The more the skeptics police ourselves, the better. Everyone who is swallowing the narrative whole will pounce on every mote in our eyes as validation of the timber in theirs.
Peer review, when properly done, is always good. This type of honest scrutiny enhances the value of Mr Berenson’s work. Of course, it also highlights your integrity. Thanks!
"unvaxxed" cohort at this point seems to have reached 50-70% natural antibody prevalence, which might explain their convergence with the "vaxxed" rates.
Plausible, but a couple of possible problems with that hypothesis. First, that would be consistent with the unvaxxed rate declining, but not explain a rising rate among the vaxxed (which we clearly see)? Second, the case rate UK data (discussed in other posts) shows for the age groups at risk, cases are just (if not more) prevalent in the vaxxed as the unvaxxed. Therefore, both groups natural antibody prevalence should be increasing over time (that does not mean they have equal %'s, but we are looking at trends, so its the change over time we care about). I've only thought about this for the 4 min since you posted your comment, so please correct any errors in my thinking :)
All true. Do we have the historical case rates among the groups?
As I'm looking at the data myself, I think some of the gradient we see in the two groups is a data alignment problem. The initial "spike" in the unvaxxed looks like a symptom of unvaxed population # (the denominator) dropping rapidly at he time. When I shift the week alignment 4 weeks, the death rate for unvaxxed looks flat, albeit noisy from week to week.
Food for thought, if you split the 50-70% "unvaxxed with immunity" from the "unvaxxed" what does that do to your denominators for vulnerable "unvaxxed" mortality?
That would not be fair for the data in this post because we are looking at all-cause mortality. Those folks can be dying of lots of other things. Just removing them would be saying that COVID was their only possible cause of death.
Valid criticism. To note 21 vaxxed dead vs 17 placebo all cause mortality from Pfizer trial of 22K @ 6 mos (also broken by Berenson) supports this increase in all cause mortality however.
I have no idea how that Pfizer data is not a MAJOR story. However the 2:1 ratio Alex highlights seemed too big to believe and the age range too wide to not investigate further.
The major story is that vaccine efficacy on a clinically relevant endpoint (death) rather than the surrogate endpoint used in the trial (infection) is too small to be found even in an enormous trial.
The selection bias is that currently infected do not leave the unvaccinated and 1 dose +21 days pools. So when 1st doses roll out the denominator suddenly bleeds the uninfected while the numerator has to keep the infected; eventually, the fact that the pool is simultaneously getting younger and younger compensates. When the 2nd dose rolls out, same exact thing, the denominator bleeds the uninfected while the numerator has to keep the infected.
For 1st dose <21 days, the distortion has a lot more cross-currents since uninfected individuals are entering and leaving the pool at the same time.
The 1st dose +21 days group is also more complicated since it selects for infected but doesn't have a easily definable default vulnerability starting point (how big is the denominator, who is in it).
But overall, the two 1st Dose groups together start sort out the uninfected in mass numbers in April (while, again, progressively getting younger).
Sniffing out selection bias doesn't require statistics. What is it that "took" all the people healthy enough to get the 2nd dose "out" of the imaginary "1st dose + 21 days" pool? Getting the second dose. But in reality they are still also 21 days past their 1st dose, so it's not the +21 days that is causing a change, it is the exit of the healthier 2nd-dosed from the imaginary pool.
You and most who are sincerely questioning the narrative pushed by opinion pieces. A statistician who is good at explaining statistical concepts and applications and willing to use SARS-CoV-19/Covid data for demonstrating lessons would probably make a killing and become famous right now. I know I'd sign up if the cost was within my budget. I'M HOPING SOMEONE PERFECT FOR THE JOB READS THIS AND FILLS THE VOID!
Well, I should have edited it a bit since it was focused on the whole picture. For the 1st dose + 21 days there's selection bias not just for infections but for people with AEs or coincidental medical events that cause them to forgo the second dose.
I was told Z scores are unreliable compared to P scores, as a way of dismissing the EuroMOMO data. Having no idea what Z scores are I could not respond. What would you have said, Matt?
