1. I think @Bronwyn_Meikle 's all cause mortality rates per 100k are wrongly calculated - I suspect she has not adjusted the respective population denominator totals to reflect the shifting totals caused by the booster rollout. (I am waiting for her to reply to my DM)
2. IMO mortality rates by vaccination status not adjusted for age is simply not a meaningful metric. (see my other comment below)
3. As a large part of your post is based on a supposed correlation between the booster rollout and an inflection in the vaxxed:unvaxxed all cause deaths ratio, I think you really need to clarify the data for those rates you are basing your correlation on.
4. IF there is a significant shift in the ratio of vaxxed:unvaxxed deaths in Q1 2022, it is important to note it would also correlate with the rise of Omicron BA.2 to dominance in NZ.
You're welcome to produce your own work and compare, fully vaxed and boosted are all over-representing over time in 2022, I've been doing graphs last year and this is similar to the covid deaths results, just this time the data comes from the horse's mouth
You have time to tell others it's useless, use your time to present your work for people to critic then, Stats NZ and MOH, wayback machine have all the info available
and yes, Omicron arrived early 2022 in NZ, & they're clearly not mainly after the vax-free.
I think both sides have points so I pinned Witzbold comments. I don’t believe in silencing the other side’s arguments as long as they are not condescending, ad hominem attacks…etc
Let’s wait for the dust to settle - including corrections and further analysis etc. @brownyn_meikle also mentioned they will publish the data shortly in stats nz so lets wait for that too.
You're guessing based on the MOH graph aren't you? Not sure why the other of your analysis was deleted when replying
You are doing cumulative for the older population which means you're not presenting younger populations, and you are not presenting trends either.
With actual numbers available on government sites - boosted are over-represented and unvaxed are under-represented in the population.
Deaths with covid proportion -
Boosted 2810/3864=72.7%
2-dosed 564/3864=14.6%
Unvaxed 490/3864=12.7%
Population (June 2021 population - before vaccine mass rollout, which is an advantage for vaxed/boosted)
Boosted 2,752,564/5111300=53.9%
2-dosed 3,983,917+155,730-2,752,564/5111300=27.1%
Unvaxed (5111300-4,030,928-269,936)/5111300=15.9%
So numbers are already ugly for the boosted, and if your calculation using population and deaths ratio which is a very weird way of doing it (try adjust to 100K then calculate protection % using Pfizer's tech?), showing slight benefit for oldies, but boosted overall number is so over-represented, that means the numbers would be WORSE for the younger boosted population, that's the paradox you have, make oldies look good, it'd mean younger ones would be slaughtered, make oldies less good, it'd be just crap across the whole age groups, because the overall data just looks crap.
There are also kiwis who have been keeping actual numbers and trends throughout 2022, the summary looks like this - a blow up since every month for the boosted respective age groups per 100K.
But you don't have those data because he's guessing the cumulative MOH vax graph probably because MOH don't show previous stats unless you use waybackmachine or keep an excel profile since last year like my friends did
I’m not sure why you have reacted to my comments as you have - it feels kind of agro. I am not a pharma shill and I am neither pro nor anti-vax. I am very skeptical and concerned about the Covid-19 so-called vaccines and similarly about the so-called pandemic. My Substack focuses primarily on German data and I am not trying to step on any Kiwi toes.
My comments have explicitly been responses to the NZ data which @Aussie17 has presented in his post and tweets including that from @Bronwyn_Meikle. And that’s also why I used the cumulative totals in my back of the envelope calculations, it is the data in his graphic!
As far as I am concerned, Bronwyn’s rates per 100k simply cannot be right because the population denominator she has used do not seem to reflect the booster rollout and the boosted population at the time. Consider the following figures from her tweet:
Jan 1st ‘22: boosted deaths = 651; Bronwyn’s rate = 25/100k => Boosted population = 2,604,00
Feb 1st ’22: boosted deaths = 1,311; Bronwyn’s rate = 51/100k => Boosted population = 2,570,588
Mar 1st ’22: boosted deaths = 2,076; Bronwyn’s rate = 81/100k => Boosted population = 2,562,962
We are in agreement that cohort rates per 100k are optimal for determining vaccine effectiveness and also for showing trends. For my weird way of calculating effectiveness I used the odds ratio instead of the risk ratio. Using rates per 100k is ideal (as that equates to a risk ratio) but I disputed Bronwyn’s rates and the subpopulation denominators were constantly changing in 2022 so I just used the data at hand for my approximate calculations. I wasn’t trying to defend vaccine effectiveness, rather to point out the data was likely not as bad as Aussie17 was suggesting. In hindsight I should have been clearer that what I was doing with the odds ratio instead of risk ratio was an approximation and actual effectiveness would be somewhat lower.
