Boosting was a time dependent covariate whose value changed from “non-boosted” to “boosted” 14 days after receipt of a vaccine booster,
Since many cases occur during the "two week worry window", the immune system issues caused by the booster in the first two weeks would cause an overcount in the "2 shot" cohort and an undercount in the "boosted" cohort.
Since omicron has enough mutations to evade natural immunity, everyone is going to get it. Those with original natural immunity seem to bounce back a lot faster based on my limited dataset.
This sounds like the most plausible explanation for that craziness. If we wait another 3 months, the "boosted" line will move above the zero-shot line. I still see no consistent explanation for that single shot line, though.
The single shot line is interesting. They provide no information on whether it's J&J or whether somebody quit after 1 shot. If they quit after 1 shot, it could just be a confounder due to vaccine injury and not getting out much. Or if the single shot was later in the trial when job mandates were taking place, it could be a shifting from 1-shot to unvaccinated if within the 2 week worry window.
I am in the "one shot" cohort. I got one dose of J&J and have no desire to get another dose of any of the covid vaccines available in the US. I did experience significant side effects after receiving my vaccine that lasted just over a week but that isn't why I haven' gotten another dose. I did further research into the vaccines and the covid data and decided that my personal risk profile doesn't warrant me risking vaccine harms at this point.
Also what if 'one shot' achieved some sort of sweet spot and it gave people some degree of protection without harming their innate immunity in the way additional doses may have?
A sweet spot is wishful thinking; if you look at Alberta data, it clearly shows lots of adverse events up to 20 days post, and its effects (ab titers and AEs) cool off for 4-6 months. The second jab is definitely more harmful, as should be 3rd, once the dust settles. And so on. This is the escalating harm, make no mistake, with the upper lethal bound. Let me know if you’d like links with substantiations, as I am not making this up as I go.
Some context, this is healthcare workers in Cleveland. No distinction is made between those who got infected prior to vaccinated vs. after vaccination.
Exactly, or "in between". Just spotted this pearl. "An individual was considered protected by natural immunity 14 days after testing positive for COVID-19 by a nucleic acid amplification test (NAAT)" , at any time since Oct. 2020. No symptoms required, so faulty PCR tests also count as „natural immunity“ - lovely! Also, if you get jabbed, then reinfected (broken through), you are considered "naturally immune". Or should you be considered toast at that point and not protected by anything? I would suggest the latter.
Then, 0 jabs for "naturally protected" in the "study" could be 0 jabs after the break-through infection, not truly "naturally immune" with 0 prior jabs? These people in Cleveland have sawdust instead of brains in their heads. Or am I all confused myself? Why wouldn't they spell out these little details?
Not sure who might be interested in this...seems significant, but I took a look today at my local newspapers obituary page, to check on the numbers of deaths....you select a duration of time to search it, and 'in the last 1 day, (37 died) 7 days (80 died), 14 days (131 died), 30 day(247 died), 6 months (1351 died) and 12 months (2640 died) .
What I noticed is that there are more deaths happening now, relatively speaking.
With the numbers for 7 days, 80 deaths, the year total would be 52*80 = 4160 deaths this coming year....See what I mean? Can someone repeat this obit exercise with their own town and see what you get?
Here's the obit site for my town paper....if you want to check me on it...
There is seasonality in deaths (more people die in winter), so the best way to look at this would be observing how many people died this week last year... Do they have year over year data? There will be some variations and adjustments needed (ie. For an aging population)
I also had the idea to datamine obits (I wanted to match it with the Alberta COVID death set before I realized they list deaths by date of covid diagnosis rather than date of death...).. So I would recommend automating the process if you are capable (ie., web scraping with Python) and keeping track of ages and causes of death when available. I think it may be an interesting canary in a coal mine in the long run
Thanks AO....very much..I didn't expect them to have it so kindly sorted by time increments.....perhaps they will forget to fudge up/hide these obituary numbers.? There COULD be another explaination, so I hope more folks contribute their local obit numbers for more data.
Funny but my comment became duplicated. So I deleted one and they are both gone. Those of you who got to read it are very lucky as it was a limited edition.
Simple. Joel Smalley has analysed these jab "categories" in the case of England. 1x-jabbed is the lowest as at least half of the adverse events, mis-characterized as Covid, have been transferred to the 0-jabbed. Some of the AEs 0-14 days post-jab must have been also mis-attributed from 2x- and 3x-jabbed to 0-jabbed as well, but mostly the AEs from 0-14 days post 3rd jab are mis-attributed to the 2x-jabbed, and some of the AEs from 14-days post 2nd jab may have been transferred to 1x-jabbed, but maybe mostly to the 0-jabbed. So, we are looking at garbage, mostly.