I agree. Really appreciate Alex but he needs someone to bounce these types of posts off of before he puts them out there. Looking at all of the tables included in the spreadsheet that was used for this chart, I noted in table 8 that there were 92,711 total deaths of the unvaxed and that 34,474, or 37%, of those deaths "involved COVID". Those totals tie to the weekly age-specific tables 3 and 4. Hard to believe that is correct. When you mate unvaxed weekly totals for COVID deaths and total deaths, more than 50% of the total deaths in England for weeks 2 and 3 "involved COVID". Really question these stats and interested in your thoughts.
Presumably you have seen the splendid work being done by retired UK NHS senior statistician, head of clinical audit at a busy NHS teaching hospital? [https://www.facebook.com/groups/johndeealmanac]
I think Johndeealmanac alone would be worth you getting an FB account. Just for him. I've no training in statistics at all and I absolutely love what he shares. If only I understood it all. But based on the responses of those that know much better than I, John Dee is the bomb and has the ability to show what kind of magic is possible and what kind of deception is going on. I do not believe he posts anywhere else.
See also Norman Fenton: I think he makes more sense of all the complex artefacts and variables than anyone else : and his stuff is understandable, which helps a poor soul like me:
Thanks for pointing this out. Hopefully they will continue collecting the data. It would be more useful if the age range were broken up into decades, although it still wouldn't beat actually maintaining a control group in a clinical trial. I guess that ship has sailed.
The more the skeptics police ourselves, the better. Everyone who is swallowing the narrative whole will pounce on every mote in our eyes as validation of the timber in theirs.
Alex has not been invaluable.
Alex IS invaluable.
Agreed. Hope no one thought I was implying otherwise. I'm a data guy my trade, not a writer, so forgive me 😄
Of course! And many many thanks for your work!!!!
Peer review, when properly done, is always good. This type of honest scrutiny enhances the value of Mr Berenson’s work. Of course, it also highlights your integrity. Thanks!
"unvaxxed" cohort at this point seems to have reached 50-70% natural antibody prevalence, which might explain their convergence with the "vaxxed" rates.
Plausible, but a couple of possible problems with that hypothesis. First, that would be consistent with the unvaxxed rate declining, but not explain a rising rate among the vaxxed (which we clearly see)? Second, the case rate UK data (discussed in other posts) shows for the age groups at risk, cases are just (if not more) prevalent in the vaxxed as the unvaxxed. Therefore, both groups natural antibody prevalence should be increasing over time (that does not mean they have equal %'s, but we are looking at trends, so its the change over time we care about). I've only thought about this for the 4 min since you posted your comment, so please correct any errors in my thinking :)
All true. Do we have the historical case rates among the groups?
As I'm looking at the data myself, I think some of the gradient we see in the two groups is a data alignment problem. The initial "spike" in the unvaxxed looks like a symptom of unvaxed population # (the denominator) dropping rapidly at he time. When I shift the week alignment 4 weeks, the death rate for unvaxxed looks flat, albeit noisy from week to week.
Food for thought, if you split the 50-70% "unvaxxed with immunity" from the "unvaxxed" what does that do to your denominators for vulnerable "unvaxxed" mortality?
That would not be fair for the data in this post because we are looking at all-cause mortality. Those folks can be dying of lots of other things. Just removing them would be saying that COVID was their only possible cause of death.
Take a look here - https://roundingtheearth.substack.com/p/uk-data-shows-no-all-cause-mortality? for another analysis.
Valid criticism. To note 21 vaxxed dead vs 17 placebo all cause mortality from Pfizer trial of 22K @ 6 mos (also broken by Berenson) supports this increase in all cause mortality however.
I have no idea how that Pfizer data is not a MAJOR story. However the 2:1 ratio Alex highlights seemed too big to believe and the age range too wide to not investigate further.
The major story is that vaccine efficacy on a clinically relevant endpoint (death) rather than the surrogate endpoint used in the trial (infection) is too small to be found even in an enormous trial.