Finally, because your reply to me is full of examples using overall population totals by vax status, I really think you should consider Simpson’s Paradox. In a nutshell: if an effect or trend is disproportionately found in a subsection of a population, then it may disappear or be reversed in overall population-level data, ie. IMO because Covid-associated deaths are disproportionately age stratified, it is important to always compare age groups and not overall populations.
You say "IMO because Covid-associated deaths are disproportionately age stratified". I don't think the age stratification is sufficient to call it disproportionate. Google Dennis Rancourt's analyses of excess mortality.
Over 90% of Covid-associated deaths in NZ occur in the over 60's population. And around half of All-Cause deaths in NZ occur in over 80's! If you don't see that as disproportionate, I don't know what to say.
I don't see that Simpson's Paradox applies. I don't see an indication of the prerequisite trend that 'disappears or reverses when the groups are combined'. The trend is in the group and in the parts.
Not to mention when you adjust for age, location, and behavior that effect vanishes. Isn't it so strange that the amateur sluths using highly-confounded population data (which no scientist uses to answer clinical questions) finds spurious correlations that run counter to all clinical research. How weird that when we perform an RCT or controlled prospective (or retrospective) study this effect vanishes completely? Hmm I wonder theoretically what it is about the nearly-identical booster that makes it a 'kill shot'. Here's a tip to the scientific illiterate: population-level data is so confounded you can find whatever you want depending on how you slice it, and since no one bothers to control for anything all the better to push really bad takes.
The question is then why authorities haven't tried to conduct more rigours studies and analysis to remove the confounders and confusion to produce reliable data???
As to the third shot. Do some reading about Moderna and Biontech's pasts and why they never successfully peviously brought an mRNA product to market.
They have. It's called clinical research. Why use satellite imagery to determine why people leave their homes when you can just go ask why they are leaving. No one uses this type of data to determine clinical questions; but it is fertile ground for amateurs to cherry-pick and drive the ignorant to their newsletters by making mountains out of specious correlations and unnuanced numbers.
Let me guess, it's a conspiracy theory, right? I know when you guys can't deal with the overwhelming evidence against your position you have to deny it all and jump straight to the conspiracies, but does the answer to your question also apply to the future mRNA vaccines coming out (Flu, RSA, Zika, Cancer)? And China's mRNA's about to come out? How about the 10 other companies working on mRNA right now? Does it apply to Nutcracker, Deep Genomics, Siraomics, Laronde, Abrogen, Arrowhead, Dicerna, Locanabio, ProQR, Shape and Stroke too? Ah yes. The GLOBAL conspiracy I'm sure.
Either way: control for age, behavior, and location and the effect in this article goes away. I wonder: back in 2021 when this same data showed vaccines had a HUGE protective effect, did you all believe it then? Well at least we can all agree back in 2021 vaccines were saving lives based on this EXACT same data 1.5 years ago. Kumbaya!
Why do you think the same population data shows differences between 2021 and 2022. Do you recognise that imperfect, confounded data can still reveal true trends and shifting effectiveness?
Of course it can (still not sure why you're using population data and not clinical data), but at least we we can all agree back in 2021 this SAME data showed the vaccine saving lives.
Please link the RCTs showing vax effectiveness against death and hospitalisation. I only know of RCTs with symptomatic infection as end point. As far as I know, all others are observational studies. Thanks.