Yes, this confirms previous findings that many of us have been saying for a long time, but this study is the holy grail of studies, not just for this graph but for other things that are represented in the study. I am planning to write a longer post dissecting it, but thought a teaser would be nice. The authors did a great job of packing this graph of reinfections full of information. I don't think its garbage. I think it's a gift wrapped in a garbage bag ;)
Scratch that. Those "naturally protected" are an odd lot (my other comment). So are 1-,2-, and 3-jabbed, as they may have been "naturally infected" anywhere before, between, or after jabs. How do you deal with this mess?
Reading the report, it seems to go against everything I’ve heard everywhere else. I have seen data to suggest that boosters add a slight bit of protection for a very limited amount of time but that in the end it decreases immunity.
All I really need to know though is that I won’t be getting the shot. Ever.
I will bet 0.0005 BTC that the dataset is entirely synthetic, designed to continue the gEt Ur BoOsTer and pAnDemiC oF tHe UnVacCiNateD hype a little longer. I trust Stanford's Steve Gordon no further than I could kick this building.
If we take them at their word, this appears to be a major "oops" because it's only a matter of time before 3 doses becomes the new 2 doses. Likewise, those with 0 doses will presumably move to the bottom of the chart after second infection as this becomes the new "multiple exposures to different variants."
I say this because I am unable, using my wits, to challenge their data, but I still think, if we take the long view, this data shows that if you took 2 doses of the vaccine, you may be locked into the "flu shot paradox." (Prior vaccination makes you more likely to become ill, so it is advisable to get vaccinated again because there is no way to unvaccinate oneself.)
My guess is cohort-shifting.
Boosting was a time dependent covariate whose value changed from “non-boosted” to “boosted” 14 days after receipt of a vaccine booster,
Since many cases occur during the "two week worry window", the immune system issues caused by the booster in the first two weeks would cause an overcount in the "2 shot" cohort and an undercount in the "boosted" cohort.
Since omicron has enough mutations to evade natural immunity, everyone is going to get it. Those with original natural immunity seem to bounce back a lot faster based on my limited dataset.
This sounds like the most plausible explanation for that craziness. If we wait another 3 months, the "boosted" line will move above the zero-shot line. I still see no consistent explanation for that single shot line, though.
The single shot line is interesting. They provide no information on whether it's J&J or whether somebody quit after 1 shot. If they quit after 1 shot, it could just be a confounder due to vaccine injury and not getting out much. Or if the single shot was later in the trial when job mandates were taking place, it could be a shifting from 1-shot to unvaccinated if within the 2 week worry window.
I am in the "one shot" cohort. I got one dose of J&J and have no desire to get another dose of any of the covid vaccines available in the US. I did experience significant side effects after receiving my vaccine that lasted just over a week but that isn't why I haven' gotten another dose. I did further research into the vaccines and the covid data and decided that my personal risk profile doesn't warrant me risking vaccine harms at this point.
If you want to know what you were injected with, there is a great new analysis of J&J from "Doctors for Covid Ethics": https://doctors4covidethics.org/expert-report-on-the-johnson-johnson-covid-19-vaccine/
Also what if 'one shot' achieved some sort of sweet spot and it gave people some degree of protection without harming their innate immunity in the way additional doses may have?
A sweet spot is wishful thinking; if you look at Alberta data, it clearly shows lots of adverse events up to 20 days post, and its effects (ab titers and AEs) cool off for 4-6 months. The second jab is definitely more harmful, as should be 3rd, once the dust settles. And so on. This is the escalating harm, make no mistake, with the upper lethal bound. Let me know if you’d like links with substantiations, as I am not making this up as I go.
Some context, this is healthcare workers in Cleveland. No distinction is made between those who got infected prior to vaccinated vs. after vaccination.
Exactly, or "in between". Just spotted this pearl. "An individual was considered protected by natural immunity 14 days after testing positive for COVID-19 by a nucleic acid amplification test (NAAT)" , at any time since Oct. 2020. No symptoms required, so faulty PCR tests also count as „natural immunity“ - lovely! Also, if you get jabbed, then reinfected (broken through), you are considered "naturally immune". Or should you be considered toast at that point and not protected by anything? I would suggest the latter.
Then, 0 jabs for "naturally protected" in the "study" could be 0 jabs after the break-through infection, not truly "naturally immune" with 0 prior jabs? These people in Cleveland have sawdust instead of brains in their heads. Or am I all confused myself? Why wouldn't they spell out these little details?
