batches and the data IS being monitored and used by B3 et al, there must be a tremendous confidence in the shield provided by liability regulations. It suggests entities operating entirely outside societal structures like law and morality. This in itself is something new? I have not spent time researching previous examples of vaccine malfeasance (I am a only layperson … mom-of-five unwittingly turned covid-analyst) but from a distance they seem more “bounded” namely by strictly bounded victim pools (ie the military, impoverished children of a particular region in India etc)
As an aside, this is a paper I refer to regularly to understand the strengths and weaknesses of VAERS. It also argues an URF of 34. To dismiss VAERS as irrelevant, the position of mainstream media and officials, is absolutely incorrect.
1: Could the lot variation be the product of systemic under-recording, where to muffle the signal many batches were capped? I imagine capping all batches would disillusion honest staffers who knew reports went up but didn't see it represented in the data, so perhaps a way of attenuating AE presentation systematically but still presenting an increase would be to allow true figures for only a subset of the batches?
2: It appears from some of the videos that the toxic batches were sent all over, but the benign ones weren't. Isn't that the sort of impression that might simply just be the result of all batches being sent all over, but only those with a high number of reports having reports associated with most states?
Love your analysis of an analysis. A couple questions:
Do we know how many vials are in a lot number and does this vary? Could it be that the toxic VLs simply had more vials produced and deployed than the less toxic VLs?
How could a manufacturer vary the “payload” or other attributes across VLs? Doesn’t the EUA have required specs?! I.e., what product was actually authorized if the mfg is allowed to alter the authorized spec?
Do we know if the VLs deployed in the US all come from the same mfg plant? The use of letters in the nomenclature suggests to me different plants. And shouldn’t the numbering/lettering be part of the EUA spec?
Thank you and these are all amazing questions. I don't have any answers. You could write to Pfizer. They would be more than willing to ignore, I mean, help you. ;) I am sure they are made at different geographic locations and as for the intentional payload variation, I don't believe in this idea. I believe that if the payload is modified from lot to lot then this is due to distribution and storage inconsistencies.
Thanks for replying. I just read another theory that the “safer” VLs may appear so because the # of VAERS reports have become suppressed over time. Who knows what to think in these crazy times! Keep up the great work!!
It’s true that all aspects of manufacturing are subject to tests & those tests will have results for which there’s an acceptable range. Under normal conditions, the manufacturers & regulators keep the former honest.
But forget normal times. Imo all institutions are dead including FDA.
There’s not a chance these products would get authorised if usual considerations applied.
A healthy 40 year old is far more likely to be injured or even killed by these “vaccines” than the virus, no question.
That ends any consideration of their use in healthy 40 year olds. Or anyone else as it turns out.
As FDA is not doing its basic job on safety, it’s not likely to tapping them on the shoulder about manufacturing consistency.
In U.K., a QP I know told me that he couldn’t do his job, because masses of product were disappearing from where they were supposed to be for periods of time (a Qualified Person checks & verifies just the sorts of things you asked).
When they reported this, the response was more or less “Don’t you know there’s a pandemic on?” (During WW2, quite a lot of irregularity occurred all over the place, presumably because corners were being cut, usually to get the job done rather than for any other reason, though of course that allowed small time crooks to exploit the chaos, and if anyone questioned why proper procedure wasn’t being followed, the usual remark was “Don’t you know there’s a war on?”)
Thanks so much for this insight. And I am not surprised to hear about the product disappearances. I wouldn't be surprised to hear much these days. There's absolutely nothing right with any of this. It's like the world of people entered a Cuckoo clock and we are all stuck inside with the incessant bird squawking 'safe and effective' 24/7. If I didn't have these analyses to keep me busy and the new and wonderful substack medium to keep me writing, I would probably lose my mind over this. It's completely bonker doodles.
I concur with Dr Yeadon. I'm retired pharma (25 years) in all aspects of drug development. Your analysis, along with the original video, proves beyond a shadow of a doubt, that there is no manufacturing control. This alone should have halted the jabs (along with so many other obvious violations of medical and manufacturing reasons).
