In this series I use survival analysis techniques to investigate delays between vaccination and death for 5,039 cases over the period 2020/w53 – 2021/w36 using data from an undisclosed NHS Trust
No idea. They might look the same or they might not; all we can do is cogitate over differences with a coffee since we don't have a control group. This is why I shall be pooling doses and using LDS in the forthcoming articles revealing Cox Regression results. What will distort results are folk who decided against a second dose being lumped in with those who didn't have a chance for a second dose.
If you ever write a book I am buying it on pre order and extra copies for clients, family and friends. For two reasons, the substance, that more tickles my fancy, and also the story telling. If you can’t following along, be horrified and have a laugh at the same time, you need to seek a deprogramming expert.
Well from what I can tell people died with U07.1 around 8-15 days after dose 1 on average, depending on age group. This is shortly before they'd receive dose 2, but correlations with dose 2 were much weaker.
Maybe I am overinterpreting things.
I just wrote a scraper that I am using to build a dataset representing hospitalizations occurring in Germany between 2019-2023. So far am seeing my interpretation/hypothesis confirmed: Patients with a clinical complexity level of zero started dying of U07.1 in January 2021, but only the 18+ crowd. For children it's happening later. There are 16 age groups total.
However, non-U07.1 mortality was the much bigger issue in Germany, which also well-reflected in PCCL=0 patients dying in excess, beginning in in early 2021.
Btw I would share this dataset with you if you are interested. It really tells the whole story.
Thanks, but while it seems ambitious, the core of scraping and combinatorics was coded in a few hours. The scraping is open-ended. The dataset will just gain detail. At the current speed, getting daily data with location information would take 10 years, running only one session. Eradicate age-stratification and each full scrape of monthly national resolution would be reduced to a couple of hours.
I suppose I have a very unusual background. Coding bots is the skillset that I built my data analysis skills on top of. So why not use those strengths, since nobody seems to be doing it. It's just such an amazing data source.
Visualizing over 40k codes * (16+1) age groups will be much more challenging. Or maybe I should cluster codes into groups of codes, based on patterns in their occurrence over time and across age group? This should highlight all the vaccine related issues. Cardiac diagnostic procedures are really striking. It seems it's only a minor mortality factor, but there are so many cardiac signals in 2021, it's crazy.
There's just so much that can be done. The fully processed dataset is 5GB in size right now, packed with signals and really strange trends, some of which are due to coding, others representing clear vaccine plandemic-/vaccine-related patterns.
Downloading 2GB per day to feed the combinatorics script. 🙂🥳
Thank you. My bleary 2024 eyes (Happy New Year) seem to see the Dose 2 slope become steeper around day 10. (Squinting reveals an initial rate (slope) for 7 days, a slow down for 3, then a change to a much steeper rate around day 10.) I acknowledge mitts must be used when handling hot bakes, and face kept away from the steam, but it does leave me curious whether there might be procedural or reporting artifacts, biological processes, or something else to lend an appearance of a quickening dose 2 die off after the first 10 days. (I assume report date eggs were beaten into death dates prior to mix, so perhaps something else.)
Biological and patient management processes may well be at play but since these delays are based on actual dates of death then it can't be a reporting issue.
Yes. If we count folk who died within 24 hours of their last dose then we find 11/2235 (0.49%) for dose 1 and 9/2804 (0.32%) for dose 2. If this doesn't shock people I don't know what will.
Yes. That is a real shocker, and I'm seriously questioning the sanity of those staff involved in jabbing people who, I can only assume, were by and large, clinging onto life by their fingernails. (I mean, we know a few healthy younger folk perished, but if 0.5% of them did then there would have been a revolution).
Their sanity then, and their sanity now - one would genuinely expect to see staff welfare services overwhelmed by nurses etc in tears....and whistleblowing like crazy.
The whole thing is very surreal since I cannot imagine any of my former clinical-side colleagues jabbing willy-nilly or, indeed, adhering to any crack-pot protocol just because management said so.