Once the vaccine is deemed effective (the primary endpoint of the original RCT was for symptomatic covid) then it is unethical to take something that is highly protective and deny it to a control group. The RCTs you seek can't ethically be run any longer, especially now we have all sorts of other evidence that it is protective against death and hospitalization. Here are 54 studies (just a drop in the bucket) of observational studies that show the vaccines are protective hospitalization (but can do the same with other endpoints):
10.3389/fpubh.2022.873596
Now why don't you lend ANY credence to the same type, and more importantly, level of evidence that we used to prove that smoking is bad for you? This isn't one study on coffee and aneurysms, this is HUNDREDS upon HUNDREDS of studies across all epidemiological modalities coming to the same conclusion. So you only trust RCTs, and completely uncontrolled highly-confounded population-level data on crappy blogs done by amateurs that throw around the semi-relevant statistical terms rarely seen in the professional statistical literature? Do I have this right? But rounding up a bunch of patients and checking for their outcomes, that is not to be trusted even if hundreds of these types of studies all say the same thing? Do I have your position correct?
Are you shifting goalposts? You brought up RCTs, not me.
Engaging in ad hominem does not make your arguments more persuading.
You are straw-manning my position. I never said I don't lend ANY credence to observational studies.
Which semi-relevant statistical terms have I thrown about, which are rarely seen in professional statistical literature?
Why have you offered no explanation for the population data showing shifting trends in effectiveness?
The meta-study which your google search yielded includes 54 studies in its meta-analysis and and uses person days for calculating odds/hazard/incidence ratios. It claims 87% PVE against infection (Pooled Vaccine Effectivess) and apparently makes no consideration of waning effectiveness over time. Really?
This is a meta-study performed by Germany's RKI (Robert Koch Institute)
It considers waning effectivess over time. The ranges of effectiveness are to my mind are very concerning (going negative as time progresses).
Do you lend ANY credence to concerns about repeat dosing with mRNA products (never done before)?
Do you understand an intervention or treatment can demonstrate positive effectivess against particular endpoints AND potentially still result in greater incidences of all-cause mortality? This is why, for example, population-level data is of interest and can be important.
Did any of the studies in your meta-analysis compare at all-cause mortality rates???
Thanks for bringing this to our attention. It seems it should be a huge story, but I'm sure it will be buried by the mainstream media. Yet another data point proving the "unvaccinated" were right all along.
The UK excess death data by jab status is due to be published tomorrow (after we’ve waited 8 months for it). It’s worth noting NZ was about 8 months behind the UK, in roll-out, so expect a clear pattern in autoimmune disease will be evident by you experts out there, pretty soon. Tragic. Thanks for your commitment to the cause.
It is instructive to look at the 2 graphs above - ACM per 100k and "Deaths with Covid" per 100k, to deduce the "non-Covid Deaths" number. I.e. NCD = ACM - DwC.
When that is done, and I did it with the July peak data, you see that Boosted are suffering massive non-Covid deaths. Even "Fully Vaccinated" has far more non-Covid deaths than "Unvaccinated".
Even if the vaccines reduce Covid deaths (IMO doubtful), vaccinated are dying from non-Covid diseases (strokes? heart attack? cancers?) by a huge margin.
We MUST stop the vaccination campaign IMMEDIATELY until we can prove that the vaccines are not causing EXCESSIVE mortalities.
I've seen data from other sites and I believe NZ's excess deaths change of 10.5%, while already a bombshell, is relatively lower compared to other countries. I think in Germany it's around the 20%?
it depends on how the country report excess deaths - usually the figures that you see are weekly excess death (ie week 7 vs week 7 of last 5 years)
sometimes, they compare it with prepandemic (ie week 7 vs week 7 of years 2015-2019).
The full year excess deaths data will be lower because it was increasing throughout 2022 - weekly from 5% to 40% in some countries. if you average it out, it will be lower than 40%. we call the last point the exit point… exit excess death (last week of the year)
the NZ data is 10% increased deaths from 2021 to 2022 (full year). I shouldn’t call it excess death… my bad.
you're welcome to produce your own work and compare, fully vaxed and boosted are all over-representing over time in 2022, I've been doing graphs last year and this is similar to the covid deaths results, just this time the data comes from the horse's mouth
And no age info is meaningless, lol, she mad one with covid deaths age stratefied before based on MOH data, looks s*** still for all age groups of vaxed lol
The NZ Medsafe records are available in an excel file. They had an huge number of vaccine injury reports filed almost a year ago. They are 5M people and had 78k reports 4/22. I live in a state with a similar population and we had 19k at the same time.
