Aha. Which is why I led with "still groggy". I'll have to wait til I've finished breakfast (all the critters cared for 1st!) & 2nd coffee. I still can't follow the text or find purebloods in the tables...
Here are some examples of how the raw data looks when you exclude it to the young (where some of these weird effects are flipped) and to unvaxx vs just 1st dosed or 21 days after dose 1 or 2 https://unglossed.substack.com/p/into-the-weeds-uk-deaths-data
It sounds to me like you are filling in missing details in a knowledge framework where you suspect there is a problem, but aren't sure what it is.
Unfortunately, that's what a lot of people are doing, and that is problematic. It's one thing to say that the data doesn't have integrity. It's another to explain specifically how. That part is necessary for some purposes beyond holding skepticism.
RE the Pfizer trial, cases were tracked starting at Dose 1 and we’re published in 2020 in the trial paper, it’s the red dots in the abstract https://www.nejm.org/doi/full/10.1056/nejmoa2034577 - the Clinical Overview goes into more detail as far as efficacy for these periods - https://unglossed.substack.com/p/the-trial?s=w#footnote-5 - But then these aren’t included in the main, headline efficacy finding, but we know that that number was an illusion anyway because the juice wears off after ~4 months. But anyone could work out a window-free efficacy number for themselves using the abstract.
The UK has a loose definition set (UKHSA) and then a strict one (ONS, get a dose and you are 1st dose < 21 days). Stats in the US always vary by health department or dataset. They are all very unreliable. But some of the CDC studies, including the big Delta / Omicron study, took care to exclude the “partially” rather than call them unvaxxed https://unglossed.substack.com/p/means-etc?s=w#footnote-anchor-3 - But again this is using state health dept data that could be fudged or not have accurate vaxx status for everyone (and so “unvaxxed” = missing status, though again there are some CDC publications including the main dashboard that allege these are excluded too).
Importantly, whether the CDC results are accurate or fraudulent they show that you can put together a pro-vaxx graph without using the 14 day fudge. And so the existence of such graphs is not proof that the fudge, where it is employed, is making any difference to the stats. and once again that’s already solved by looking at the ONS data instead because there’s ostensibly no fudge, so the question is what else is going on.
Ah, okay, thank you Brian for this explanation. I see I got that idea from the Pfizer trial press releases. But as you and Matthew have pointed out in posts - God knows what's going on with the data. I have really learned that statistics can be made to show just about anything, especially when the raw data is hidden. But even then, it depends on vaxxed and vax free people being categorized correctly.
I just had one semester of stats in grad school.
Btw, that is so cool that the links you provided go right to the part of your post that I needed to read. (I think you did that on purpose). That is really advanced substacking. 👍🏼❤️
Of course there are shenanigans going on. Heck, they've never even proven that "regular" (pre-Covid) vaccines are effective in the long term. The whole thing is a giant myth birthed by the Great White Polio Panic of the 1940s and 50s (when they used to literally think black people were immune) combined with the WHO finally getting a win in the 70s with their smallpox program. When the WHO was founded, the two big issues were cholera and malaria, neither of which has ever shown any improvement whatsoever.
Yeah — kids’ school registration for next year coming up, and I’m going to have to spend time this summer researching any shots that are supposed to happen. Not in a place where we can assume anything anymore.
Though with VAERS as my guide, effective or not I’d take any of those older shots over these things.
True, and if you look back to when vaccines began hitting the market, sanitation was getting better, so the number of disease cases were already coming down before the vaccines became available. The vaccines didn't improve the numbers, cleanliness did.
My microbiology profs said the same thing about clean water, sanitation and hygiene in the 70's. About all you can say is that vaccines probably had some effects on the margins.
It's frustrating to know that Fauci and Kaiser and the CDC and the DoD have all the numbers you need, but they just don't want to share, and they won't share until the numbers don't matter anymore, and there is no group within the House of Representatives, or the Graveyard that is the Senate, that is working to make them share the numbers now. Ron Johnson is working alone, and appears to be a 'safety valve' to control pressure.
May 9, 2022·edited May 9, 2022Liked by Mathew Crawford
So, a same-day death theory would just be a narrower version of Fenton’s time lag theory as far as I understand the latter.