Not sure who might be interested in this...seems significant, but I took a look today at my local newspapers obituary page, to check on the numbers of deaths....you select a duration of time to search it, and 'in the last 1 day, (37 died) 7 days (80 died), 14 days (131 died), 30 day(247 died), 6 months (1351 died) and 12 months (2640 died) .
What I noticed is that there are more deaths happening now, relatively speaking.
With the numbers for 7 days, 80 deaths, the year total would be 52*80 = 4160 deaths this coming year....See what I mean? Can someone repeat this obit exercise with their own town and see what you get?
Here's the obit site for my town paper....if you want to check me on it...
https://obits.oregonlive.com/us/obituaries/oregon/browse
There is seasonality in deaths (more people die in winter), so the best way to look at this would be observing how many people died this week last year... Do they have year over year data? There will be some variations and adjustments needed (ie. For an aging population)
I also had the idea to datamine obits (I wanted to match it with the Alberta COVID death set before I realized they list deaths by date of covid diagnosis rather than date of death...).. So I would recommend automating the process if you are capable (ie., web scraping with Python) and keeping track of ages and causes of death when available. I think it may be an interesting canary in a coal mine in the long run
Wow! That is some serious data mining! Brava!
Thanks AO....very much..I didn't expect them to have it so kindly sorted by time increments.....perhaps they will forget to fudge up/hide these obituary numbers.? There COULD be another explaination, so I hope more folks contribute their local obit numbers for more data.
That would be very interesting to see, great idea! Obit hunt!
maybe i will finally make a substack...just for this (thanks for the phrase) THE OBIT HUNT....
I worry that someone somewhere is going to try and RAT me at the front door.
Funny but my comment became duplicated. So I deleted one and they are both gone. Those of you who got to read it are very lucky as it was a limited edition.
that is a bug in the javascript code from substack. In such cases refresh the page instead of retyping or deleting.
Do you have an NFT of the OP? How much do you want for it?
Wait a moment and see the rats jumping ship.
Yes I did that early on in the "Pandemic". And found an old peoples home in Invercargill, NZ popping them out.
Simple. Joel Smalley has analysed these jab "categories" in the case of England. 1x-jabbed is the lowest as at least half of the adverse events, mis-characterized as Covid, have been transferred to the 0-jabbed. Some of the AEs 0-14 days post-jab must have been also mis-attributed from 2x- and 3x-jabbed to 0-jabbed as well, but mostly the AEs from 0-14 days post 3rd jab are mis-attributed to the 2x-jabbed, and some of the AEs from 14-days post 2nd jab may have been transferred to 1x-jabbed, but maybe mostly to the 0-jabbed. So, we are looking at garbage, mostly.
Yes, this confirms previous findings that many of us have been saying for a long time, but this study is the holy grail of studies, not just for this graph but for other things that are represented in the study. I am planning to write a longer post dissecting it, but thought a teaser would be nice. The authors did a great job of packing this graph of reinfections full of information. I don't think its garbage. I think it's a gift wrapped in a garbage bag ;)
Can’t wait!
Scratch that. Those "naturally protected" are an odd lot (my other comment). So are 1-,2-, and 3-jabbed, as they may have been "naturally infected" anywhere before, between, or after jabs. How do you deal with this mess?
Reading the report, it seems to go against everything I’ve heard everywhere else. I have seen data to suggest that boosters add a slight bit of protection for a very limited amount of time but that in the end it decreases immunity.
All I really need to know though is that I won’t be getting the shot. Ever.
Are they not comparing Delta immunity from prior infection and it’s effectiveness in preventing Omicron?
Guessing:
https://www.researchgate.net/publication/7322932_A_Note_on_Including_Time-dependent_Covariate_in_Regression_Model_for_Competing_Risks_Data
FTA: "inclusion of time-dependent covariates in this model can lead to serious bias"
I will bet 0.0005 BTC that the dataset is entirely synthetic, designed to continue the gEt Ur BoOsTer and pAnDemiC oF tHe UnVacCiNateD hype a little longer. I trust Stanford's Steve Gordon no further than I could kick this building.
Waning antibody ADE - https://nakedemperor.substack.com/p/pfizers-documented-antibody-dependent
If we take them at their word, this appears to be a major "oops" because it's only a matter of time before 3 doses becomes the new 2 doses. Likewise, those with 0 doses will presumably move to the bottom of the chart after second infection as this becomes the new "multiple exposures to different variants."
I say this because I am unable, using my wits, to challenge their data, but I still think, if we take the long view, this data shows that if you took 2 doses of the vaccine, you may be locked into the "flu shot paradox." (Prior vaccination makes you more likely to become ill, so it is advisable to get vaccinated again because there is no way to unvaccinate oneself.)
When did “free” testing start?