This is science and needs to be further investigated and openly debated to be sure we aren’t doing more harm than good through the use of these drugs. Let’s discard the arrogant attitudes of the Faucis and Collins of the world who would have us believe that science is only what they claim to be true.
I can see how it is easy to argue there are problems with some of the “analysis” — maybe, those choosing to get boosted weighted to the truly sick (the opposite argument has also been made that maybe those with dementia or stage 4 cancer didn’t bother with any vaccines), or that the unvaccinated were killed off early etc but the “common man with common sense” would look at these illustrations and go “no way am I having a booster”. And ethical public health officials would go “confounded or not this signal is so large we got to look into it (and pause boosters in the meantime)”.
I agree with some of the comments below. If the data is not age adjusted it is meaningless. The higher mortality for the boosted may simply reflect that the elderly got boosted first and remain the most boosted. They are the ones who do 90% of the dying- so there is not much to see here. The interesting comparison is the 2 dose vs 'unvaccinated' who in reality are unvaccinated + people who only got 1 dose and they probably only got one dose because they had a serious reaction to it and their health is stuffed.
Also, the unvaccinated numbers ARE almost certainly under reported. The Govt uses the Health service user population which IS an underestimate. The real figure of unvaxxed is somewhere between their figure, and as much as 50% higher, so the rates per 100k could be wildly out
1) People with dementia, Alzheimers and stage four cancer were told to be vaccinated as they were more at risk from infection. I know. My husband was one of them.
2) We have no proof of this, but someone involved in policy and risk management has leaked that the unvaccinated are at least double the numbers reported. Apparently this is deliberate, for two reasons... to persuade the reluctant that they are stupid outliers, and to make medsafe data on infections, ICU and deaths doubly incriminating for the unvaccinated by halving the numbers.
As I said, we have no proof
3) Unvaccinated include every who has had no shots, 1 shot up to 14 days after, and 2 shots up to 14 days after. There is also internal discussion as to whether or not, not fully vaccinated should include anyone who hasn't had the latest booster, since "they" say that because immunity wears off so fast those people are essentially unvaccinated.
So there is a lot of statistical jury-rigging going on.
I just looked at Bronwyns twitter and see that she has an age adjustment on the graph there (https://twitter.com/Bronwyn_Meikle/status/1627595604246560768/photo/2). As I said above the unvaccinated population cant be estimated accurately so we cant do adequate vaxxed/unvaxxed comparisons, but that does not apply to 2dose/boosted comparisons. Her graph on twitter shows that 0-59 boosted death rate was considerably higher than the 2 dose in all months since April except July. And this gets worse with the older age groups... so there is something to see here. Good work Bronwyn.
@Aussie17,
1. I think @Bronwyn_Meikle 's all cause mortality rates per 100k are wrongly calculated - I suspect she has not adjusted the respective population denominator totals to reflect the shifting totals caused by the booster rollout. (I am waiting for her to reply to my DM)
2. IMO mortality rates by vaccination status not adjusted for age is simply not a meaningful metric. (see my other comment below)
3. As a large part of your post is based on a supposed correlation between the booster rollout and an inflection in the vaxxed:unvaxxed all cause deaths ratio, I think you really need to clarify the data for those rates you are basing your correlation on.
4. IF there is a significant shift in the ratio of vaxxed:unvaxxed deaths in Q1 2022, it is important to note it would also correlate with the rise of Omicron BA.2 to dominance in NZ.
thanks! pinned your comment and added an update.
You're welcome to produce your own work and compare, fully vaxed and boosted are all over-representing over time in 2022, I've been doing graphs last year and this is similar to the covid deaths results, just this time the data comes from the horse's mouth
And re: no age info is meaningless, lol, she made one with covid deaths age stratified before based on MOH data, looks s*** still for all age groups of vaxed lol - https://twitter.com/Bronwyn_Meikle/status/1627595604246560768
You have time to tell others it's useless, use your time to present your work for people to critic then, Stats NZ and MOH, wayback machine have all the info available
and yes, Omicron arrived early 2022 in NZ, & they're clearly not mainly after the vax-free.