“ If somebody accidentally found an answer then the trick was to keep it from spreading, and especially ‘upwards’, with the final ring of upper guardians being the departmental assistant secretaries who ensured ministers never got to hear anything that would compromise their “well, we just don’t know” ploy. The uninformed minister is a powerful weapon. “
Yes Minister! Been looking at that series again! Masterwork, and accurate as to governments from days long ago to the present ones. Happy New Year John Dee!
I started out 18 months ago assuming that vaccines were the primary cause of excess deaths, but now I'm not so sure any more. The reason is that International comparisons are really not that clear: this doesn't mean that the vaccine is safe, merely that it is not the primary cause of excess deaths: else why are Denmark, Switzerland and Belgium so little affected?
"The death rate of 8.6 per cent above the expected amount for the year significantly outpaced Israel, the next worst country, with 5.5 per cent.
Excess deaths in Britain were around four times higher than Germany’s 2.2 per cent. New Zealand had 1.4 per cent more deaths than normal, while France had 1.7 per cent fewer than expected, a separate Telegraph analysis of the World Mortality Dataset revealed.
Data for Australia and the United States was only available up until mid-August, when excess deaths were at 8.4 per cent and 1.4 per cent, respectively. The UK’s figure at that time was 9.0 per cent."
I don't trust 'Apocalypse Now' vendors - on either side. But I remain open minded, of course. I think that the NHS itself has taken a huge battering, with waiting lists soaring, ambulances in chaos, and denial of access to primary and secondary care at a high point: hence all those excess deaths at home , maybe?
A lame idea: Perhaps some subgroup of deaths could be identified as having been in the hospital at least 7 days. Not sure if any specific diagnostic codes allows for that inference.. But if it were possible, you could infer that those who were vaccinated within the last one week must have been vaccinated in the hospital. And then do some kind of analysis on them.
Looking at practice level data needle-to-death by cause of death, my focus is drawn to sudden deaths including witnessed cardiac arrests <28d (of any jab) and most of these people don't reach hospital so wouldn't feature in hospital data. Most in 70s/80s so though unexpected in that there was no warning, not unexpected in terms of age and risk factors. I don't see the same signal with other causes of death, only with sudden /circulatory/presumed cardiac. However it is a small sample size and I have no idea if it is statistically significant. I wish someone would do this sort of analysis with primary care data, but with this you can't really rely on coding being accurate so do have to look at the case records.
Yes indeed, I'm only seeing it from the secondary/tertiary end and thus the tip of the iceberg. I do not have access to primary care records I'm afraid. As you will see in part 2 AMI features strongly and I'll be pursuing this in part 3. Asymptomatic COVID (non-respiratory) is also a feature, and this could well be pointing to cardiac issues.
I look forward to reading the next episode. Ours isn't a large population - just over 2000 over 55y olds, and only small numbers of sudden deaths annually (23 in the 3y pre Covid, more in the 4y post Covid) . Would probably need to pool efforts with other practices to see if anything more to this, as I may be barking up the wrong tree entirely. Also as we have no idea about Covid infection status at the time of death that is a major gap in the data. eg theoretically as vaccination can render a person more susceptible to Covid due to transient lymphopoenia, vaccination-infection could be the risk.
What shape would these graphs look like if death was totally independent of the jabs?
No idea. They might look the same or they might not; all we can do is cogitate over differences with a coffee since we don't have a control group. This is why I shall be pooling doses and using LDS in the forthcoming articles revealing Cox Regression results. What will distort results are folk who decided against a second dose being lumped in with those who didn't have a chance for a second dose.
And isn’t asbestos perfectly safe as long as it is NEVER disturbed, drilled into, broken etc.?
That's the theory. We'd find bits of crumbling roof panel on the floor every now and then.
Is this similar to Steve Kirsch’s cohort time-series analysis on the controversial NZH data?
No idea - I haven't been following Steve's work for a while now!
https://openvaet.substack.com/p/the-new-zealand-whistleblower-data
This article discredits the data... I lack the skills and time to assess it.
Sorry, I meant to include a link to his original article.
https://open.substack.com/pub/stevekirsch/p/its-time-for-criminal-charges-to?r=peo1w&utm_medium=ios&utm_campaign=post
Cheers - I'll try and find time later this week to have a squint at what he's been up to!