From day 1, no animal studies meant that those who are taking the jab are the animals in this study. I have no doubt they are monitoring it all and know the issues. If they had manufacturing control, including all of the requisite stability studies for product, the AEs would be evenly distributed statistically across all lots.
There are additional factors as well such as differences in distribution of the LNP, translation of mRNA output (effective dose), post-translational modification, and release of spike among a host of other factors such as immune response differences in cohorts. This is a combination product and the complexity of this system would take years to study properly before ever being approved properly according to the FDAs own guidances. However, thanks to 'Emergency Authorizations' being abused in many countries, they are getting away with harm and murder. There is no other way to put it. I've been following your work since your first video - its invaluable analysis.
There is no other way to say this, but its one big clusterf&ck.
The FDA undertook to rigorously monitor quality control of this EUA biologic (along with an undertaking to rigorously monitor adverse events). Two “r” words that have changed their definitions during the pandemic- rare and rigorous!
The EMA approval of Pfizer included five specific obligations that were to be met by specified dates.
Have these been satisfied?
Is anyone following up?
These form part of the approval and as such, must be met or formally waived by EMA.
Either way, is any agency following through?
See 👇🏻
https://twitter.com/gutwat1/status/1446339086097207335?s=21
Also, to date 8bn doses have been administered (1.3bn vials).
This is a novel mRNA product that has never been produced for human application before, let alone on this scale.
MRNA and it’s delivery mechanism via LNP’s are novel and also notoriously fragile and complex to manufacture.
Has any one ie drug development, engineer, Pharma etc sat down and analysed if this 8bn dose volume is even remotely feasible given the technical expertise required at all levels and at every manufacturing facility; retooling of manufacturing plants; manufacturing plant capacity; supply chain ie availability of raw materials incl vials etc and every other step of the process?
This was raised by a 30-year chemical and Pharma professional recently.
I tried but was unable to attach the screenshot of his post.
I love following your work J.
Thank you for your valuable contribution, analysis and insight. 💫
Re the VAERS batch analysis:
from casual observation, EUdravigilance, WHO Vigibase, Yellow Card, DAENS (Aust) and VAERS seem consistent in the number of AE, SAE and deaths recorded on a per capita basis (Yellow Card is massively under reported as most don't know of its existence and NHS doctors appear disinterested).
Plus the recently released Pfizer 90-day post authorisation data of 42,086 case reports containing 158,893 events incl. 1,223 deaths.
These observations cast some doubt in the deliberate release of toxic batches hypothesis for me.
What is evident is that there is no QC and as you said “there’s nothing right with any of this.”
I would highly recommend reading the legislation around EUAs. You will find all kinds of golden nuggets inside it...
One particular point is §E(3): the FDA can "waive requirements regarding current good manufacturing practice otherwise applicable to the manufacture, processing, [and] packing..."
In other words, there is no QA required. They could potentially vary each individual lot to conduct unauthorised dose-finding and other 'interesting' studies...
If they bribed their way into subjecting the whole world to Phase 3 Trials - without informed consent - what wouldn't they do with QA waived for 'emergency reasons'?
(Ref: 21 USC §360bbb–3 | Authorization for Medical Products for Use in Emergencies
https://www.law.cornell.edu/uscode/text/21/360bbb-3)
Thank you for this. I want these people on the gallows.
Very interesting and disturbing!
Jessica,
I have received a couple of comments from Craig Paardekooper. Like you I had conjectured that he derived the date of the deployment of the batches from the batch ID. But we are wrong. His account of what he did is as follows:
“Dear Andrew
perhaps this might explain the time sequence -
NOTE ON TIME SEQUENCE OF BATCHES
Note: The time sequence of all batches is determined by the order in which each batch first appears in VAERS. This inturn is determined by the order of the VAERS ID for the first report associated with that batch.