"And re: no age info is meaningless, lol"
Do you understand about Simpson's Paradox? https://en.wikipedia.org/wiki/Simpson%27s_paradox
I think both sides have points so I pinned Witzbold comments. I don’t believe in silencing the other side’s arguments as long as they are not condescending, ad hominem attacks…etc
Let’s wait for the dust to settle - including corrections and further analysis etc. @brownyn_meikle also mentioned they will publish the data shortly in stats nz so lets wait for that too.
You're guessing based on the MOH graph aren't you? Not sure why the other of your analysis was deleted when replying
You are doing cumulative for the older population which means you're not presenting younger populations, and you are not presenting trends either.
With actual numbers available on government sites - boosted are over-represented and unvaxed are under-represented in the population.
Deaths with covid proportion -
Boosted 2810/3864=72.7%
2-dosed 564/3864=14.6%
Unvaxed 490/3864=12.7%
Population (June 2021 population - before vaccine mass rollout, which is an advantage for vaxed/boosted)
Boosted 2,752,564/5111300=53.9%
2-dosed 3,983,917+155,730-2,752,564/5111300=27.1%
Unvaxed (5111300-4,030,928-269,936)/5111300=15.9%
So numbers are already ugly for the boosted, and if your calculation using population and deaths ratio which is a very weird way of doing it (try adjust to 100K then calculate protection % using Pfizer's tech?), showing slight benefit for oldies, but boosted overall number is so over-represented, that means the numbers would be WORSE for the younger boosted population, that's the paradox you have, make oldies look good, it'd mean younger ones would be slaughtered, make oldies less good, it'd be just crap across the whole age groups, because the overall data just looks crap.
https://www.stats.govt.nz/topics/population
https://www.health.govt.nz/covid-19-novel-coronavirus/covid-19-data-and-statistics/covid-19-vaccine-data
There are also kiwis who have been keeping actual numbers and trends throughout 2022, the summary looks like this - a blow up since every month for the boosted respective age groups per 100K.
But you don't have those data because he's guessing the cumulative MOH vax graph probably because MOH don't show previous stats unless you use waybackmachine or keep an excel profile since last year like my friends did
By Bronwyn
https://twitter.com/Bronwyn_Meikle/status/1627595604246560768
By Guy Hatchard
https://twitter.com/Greenli44101756/status/1627599134411870210
For people interested here's analysis done by Grant Dixon of NZ
https://rumble.com/v1j6gvn-grant-dixon-official-data-shows-the-vaccine-is-harming-and-killing-a-large-.html
Here is another analysis graph showing the trend by another user
https://twitter.com/Greenli44101756/status/1627599949386100736
All cause is exactly the same trend in the UK govt data before they pulled it in June 2022
https://twitter.com/Greenli44101756/status/1627576808601436161
and NSW govt data showing the exact same trend of worse per million as well
https://twitter.com/Greenli44101756/status/1627799991279558657
@CW
I’m not sure why you have reacted to my comments as you have - it feels kind of agro. I am not a pharma shill and I am neither pro nor anti-vax. I am very skeptical and concerned about the Covid-19 so-called vaccines and similarly about the so-called pandemic. My Substack focuses primarily on German data and I am not trying to step on any Kiwi toes.
My comments have explicitly been responses to the NZ data which @Aussie17 has presented in his post and tweets including that from @Bronwyn_Meikle. And that’s also why I used the cumulative totals in my back of the envelope calculations, it is the data in his graphic!
As far as I am concerned, Bronwyn’s rates per 100k simply cannot be right because the population denominator she has used do not seem to reflect the booster rollout and the boosted population at the time. Consider the following figures from her tweet:
Jan 1st ‘22: boosted deaths = 651; Bronwyn’s rate = 25/100k => Boosted population = 2,604,00
Feb 1st ’22: boosted deaths = 1,311; Bronwyn’s rate = 51/100k => Boosted population = 2,570,588
Mar 1st ’22: boosted deaths = 2,076; Bronwyn’s rate = 81/100k => Boosted population = 2,562,962
Apr 1st ’22: boosted deaths = 2,241; Bronwyn’s rate = 88/100k => Boosted population = 2,546,590
Do you see the problem?