Both have a flaw, at least in the younger groups where Pfizer is used, in that same-day Dose 2 deaths should then dump into the Dose 1 <21 days column. And AEs seem to be higher on Dose 2 though there’s not good fidelity with then AE data. Either way it should auto-correct the Dose 1 <21 days group starting older than the current reversal.
You already saw my comment RE not-deathbed bias on Kirsch’s post. I still think that is sufficient to explain everything, right down to why the bias drops when age does. I have offered an explanation of the immortality effect and the dying straggler effect using an analogy with a room full of citizens going up to get Panera buzzers https://unglossed.substack.com/p/the-panera-kingdom-problem
This isn't just the time lag theory, which creates an artificial data matching.
If my guess is correct, we're talking about a protocol problem baked into an automated counting system that timestamps not continuously, but discretely.
It is possible that this problem has been noted in the past, and that the statistical sieve could be used to justify fraudulent trial data.
I still think, though perhaps as a result of incomprehension on my part, that that suggests the issue should recycle at Day 21 in groups that went for Pfizer, though not to the same degree as for a longer lag and not as much when a blend of brands was popular in an age group. So you could ask if this is instead driving dose 1 > 21 days deaths (as opposed to a straggler effect) due to longer between-dose intervals.
So whereas you focused on the older less noisy groups I would use the young as a more sensitive test of the theory. In the second version of my hack of the ONS spreadsheet, where dose 1 >21 days is highlighted, I would note the super-low absolute death counts. So despite the high rate (straggler effect) there’s not a ton of actual dying. Actually I could try throwing those back into the <21 column to see what happens. Meanwhile the rate is super low in the <21 days despite the fact that the young move the 2nd dose closer to dose 1 because Pfizer https://unglossed.substack.com/p/into-the-weeds-uk-deaths-data
Thank you Mathew. The DPDH hypothesis certainly may be a contributor. There must be something else going on, right? Only 16% of vaccine deaths occur within 24 hours (VAERS). The others will end up in one of the vaxxxxed buckets (mitigating the immortality effect) or be misclassified as a C19 death (driving down VE).
Did you attempt to calculate the potential size of the effect of this partial day mis-classification? Would it have such a big effect? Intuitively it feels like it would not have such a large impact, unless the vaccine is really killing a crapload of people within 12 hours of taking it.
This was a "quick look" for me, and I wanted to share my thoughts.
But yes, it is killing a large portion quickly. The VAERS time curve is steep. Add that to the 2,000 deaths not counted into the stats, and the effect is substantial.
Thanks for the analysis. While I find the same day hypothesis interesting, for me a huge point here is the consistency of the 13% number year over year. IMO this is a deal breaker for VE considering UK had both very high uptake and high spread in 2020.
It reminds me of Gatos comparisons of Israel and Palestine, showing very similar outcomes over the past winter despite huge differences in vax rate. Now, we see the same effect happening in a region compared to it's 2020 self. I know many other such analyses have shown this too, but I find this one particularly compelling because of the consistency.
I live in the UK, I had 2x Astra Zennica,+ Pfizer booster,(Comirnaty,for all you US citizens who think that version is OK) VERY BAD effects,it took over half an hour to even list on the Yellow Card register.Your VAERS…There are endless boxes where you have to think of a word that describes your symptoms ( example: my description, prismatic effect on edges of vision of vision field) nothing! Etc etc eventually visual disturbances produced a drop down list….Anyone without a good command of medical language would have problems producing the numerous drop down boxes, if you can’t find anything you CANT MOVE ON with the filing 🤬🤯
I am lucky I am still here 6 months later 🤞🏻
Then regarding ONS Data, without a doubt the rules governing the filing of info is biased in every way to make the vaxed deaths look like unvaxed ,that is the same in almost every country….If I had died in the 2 weeks after the vax I would have been unvaxed..HEY PRESTO another STUPID UNVAXED PERSON BITES THE DUST.
THANK YOU MATHEW👏🏻👏🏻👏🏻
for showing us even more fixing of the figures ,and in such a numerous ways, but all of us readers are here becomes we know that…
In UK practically one third are not vaxed with these EUA products,the other 2/3 rds.had NO IDEA we were being lied to, we trusted our UK Gov ,our NHS.I was one of those and I am having extreme difficulty showing the others what is going on.