The VAERS ids are ALWAYS ascending, are completely numeric, and are unique. As each new report is made, the VAERS system generates the next successive numerical VAERS ID for that report.
Consequently, the resultant graph depicts the time sequence in which the batches were FIRST REPORTED for adverse reactions. Yes, there could be a delay between the deployment of a batch and the first report, HOWEVER this would be totally insignificant given the number of reports generated by batches, and the very high probability that some reports were generated within a day of taking the vaccine.”
A further comment is this.
“I have seen Jessica's post.
My time sequence for the batches is based on the sequence of VAERS Ids. As each report is added to VAERS it generates a new VAERS Id - which is a pure number, always ascending.
I count the number of adverse reactions for each batch in the order in which those batches appear in the VAERS database - in other words, the order in which a FIRST adverse report is made for each batch.
Now, if there was one report for a batch, then the whole batch must have been made prior to that time - so we have, in effect, the order in which the batches were reported, which equals the order in which the batches were deployed.
Consequently, my graph is sound.
Jessica may have assumed I was sequencing the batches based on batch lot numbers.
Regards
Craig”
These explanations make perfectly good sense to me. As far as I can see they support the whole analysis given in his video, including the temporal separation of the batches of the three manufacturers.
His analysis strikes me as being so extraordinarily significant that I would like to see attempts at disconfirming it from every possible angle, to see whether it still stands.
I thought you had his email address, but if not I am happy to act as go-between between you and him. If you would like me to send you his email address just email me at the address I used to subscribe here. In any case I will be most interested in any further consideration of his analysis.
On Dec 3, 2021 Craig Paardekooper responded to an email of mine, as follows:
“Andrew, Jessica was right. Excel reorderd the batches alpha numerically in order of the batch numbers, which caused the deployment pattern. So what the "deployment" pattern reveals is something very interesting - namely that with Pfizer when batches are sorted alphanumerically and counted, then they cluster into specific ranges of toxicity - because Pfizer was using batch code sequences for specific toxic ranges.
Moderna was more careful to avoid alphanumeric sequences, by putting the toxin level identifier at the end of the string instead of at the beginning. As a result when we do the same plot for Moderna it looks random. Yet on closer examination, we find that all batches in excess of 1780 x base toxicity end in 20A, and below 1780x level there is a sharp change in batch number ending - it changes from 20A to 21A”
Since then he has taken down the video linked in Jessica's post. In that video he had said that a temporal separation of clumps of adverse events made it look as if the 3 manufacturers had been allocated their own time periods. The temporal separation claim seems particularly implausible to me, and in her post here Jessica shows that it does not make sense.
The most recent (December 6, 2021) video Paardekooper has put out is titled MODERNA USED THE ALPHABET TO LABEL DIFFERENT TOXICITIES OF VACCINE, which can be found here: https://www.bitchute.com/video/vImdZ7WsV9iW/.
The patterns Paardekooper is uncovering are indeed remarkable and do lend credence to the hypothesis that deliberate testing for toxicity is taking place. However, we should also be looking for alternative hypotheses. Is there some way of reconciling the lot number patterns with a more accidental correlation with adverse events? Might there be some inadvertent failure within the manufacturing process that would explain the patterns? Might some groups of lots have been ruined in the shipping process (e.g., they were ruined by high temperature)? It would help a lot if someone who is familiar with these processes were to offer suggestions.
Andreas Oehler offers a plausible explanation. He says that the patterns could be a result of how the data is reported, and not that the vaccine lots are labelled according to toxicity:
https://live2fightanotherday.substack.com/p/exposing-the-expose-in-good-way. I don’t find this completely convincing as it does not explain the ranges of adverse events as grouped by the Pfizer lot ID patterns, but there might be an explanation for that that is not yet clear to me.
On a related note, see http://whale.to/c/olmsted_on_autism1979.html for a historical example of a pharmaceutical company doing a coverup of bad vaccine lots.