The dose timing mortality "mystery" was also covered at https://boriquagato.substack.com/p/all-cause-deaths-and-vaccination - same response I posted there:
The selection bias is that currently infected do not leave the unvaccinated and 1 dose +21 days pools. So when 1st doses roll out the denominator suddenly bleeds the uninfected while the numerator has to keep the infected; eventually, the fact that the pool is simultaneously getting younger and younger compensates. When the 2nd dose rolls out, same exact thing, the denominator bleeds the uninfected while the numerator has to keep the infected.
For 1st dose <21 days, the distortion has a lot more cross-currents since uninfected individuals are entering and leaving the pool at the same time.
The 1st dose +21 days group is also more complicated since it selects for infected but doesn't have a easily definable default vulnerability starting point (how big is the denominator, who is in it).
But overall, the two 1st Dose groups together start sort out the uninfected in mass numbers in April (while, again, progressively getting younger).
I think I'm going to need a statistics course to understand everything that is happening. Damn it.
Sniffing out selection bias doesn't require statistics. What is it that "took" all the people healthy enough to get the 2nd dose "out" of the imaginary "1st dose + 21 days" pool? Getting the second dose. But in reality they are still also 21 days past their 1st dose, so it's not the +21 days that is causing a change, it is the exit of the healthier 2nd-dosed from the imaginary pool.
You and most who are sincerely questioning the narrative pushed by opinion pieces. A statistician who is good at explaining statistical concepts and applications and willing to use SARS-CoV-19/Covid data for demonstrating lessons would probably make a killing and become famous right now. I know I'd sign up if the cost was within my budget. I'M HOPING SOMEONE PERFECT FOR THE JOB READS THIS AND FILLS THE VOID!
Well, I should have edited it a bit since it was focused on the whole picture. For the 1st dose + 21 days there's selection bias not just for infections but for people with AEs or coincidental medical events that cause them to forgo the second dose.
Look at England's Euromomo z scores in the age 10-44. Well above base. There is a signal.
I was told Z scores are unreliable compared to P scores, as a way of dismissing the EuroMOMO data. Having no idea what Z scores are I could not respond. What would you have said, Matt?
Thanks for pointing this out, and thanks as well for the careful framing. You did both with great clarity.
I agree. Really appreciate Alex but he needs someone to bounce these types of posts off of before he puts them out there. Looking at all of the tables included in the spreadsheet that was used for this chart, I noted in table 8 that there were 92,711 total deaths of the unvaxed and that 34,474, or 37%, of those deaths "involved COVID". Those totals tie to the weekly age-specific tables 3 and 4. Hard to believe that is correct. When you mate unvaxed weekly totals for COVID deaths and total deaths, more than 50% of the total deaths in England for weeks 2 and 3 "involved COVID". Really question these stats and interested in your thoughts.
That definitely sounds fishy. I'll try to dig in tomorrow.
You can also watch Norman Fenton’s work in his YouTube video https://www.youtube.com/watch?v=6umArFc-fdc&t=2s
Thanks for the link.
Indeed Prof Fenton is doing excellent work!
Presumably you have seen the splendid work being done by retired UK NHS senior statistician, head of clinical audit at a busy NHS teaching hospital? [https://www.facebook.com/groups/johndeealmanac]
To date I have proudly abstained from having a Facebook account :) . Is there an alternative way for me to review?
I think Johndeealmanac alone would be worth you getting an FB account. Just for him. I've no training in statistics at all and I absolutely love what he shares. If only I understood it all. But based on the responses of those that know much better than I, John Dee is the bomb and has the ability to show what kind of magic is possible and what kind of deception is going on. I do not believe he posts anywhere else.
John Dee posts on Telegram.
thank you!
See also Norman Fenton: I think he makes more sense of all the complex artefacts and variables than anyone else : and his stuff is understandable, which helps a poor soul like me:
https://rumble.com/vqbtjd-prof-norman-fenton-explaining-ons-vaccine-data-anomalies.html
Absolutely right to call attention to discrepancies .... the less ammo the better for the cultists! Hats off to you and AB.
Thanks for pointing this out. Hopefully they will continue collecting the data. It would be more useful if the age range were broken up into decades, although it still wouldn't beat actually maintaining a control group in a clinical trial. I guess that ship has sailed.
Excellent journalism!