The PCR Case …FAKE. ONS Fig FAKE (Rigged)…TOTAL MEDIA CENSORSHIP IN UK.
THANK YOU AGAIN for giving me some more ammunition to fight this battle.🤗 😊
How do you heal? Soul, physiology, and informationally?
Have you tried the Macrophage Repolarisation Therapy proposed by Bruce Patterson (see yt: Spike in immune cells, by DrBeen medical). Or skirsch at io und Treatment, search for maraviroc.
I try to do it via TCM, found a PoT-Cov protocol in DE (search Covid tcm.edu ).
Then Intry to use the book „ Ploberger - Rezepturen aus westlichen Käutern für Syndrome der TCM“ to be able to pluck some herbs growing locally from the meadow.
I tried Grapeseed Extract (anti-CCR5), Artemisia Annua (anti-*, viral here) and Moringa (delaying metabolisation of artemisin in liver, like Ritonavir from Aids-Medication in Paxlov* from Pfi*, only plants are “evulutionary tested” - we grew up with them:)
But you have to combine several “cures” in parallel and in sequence, I added baking soda (5g/d in 1-2L water, a glass on empty stomach) and CDS with DMSO (detox protocol, gives me energy), also plant based: waltnut leaves ground to dust 1-3TS / d in something binding. An a lot from I-Recover by FLCCC like Zn, VitC, Black Cumine Oil, and add MCAS medication esp. montelukast as need gets bitter.
Of course the shots only did make things worse, much worse, but they also sped up degradation so horribly. We are now fighting a juvenilisation fight for immune system. Search for cheap tricks to get old. Like doing tarzan’s chest drum 20x in the morning. If you like cry tarzan’s call to it. This was from an old Austrian physio-therapist with “golden hands”. :) )
Thank you Andy for this helpful summary, I have bought DMSO and follow all of the experts you mention but there are a few other helpful suggestions for me to explore.I am also trying Wim Hof breathing, saunas and a 6/18 eat/fast regimen,( boost autophagy)👍after going deep into the history of big Pharma I will never have another vaccination of any sort again.I am not sure how my little dog or 84 year old neighbours will like a regular Tarzan routine 😂🤣I hope you have managed to cure yourself if you have also been vax damaged….🤗😊
This is whereI was headed in the wee hours. Bad Cattitude has been describing bayesian datacrimes -- & doing corrective statistical analysis -- for many months now!
Fascinating analysis. I like this hypothesis. I'm not sure you need a data sieve at the statistical level - just normal anchoring bias. After having been ascribed to COVID there would be no reason for the attending physician to consider assigning the death to the vax and it would go unreported as such. Here in the UK, much free PCR testing occurred, at drop-in stations and at places of work. Those who felt the need to attend a voluntary test and those whose employer made them do it would have been more likely to take up the offer of a shot.
Mathew, do you think they are seeing more deaths than they predicted, or less, given that some damn body really must have known what the heck this was going to do to the particular populations and there certainly had to be "a plan" from the very start.
I mean, this damn thing seems to have been in the works for a long time.
I don not believe we got here because of a "stumbling colossus."
that's a bingo! here is what's going on in the db code. each person has a datetime field for vaccine date and death date. In order to find the difference in time between these fields, you use a datediff operator in SQL
DATEDIFF ( datepart , vaccinedate , deathdate )
The datepart can be set to days, hours, minutes etc
Since everything in ONS is defined by "days" the programmer spec requirements would have used days. And days is defined as 24 hours between dates.
So if you get vaccinated and die less than 24 hours then no matter what you are in the unvaccinated bucket.
And here's the kicker.
What happens when they find your body dead the next day after vaccination?
Do they give you a time of death?
If they don't then guess what happens in the db when you don't input a time?
The time will automatically default to
midnight 00:00:00 for that date.
I'm sure they don't always know when you died so they just enter a date with no time.
So if you if you died on Jan 1 2022 and no time was entered then the database records it as
"Published Date" will be difficult to compute unless you've been tabulating on your own as there is no data field in the downloads for published or "appeared" date...
Great observation, now measure the days lag between Received Date and Published Date and see how many of these records you find: https://i.imgur.com/DBkASpE.jpg
They record whether or not you're vaccinated at, say, 9 a.m. every day. Or whatever.
Now if you get vaccinated at 10:00 a.m you're still not recorded as vaccinated.