If you ever write a book I am buying it on pre order and extra copies for clients, family and friends. For two reasons, the substance, that more tickles my fancy, and also the story telling. If you can’t following along, be horrified and have a laugh at the same time, you need to seek a deprogramming expert.
Maybe one day. The trick will be avoiding litigation!
I have always thought this low dose (lower than is often assumed to be toxic and it maybe cumulative) toxicity effect is at play not just with conventional endocrine disruptors but also vaccinations in general nevermind the as yet unknowns (this substack is highlighting they are present) the current gene therapy injections. https://endocrinesciencematters.org/non-monotonic-dose-responses-2/non-monotonic-dose-responses-technical-overview/
Very nice.
I found the exact same thing in the us data. Is a short-term effect of dose 1.
A large share is due to early infections causing VMED/VAED.
Aha! Sometimes I run these analyses and wonder if I'm too left-field. Nice to have confirmation - thanks.
Well from what I can tell people died with U07.1 around 8-15 days after dose 1 on average, depending on age group. This is shortly before they'd receive dose 2, but correlations with dose 2 were much weaker.
Maybe I am overinterpreting things.
I just wrote a scraper that I am using to build a dataset representing hospitalizations occurring in Germany between 2019-2023. So far am seeing my interpretation/hypothesis confirmed: Patients with a clinical complexity level of zero started dying of U07.1 in January 2021, but only the 18+ crowd. For children it's happening later. There are 16 age groups total.
However, non-U07.1 mortality was the much bigger issue in Germany, which also well-reflected in PCCL=0 patients dying in excess, beginning in in early 2021.
Btw I would share this dataset with you if you are interested. It really tells the whole story.
That's some serious work you've got there! Thanks for the kind offer but I'm trying to keep a tight rein on my research otherwise I have no life :-)
Thanks, but while it seems ambitious, the core of scraping and combinatorics was coded in a few hours. The scraping is open-ended. The dataset will just gain detail. At the current speed, getting daily data with location information would take 10 years, running only one session. Eradicate age-stratification and each full scrape of monthly national resolution would be reduced to a couple of hours.
I suppose I have a very unusual background. Coding bots is the skillset that I built my data analysis skills on top of. So why not use those strengths, since nobody seems to be doing it. It's just such an amazing data source.
Visualizing over 40k codes * (16+1) age groups will be much more challenging. Or maybe I should cluster codes into groups of codes, based on patterns in their occurrence over time and across age group? This should highlight all the vaccine related issues. Cardiac diagnostic procedures are really striking. It seems it's only a minor mortality factor, but there are so many cardiac signals in 2021, it's crazy.
There's just so much that can be done. The fully processed dataset is 5GB in size right now, packed with signals and really strange trends, some of which are due to coding, others representing clear vaccine plandemic-/vaccine-related patterns.
Downloading 2GB per day to feed the combinatorics script. 🙂🥳
The exact man for the job - fabulous work!
Hehe thank you
Dear god.
Thank you. My bleary 2024 eyes (Happy New Year) seem to see the Dose 2 slope become steeper around day 10. (Squinting reveals an initial rate (slope) for 7 days, a slow down for 3, then a change to a much steeper rate around day 10.) I acknowledge mitts must be used when handling hot bakes, and face kept away from the steam, but it does leave me curious whether there might be procedural or reporting artifacts, biological processes, or something else to lend an appearance of a quickening dose 2 die off after the first 10 days. (I assume report date eggs were beaten into death dates prior to mix, so perhaps something else.)
Biological and patient management processes may well be at play but since these delays are based on actual dates of death then it can't be a reporting issue.
Did anyone die the day of their second dose?
Yes. If we count folk who died within 24 hours of their last dose then we find 11/2235 (0.49%) for dose 1 and 9/2804 (0.32%) for dose 2. If this doesn't shock people I don't know what will.
Yes. That is a real shocker, and I'm seriously questioning the sanity of those staff involved in jabbing people who, I can only assume, were by and large, clinging onto life by their fingernails. (I mean, we know a few healthy younger folk perished, but if 0.5% of them did then there would have been a revolution).
Their sanity then, and their sanity now - one would genuinely expect to see staff welfare services overwhelmed by nurses etc in tears....and whistleblowing like crazy.