I'm rarely monosyllabic, but... "Whew!"
Jessica, there was a discussion about the idea of "highly toxic lots" in the comments section to your Nov. 2 article "A Report on Myocarditis Adverse Events....". At that time, you said that the data was too sparse to support any conclusions or claims about significant patterns. You were especially concerned that many records have missing or obviously spurious VAX_LOT fields.
I'm glad to see that you're still looking at this. The distribution of events is very different from what I would expect from randomly distributed, sparsely sampled AE's. So, I was puzzled by your earlier dismissal.
Could you clarify how your thinking has changed, about the problem of sparse data?
Is it possible that reporting bias could be an important factor? That is, Steve Kirsch mentions one particular neurological practice with 20,000 patients that reported 2,000 AE's. Other clinics might have made zero VAERS reports even with similar actual AE rates. What if clinics with high reporting propensity, were somehow associated with shots from just a few lots?
THE EXPOSE (UK) noticed that AE reports from red states were coming in at a much greater rate than blue states. The rate from Kentucky was about 20x worse than from California. They thought perhaps the red states were being targeted with bad lots. But perhaps again it's a reporting bias, as red-state doctors are much more likely to report AE's?
https://dailyexpose.uk/2021/11/10/deadliest-batches-of-covid-vaccine-sent-to-red-states-in-usa/
I agree reporting bias has effects...however, as to this analysis, the data show a clear signal and that's what we're looking for. If we had systematic, independent lot testing that normally happens, we would know for sure - but bet your bottom dollar, that's by design.
My thinking hasn't changed... just in a process. Glad that you're glad. :) Reporting bias? Dunno.
Correction: Steve Kirsch said the neurological practice SEES 2000 AEs, but has only reported 2 to VAERS, for an URF of 1000.
Oops! Thanks for the correction.
Have you read Andreas Oehlers writing on this?
https://live2fightanotherday.substack.com/p/exposing-the-expose-in-good-way
Just did! Thanks for the link. I subscribed. I love the like minds converging. We will catch them with their pants down for sure. I know it.
Craig Paardekooper has posted another video today (Dec. 1, 2021) at https://www.bitchute.com/video/g62gcJrOuOYu/, titled COVID VACCINE BATCH NUMBERS CODE FOR TOXICITY. He uncovers an extraordinary pattern. The video at https://www.bitchute.com/video/6xIYPZBkydsu/, VARIATION IN TOXICITY OF COVID VACCINE BATCHES is also worth watching.
I know. I watched the first one. And the second one that you list is what this article is about.
I think this might be a HOT LOT #032H20A: https://i.imgur.com/GCqqSPf.jpg
Well done data analysis. If only most commentators were as competent as you.
I have done some analysis on cleaning up Lot numbers.
I noticed for MODerna, aswell as their format 999X99X (eg. 025J20A) they also have a format 999X99-9X (eg: 025J20-2A)
I noticed a large number of events against 025J202A, but this is not a valid Lot# and should actually be 025J20-2A.
I recognize my vax lot in your work. Yikes.
It would be good to get Craig Paardekooper’s input on this, and I have been trying to find contact information for him. I haven’t been able to find an email address for him, but I have left messages in various places, such as this facebook page, https://www.facebook.com/craig.kooper.3. He has videos on bitchute: https://www.bitchute.com/Craig-Paardekooper/. I hope he will join in here.
Your hypothesis that Craig is taking the deployed date of the Vaccine Lot from its alphanumeric ID is plausible, and if this was done without taking into account the differing ID patterns used by the differing manufacturers, then this would indeed explain the apparent temporal separation of the batches by manufacturer. However, this seems to me too obvious an error for Craig to have made, though I grant he might have gotten excited about seeing a pattern which didn’t mean what he took it to mean, and so leapt too quickly to a mistaken interpretation. But we can ask him, if he will join in.