And won't be until tomorrow.
But if you die today at say 5p.m. there'll be no tomorrow for you.
Right?
So you'll be recorded as dying 'unvaccinated'.
Right?
Well I wish you'd said so at the beginning and then provided the reasoning.
My apologies if I've got it all wrong.
And my request for a clear statement that is correct.
If I have it right then it reads like they interview and ask if you've had a vax and if you're dead they can't ask and you can't reply 'yes, yesterday'. So you remain as unvaxed, right?
But that's unlikely, surely. Records of vaxxed or not vaxxed would be make at the time of vaxing.
So what? They're consulting the records to assess your status and if 'deceased' they don't consult to the day of death, only to the day prior.
This maybe seeming sensible to a young programmer - what's the point of looking for a record on the day he's dead?
I can easily see myself setting search parameters on an SQL database, say to run from 'date of admission' to 'day of death minus one' and thinking myself very clever.
That could be hard coded into some stats package they all use.
Please inform: have I got it all wrong? If so, how is it to be understood.
And sorry about my lack of intellectual acumen. :)
p.s. the scenario I paint - or any really - would be checkable wouldn't it? Hospital records of vaccinations matched against records of deaths?
Just woke up so still groggy, but aren't they still counted as unvaxxed until 2 weeks after their (latest) jab?
Not in the ONS set. They go into the 1 dose <21 days column, exactly where there is immediate below-baseline mortality.
Aha. Which is why I led with "still groggy". I'll have to wait til I've finished breakfast (all the critters cared for 1st!) & 2nd coffee. I still can't follow the text or find purebloods in the tables...
Here are some examples of how the raw data looks when you exclude it to the young (where some of these weird effects are flipped) and to unvaxx vs just 1st dosed or 21 days after dose 1 or 2 https://unglossed.substack.com/p/into-the-weeds-uk-deaths-data
I thought people were counted as unvaxed until after 2 weeks too. Maybe that's just the United States, do you know if this is true in the US?
I think it was true in the Pfizer trial data, do you know if that's correct?
It sounds to me like you are filling in missing details in a knowledge framework where you suspect there is a problem, but aren't sure what it is.
Unfortunately, that's what a lot of people are doing, and that is problematic. It's one thing to say that the data doesn't have integrity. It's another to explain specifically how. That part is necessary for some purposes beyond holding skepticism.
Yeah. Going back over a link that Brian provided, I got that idea from Pfizer's trial press releases before the vaccine roll out.
RE the Pfizer trial, cases were tracked starting at Dose 1 and we’re published in 2020 in the trial paper, it’s the red dots in the abstract https://www.nejm.org/doi/full/10.1056/nejmoa2034577 - the Clinical Overview goes into more detail as far as efficacy for these periods - https://unglossed.substack.com/p/the-trial?s=w#footnote-5 - But then these aren’t included in the main, headline efficacy finding, but we know that that number was an illusion anyway because the juice wears off after ~4 months. But anyone could work out a window-free efficacy number for themselves using the abstract.
The UK has a loose definition set (UKHSA) and then a strict one (ONS, get a dose and you are 1st dose < 21 days). Stats in the US always vary by health department or dataset. They are all very unreliable. But some of the CDC studies, including the big Delta / Omicron study, took care to exclude the “partially” rather than call them unvaxxed https://unglossed.substack.com/p/means-etc?s=w#footnote-anchor-3 - But again this is using state health dept data that could be fudged or not have accurate vaxx status for everyone (and so “unvaxxed” = missing status, though again there are some CDC publications including the main dashboard that allege these are excluded too).
Importantly, whether the CDC results are accurate or fraudulent they show that you can put together a pro-vaxx graph without using the 14 day fudge. And so the existence of such graphs is not proof that the fudge, where it is employed, is making any difference to the stats. and once again that’s already solved by looking at the ONS data instead because there’s ostensibly no fudge, so the question is what else is going on.
Ah, okay, thank you Brian for this explanation. I see I got that idea from the Pfizer trial press releases. But as you and Matthew have pointed out in posts - God knows what's going on with the data. I have really learned that statistics can be made to show just about anything, especially when the raw data is hidden. But even then, it depends on vaxxed and vax free people being categorized correctly.
I just had one semester of stats in grad school.