The whole thing is very surreal since I cannot imagine any of my former clinical-side colleagues jabbing willy-nilly or, indeed, adhering to any crack-pot protocol just because management said so.
“ If somebody accidentally found an answer then the trick was to keep it from spreading, and especially ‘upwards’, with the final ring of upper guardians being the departmental assistant secretaries who ensured ministers never got to hear anything that would compromise their “well, we just don’t know” ploy. The uninformed minister is a powerful weapon. “
Yes Minister! Been looking at that series again! Masterwork, and accurate as to governments from days long ago to the present ones. Happy New Year John Dee!
That series was like looking into a mirror - marvellous stuff!
I've been looking at the Telegraph https://www.telegraph.co.uk/news/2024/01/01/nhs-strikes-fuel-record-number-excess-deaths/?li_source=LI&li_medium=for_you today.
I started out 18 months ago assuming that vaccines were the primary cause of excess deaths, but now I'm not so sure any more. The reason is that International comparisons are really not that clear: this doesn't mean that the vaccine is safe, merely that it is not the primary cause of excess deaths: else why are Denmark, Switzerland and Belgium so little affected?
"The death rate of 8.6 per cent above the expected amount for the year significantly outpaced Israel, the next worst country, with 5.5 per cent.
Excess deaths in Britain were around four times higher than Germany’s 2.2 per cent. New Zealand had 1.4 per cent more deaths than normal, while France had 1.7 per cent fewer than expected, a separate Telegraph analysis of the World Mortality Dataset revealed.
Data for Australia and the United States was only available up until mid-August, when excess deaths were at 8.4 per cent and 1.4 per cent, respectively. The UK’s figure at that time was 9.0 per cent."
Yes indeed, it's not clear to me either. My money is on the elixir being a major factor but not necessarily the sole cause.
I don't trust 'Apocalypse Now' vendors - on either side. But I remain open minded, of course. I think that the NHS itself has taken a huge battering, with waiting lists soaring, ambulances in chaos, and denial of access to primary and secondary care at a high point: hence all those excess deaths at home , maybe?
Place of death is something I've got jotted down in my big black book.
Yes: we haven't made much of it to date, but actually it is a stonking great clue. Like the dog that didn't bark in the night, dear Holmes!
I keep forgetting what data is available. Is it possible to do needle-to-admitted time?
I'm afraid not - the dump was quite Spartan.
A lame idea: Perhaps some subgroup of deaths could be identified as having been in the hospital at least 7 days. Not sure if any specific diagnostic codes allows for that inference.. But if it were possible, you could infer that those who were vaccinated within the last one week must have been vaccinated in the hospital. And then do some kind of analysis on them.
Been scratching my head on that but no joy so far!
Looking at practice level data needle-to-death by cause of death, my focus is drawn to sudden deaths including witnessed cardiac arrests <28d (of any jab) and most of these people don't reach hospital so wouldn't feature in hospital data. Most in 70s/80s so though unexpected in that there was no warning, not unexpected in terms of age and risk factors. I don't see the same signal with other causes of death, only with sudden /circulatory/presumed cardiac. However it is a small sample size and I have no idea if it is statistically significant. I wish someone would do this sort of analysis with primary care data, but with this you can't really rely on coding being accurate so do have to look at the case records.
Yes indeed, I'm only seeing it from the secondary/tertiary end and thus the tip of the iceberg. I do not have access to primary care records I'm afraid. As you will see in part 2 AMI features strongly and I'll be pursuing this in part 3. Asymptomatic COVID (non-respiratory) is also a feature, and this could well be pointing to cardiac issues.
I look forward to reading the next episode. Ours isn't a large population - just over 2000 over 55y olds, and only small numbers of sudden deaths annually (23 in the 3y pre Covid, more in the 4y post Covid) . Would probably need to pool efforts with other practices to see if anything more to this, as I may be barking up the wrong tree entirely. Also as we have no idea about Covid infection status at the time of death that is a major gap in the data. eg theoretically as vaccination can render a person more susceptible to Covid due to transient lymphopoenia, vaccination-infection could be the risk.