It is a reasonable conjecture that each manufacturer will be auto-generating its own Vaccine Lot ID, and that these will occur in ordinal sequence per manufacturer. It might be interesting to separate the data by manufacturer and then graph the AEs by Lot ID, and see what it shows.
I have read a story about a previous coverup in which bad batches were spread out geographically so as to conceal them. (I will look for a reference to that story, but I don’t have it right at my fingertips.) I think that Craig is suggesting that we are looking at an even more sinister scenario: namely that the data show the fingerprints of a deliberately designed medical experiment. It is important to note that if we are looking for confirmation of such a scenario then we are over-focussing on dates. All that matters is VL ID. Imagine, for example, that certain lots contain discrete amounts of graphene hydroxide, but most do not. The experimenters need not care about dates as long as they are able to calibrate the lethality by lot number. I do not myself believe that we are in such a scenario, but I do not discount the possibility, which is why I find Craig’s analysis so alarming.
Yes it would. But no one can find an email address and I don't have a phone. Everyone makes mistakes. Myself included. But I am 99% sure that this is what he did. I also share excitement. I am MORE than willing to do deeper into this with him. It would be loads of fun.
UPDATE: in a joint email with him now... the internet is brilliant.
I have been looking at Craig's Data too..just a novice..Today my sister got her ....I asked her...What number did you receive..she said...Oh they have stopped that now because of the V passports..this is in NZ.. I was like OMG......watch this space people...
What? They stopped putting lot numbers on the vials because of the V passports?
I come away from Craig’s and this analysis with a very bad smell lingering … clearly something is not right. Jessica, I love your critical eye! However, as Craig’s temporal ordering was not by alphanumeric sorting but by VAERS report date (very smart!) we are left again with something like his disturbing conclusion that batches are being varied to see what AE reports result. Which leaves us with two “certainties” and more questions:
1) VAERS is not the crappy unreliable system the CDC/FDA claim it to be. It is possibly serving as the platform for a massive trial on the general public? Thus would mean the big three are consuming this data as carefully as we are. I believe
the data quality is pretty good as far as large databases go … I have read new reports are managed and examined by a third party before being released weekly for consumption. Great care goes into identifying duplicate reports.
2) the appetite of Big 3 and FDA/CDC to willfully inflict harm on the public knows no end. If data shows ongoing toxicity in new batches and the data IS being monitored and used by B3 et al, there must be a tremendous confidence in the shield provided by liability regulations. It suggests entities operating entirely outside societal structures like law and morality. This in itself is something new? I have not spent time researching previous examples of vaccine malfeasance (I am a only layperson … mom-of-five unwittingly turned covid-analyst) but from a distance they seem more “bounded” namely by strictly bounded victim pools (ie the military, impoverished children of a particular region in India etc)
As an aside, this is a paper I refer to regularly to understand the strengths and weaknesses of VAERS. It also argues an URF of 34. To dismiss VAERS as irrelevant, the position of mainstream media and officials, is absolutely incorrect.
https://cf5e727d-d02d-4d71-89ff-9fe2d3ad957f.filesusr.com/ugd/adf864_0490c898f7514df4b6fbc5935da07322.pdf?fbclid=IwAR2YHIudpnRhVYNKfDyqCqRdSAUUnP4Q277iz2qjzSKf_C4fUNjfvxZQqZU
Here is so far the complete batch nos. With their toxicity www.howbad.info
Dumb questions:
1: Could the lot variation be the product of systemic under-recording, where to muffle the signal many batches were capped? I imagine capping all batches would disillusion honest staffers who knew reports went up but didn't see it represented in the data, so perhaps a way of attenuating AE presentation systematically but still presenting an increase would be to allow true figures for only a subset of the batches?
2: It appears from some of the videos that the toxic batches were sent all over, but the benign ones weren't. Isn't that the sort of impression that might simply just be the result of all batches being sent all over, but only those with a high number of reports having reports associated with most states?
Robin Monotti and Dr Mike Yeadon mentioned your post.
https://t.me/robinmg/12802