Btw, that is so cool that the links you provided go right to the part of your post that I needed to read. (I think you did that on purpose). That is really advanced substacking. 👍🏼❤️
Shucks, beat me to it😎
😁 Someone below posted where I was headed. Bad Cattitude, bayesian datacrimes!
Of course there are shenanigans going on. Heck, they've never even proven that "regular" (pre-Covid) vaccines are effective in the long term. The whole thing is a giant myth birthed by the Great White Polio Panic of the 1940s and 50s (when they used to literally think black people were immune) combined with the WHO finally getting a win in the 70s with their smallpox program. When the WHO was founded, the two big issues were cholera and malaria, neither of which has ever shown any improvement whatsoever.
I have not yet had the chance to read on all those older topics well enough to have more than a superficial understanding. But I plan to.
Yeah — kids’ school registration for next year coming up, and I’m going to have to spend time this summer researching any shots that are supposed to happen. Not in a place where we can assume anything anymore.
Though with VAERS as my guide, effective or not I’d take any of those older shots over these things.
True, and if you look back to when vaccines began hitting the market, sanitation was getting better, so the number of disease cases were already coming down before the vaccines became available. The vaccines didn't improve the numbers, cleanliness did.
My microbiology profs said the same thing about clean water, sanitation and hygiene in the 70's. About all you can say is that vaccines probably had some effects on the margins.
Change "probably" to "possibly", and I'll agree with you.
On further thought I should have used possibly rather than probably
It's frustrating to know that Fauci and Kaiser and the CDC and the DoD have all the numbers you need, but they just don't want to share, and they won't share until the numbers don't matter anymore, and there is no group within the House of Representatives, or the Graveyard that is the Senate, that is working to make them share the numbers now. Ron Johnson is working alone, and appears to be a 'safety valve' to control pressure.
"shenanigans based on bucketing.." Yup there is a huge amount of mis-categorized AE's in VAERS! https://i.imgur.com/Kq9stpp.jpg and the throttling and the deleting. https://i.imgur.com/d3s996J.jpg
So, a same-day death theory would just be a narrower version of Fenton’s time lag theory as far as I understand the latter.
Both have a flaw, at least in the younger groups where Pfizer is used, in that same-day Dose 2 deaths should then dump into the Dose 1 <21 days column. And AEs seem to be higher on Dose 2 though there’s not good fidelity with then AE data. Either way it should auto-correct the Dose 1 <21 days group starting older than the current reversal.
You already saw my comment RE not-deathbed bias on Kirsch’s post. I still think that is sufficient to explain everything, right down to why the bias drops when age does. I have offered an explanation of the immortality effect and the dying straggler effect using an analogy with a room full of citizens going up to get Panera buzzers https://unglossed.substack.com/p/the-panera-kingdom-problem
This isn't just the time lag theory, which creates an artificial data matching.
If my guess is correct, we're talking about a protocol problem baked into an automated counting system that timestamps not continuously, but discretely.
It is possible that this problem has been noted in the past, and that the statistical sieve could be used to justify fraudulent trial data.
I still think, though perhaps as a result of incomprehension on my part, that that suggests the issue should recycle at Day 21 in groups that went for Pfizer, though not to the same degree as for a longer lag and not as much when a blend of brands was popular in an age group. So you could ask if this is instead driving dose 1 > 21 days deaths (as opposed to a straggler effect) due to longer between-dose intervals.
So whereas you focused on the older less noisy groups I would use the young as a more sensitive test of the theory. In the second version of my hack of the ONS spreadsheet, where dose 1 >21 days is highlighted, I would note the super-low absolute death counts. So despite the high rate (straggler effect) there’s not a ton of actual dying. Actually I could try throwing those back into the <21 column to see what happens. Meanwhile the rate is super low in the <21 days despite the fact that the young move the 2nd dose closer to dose 1 because Pfizer https://unglossed.substack.com/p/into-the-weeds-uk-deaths-data
Thank you Mathew. The DPDH hypothesis certainly may be a contributor. There must be something else going on, right? Only 16% of vaccine deaths occur within 24 hours (VAERS). The others will end up in one of the vaxxxxed buckets (mitigating the immortality effect) or be misclassified as a C19 death (driving down VE).
Yes, I think there is also a classification game going on. That's partially an R-code issue WRT ICD-10. But probably in other ways, too.
Did you attempt to calculate the potential size of the effect of this partial day mis-classification? Would it have such a big effect? Intuitively it feels like it would not have such a large impact, unless the vaccine is really killing a crapload of people within 12 hours of taking it.
No time. So many projects.
This was a "quick look" for me, and I wanted to share my thoughts.
But yes, it is killing a large portion quickly. The VAERS time curve is steep. Add that to the 2,000 deaths not counted into the stats, and the effect is substantial.
Thanks for the analysis. While I find the same day hypothesis interesting, for me a huge point here is the consistency of the 13% number year over year. IMO this is a deal breaker for VE considering UK had both very high uptake and high spread in 2020.
It reminds me of Gatos comparisons of Israel and Palestine, showing very similar outcomes over the past winter despite huge differences in vax rate. Now, we see the same effect happening in a region compared to it's 2020 self. I know many other such analyses have shown this too, but I find this one particularly compelling because of the consistency.
I live in the UK, I had 2x Astra Zennica,+ Pfizer booster,(Comirnaty,for all you US citizens who think that version is OK) VERY BAD effects,it took over half an hour to even list on the Yellow Card register.Your VAERS…There are endless boxes where you have to think of a word that describes your symptoms ( example: my description, prismatic effect on edges of vision of vision field) nothing! Etc etc eventually visual disturbances produced a drop down list….Anyone without a good command of medical language would have problems producing the numerous drop down boxes, if you can’t find anything you CANT MOVE ON with the filing 🤬🤯
I am lucky I am still here 6 months later 🤞🏻
Then regarding ONS Data, without a doubt the rules governing the filing of info is biased in every way to make the vaxed deaths look like unvaxed ,that is the same in almost every country….If I had died in the 2 weeks after the vax I would have been unvaxed..HEY PRESTO another STUPID UNVAXED PERSON BITES THE DUST.
THANK YOU MATHEW👏🏻👏🏻👏🏻
for showing us even more fixing of the figures ,and in such a numerous ways, but all of us readers are here becomes we know that…
In UK practically one third are not vaxed with these EUA products,the other 2/3 rds.had NO IDEA we were being lied to, we trusted our UK Gov ,our NHS.I was one of those and I am having extreme difficulty showing the others what is going on.
The PCR Case …FAKE. ONS Fig FAKE (Rigged)…TOTAL MEDIA CENSORSHIP IN UK.
THANK YOU AGAIN for giving me some more ammunition to fight this battle.🤗 😊
How do you heal? Soul, physiology, and informationally?
Have you tried the Macrophage Repolarisation Therapy proposed by Bruce Patterson (see yt: Spike in immune cells, by DrBeen medical). Or skirsch at io und Treatment, search for maraviroc.
I try to do it via TCM, found a PoT-Cov protocol in DE (search Covid tcm.edu ).
Then Intry to use the book „ Ploberger - Rezepturen aus westlichen Käutern für Syndrome der TCM“ to be able to pluck some herbs growing locally from the meadow.
I tried Grapeseed Extract (anti-CCR5), Artemisia Annua (anti-*, viral here) and Moringa (delaying metabolisation of artemisin in liver, like Ritonavir from Aids-Medication in Paxlov* from Pfi*, only plants are “evulutionary tested” - we grew up with them:)
But you have to combine several “cures” in parallel and in sequence, I added baking soda (5g/d in 1-2L water, a glass on empty stomach) and CDS with DMSO (detox protocol, gives me energy), also plant based: waltnut leaves ground to dust 1-3TS / d in something binding. An a lot from I-Recover by FLCCC like Zn, VitC, Black Cumine Oil, and add MCAS medication esp. montelukast as need gets bitter.
Of course the shots only did make things worse, much worse, but they also sped up degradation so horribly. We are now fighting a juvenilisation fight for immune system. Search for cheap tricks to get old. Like doing tarzan’s chest drum 20x in the morning. If you like cry tarzan’s call to it. This was from an old Austrian physio-therapist with “golden hands”. :) )
Thank you Andy for this helpful summary, I have bought DMSO and follow all of the experts you mention but there are a few other helpful suggestions for me to explore.I am also trying Wim Hof breathing, saunas and a 6/18 eat/fast regimen,( boost autophagy)👍after going deep into the history of big Pharma I will never have another vaccination of any sort again.I am not sure how my little dog or 84 year old neighbours will like a regular Tarzan routine 😂🤣I hope you have managed to cure yourself if you have also been vax damaged….🤗😊
Absolutely, and the "immortal time bias" (https://jasn.asnjournals.org/content/19/5/841.short) was pointed out (not by this name) by boriquagato in his "bayesian datacrimes" article (https://boriquagato.substack.com/p/bayesian-datacrime-defining-vaccine) and more memorably in "foxhole deaths" (https://boriquagato.substack.com/p/why-vaccinated-covid-deathshospitalizations).
This is whereI was headed in the wee hours. Bad Cattitude has been describing bayesian datacrimes -- & doing corrective statistical analysis -- for many months now!
Fraudulent RCTs and fraudulent data reporting from all agencies. I also suspect a mass psychosis of confirmation bias in all studies around VE.
Fascinating analysis. I like this hypothesis. I'm not sure you need a data sieve at the statistical level - just normal anchoring bias. After having been ascribed to COVID there would be no reason for the attending physician to consider assigning the death to the vax and it would go unreported as such. Here in the UK, much free PCR testing occurred, at drop-in stations and at places of work. Those who felt the need to attend a voluntary test and those whose employer made them do it would have been more likely to take up the offer of a shot.
Phew Mama, you are pretty amazing. I’d say the likelihood of shenanigans is pretty effing high.
Mathew, do you think they are seeing more deaths than they predicted, or less, given that some damn body really must have known what the heck this was going to do to the particular populations and there certainly had to be "a plan" from the very start.
I mean, this damn thing seems to have been in the works for a long time.
I don not believe we got here because of a "stumbling colossus."
that's a bingo! here is what's going on in the db code. each person has a datetime field for vaccine date and death date. In order to find the difference in time between these fields, you use a datediff operator in SQL
DATEDIFF ( datepart , vaccinedate , deathdate )
The datepart can be set to days, hours, minutes etc
Since everything in ONS is defined by "days" the programmer spec requirements would have used days. And days is defined as 24 hours between dates.
So if you get vaccinated and die less than 24 hours then no matter what you are in the unvaccinated bucket.
And here's the kicker.
What happens when they find your body dead the next day after vaccination?
Do they give you a time of death?
If they don't then guess what happens in the db when you don't input a time?
The time will automatically default to
midnight 00:00:00 for that date.
I'm sure they don't always know when you died so they just enter a date with no time.
So if you if you died on Jan 1 2022 and no time was entered then the database records it as
01/01/2022 00:00:00 (midnight)
"Published Date" will be difficult to compute unless you've been tabulating on your own as there is no data field in the downloads for published or "appeared" date...
Great observation, now measure the days lag between Received Date and Published Date and see how many of these records you find: https://i.imgur.com/DBkASpE.jpg
I can't follow all your technical talk.
I think you are saying this:
They record whether or not you're vaccinated at, say, 9 a.m. every day. Or whatever.
Now if you get vaccinated at 10:00 a.m you're still not recorded as vaccinated.
And won't be until tomorrow.
But if you die today at say 5p.m. there'll be no tomorrow for you.
Right?
So you'll be recorded as dying 'unvaccinated'.
Right?
Well I wish you'd said so at the beginning and then provided the reasoning.
My apologies if I've got it all wrong.
And my request for a clear statement that is correct.
If I have it right then it reads like they interview and ask if you've had a vax and if you're dead they can't ask and you can't reply 'yes, yesterday'. So you remain as unvaxed, right?
But that's unlikely, surely. Records of vaxxed or not vaxxed would be make at the time of vaxing.
So what? They're consulting the records to assess your status and if 'deceased' they don't consult to the day of death, only to the day prior.
This maybe seeming sensible to a young programmer - what's the point of looking for a record on the day he's dead?
I can easily see myself setting search parameters on an SQL database, say to run from 'date of admission' to 'day of death minus one' and thinking myself very clever.
That could be hard coded into some stats package they all use.
Please inform: have I got it all wrong? If so, how is it to be understood.
And sorry about my lack of intellectual acumen. :)
p.s. the scenario I paint - or any really - would be checkable wouldn't it? Hospital records of vaccinations matched against records of deaths?