We are in agreement that cohort rates per 100k are optimal for determining vaccine effectiveness and also for showing trends. For my weird way of calculating effectiveness I used the odds ratio instead of the risk ratio. Using rates per 100k is ideal (as that equates to a risk ratio) but I disputed Bronwyn’s rates and the subpopulation denominators were constantly changing in 2022 so I just used the data at hand for my approximate calculations. I wasn’t trying to defend vaccine effectiveness, rather to point out the data was likely not as bad as Aussie17 was suggesting. In hindsight I should have been clearer that what I was doing with the odds ratio instead of risk ratio was an approximation and actual effectiveness would be somewhat lower.
Finally, because your reply to me is full of examples using overall population totals by vax status, I really think you should consider Simpson’s Paradox. In a nutshell: if an effect or trend is disproportionately found in a subsection of a population, then it may disappear or be reversed in overall population-level data, ie. IMO because Covid-associated deaths are disproportionately age stratified, it is important to always compare age groups and not overall populations.
You say "IMO because Covid-associated deaths are disproportionately age stratified". I don't think the age stratification is sufficient to call it disproportionate. Google Dennis Rancourt's analyses of excess mortality.
Over 90% of Covid-associated deaths in NZ occur in the over 60's population. And around half of All-Cause deaths in NZ occur in over 80's! If you don't see that as disproportionate, I don't know what to say.
Hmm.. crickets 🦗 from you and Bronwyn...
hm I’m waiting for the dust to settle a bit and write a followup next week
I don't see that Simpson's Paradox applies. I don't see an indication of the prerequisite trend that 'disappears or reverses when the groups are combined'. The trend is in the group and in the parts.
Bronwyn's tweet shows in overall population all-cause deaths, the boosted are "over-represented".
Aussie17's chart shows in age groups they are NOT "over-represented"
https://twitter.com/_shloka/status/1627648119390216192?s=20
Not to mention when you adjust for age, location, and behavior that effect vanishes. Isn't it so strange that the amateur sluths using highly-confounded population data (which no scientist uses to answer clinical questions) finds spurious correlations that run counter to all clinical research. How weird that when we perform an RCT or controlled prospective (or retrospective) study this effect vanishes completely? Hmm I wonder theoretically what it is about the nearly-identical booster that makes it a 'kill shot'. Here's a tip to the scientific illiterate: population-level data is so confounded you can find whatever you want depending on how you slice it, and since no one bothers to control for anything all the better to push really bad takes.
The question is then why authorities haven't tried to conduct more rigours studies and analysis to remove the confounders and confusion to produce reliable data???
As to the third shot. Do some reading about Moderna and Biontech's pasts and why they never successfully peviously brought an mRNA product to market.
They have. It's called clinical research. Why use satellite imagery to determine why people leave their homes when you can just go ask why they are leaving. No one uses this type of data to determine clinical questions; but it is fertile ground for amateurs to cherry-pick and drive the ignorant to their newsletters by making mountains out of specious correlations and unnuanced numbers.
Let me guess, it's a conspiracy theory, right? I know when you guys can't deal with the overwhelming evidence against your position you have to deny it all and jump straight to the conspiracies, but does the answer to your question also apply to the future mRNA vaccines coming out (Flu, RSA, Zika, Cancer)? And China's mRNA's about to come out? How about the 10 other companies working on mRNA right now? Does it apply to Nutcracker, Deep Genomics, Siraomics, Laronde, Abrogen, Arrowhead, Dicerna, Locanabio, ProQR, Shape and Stroke too? Ah yes. The GLOBAL conspiracy I'm sure.
Either way: control for age, behavior, and location and the effect in this article goes away. I wonder: back in 2021 when this same data showed vaccines had a HUGE protective effect, did you all believe it then? Well at least we can all agree back in 2021 vaccines were saving lives based on this EXACT same data 1.5 years ago. Kumbaya!
Why do you think the same population data shows differences between 2021 and 2022. Do you recognise that imperfect, confounded data can still reveal true trends and shifting effectiveness?
Of course it can (still not sure why you're using population data and not clinical data), but at least we we can all agree back in 2021 this SAME data showed the vaccine saving lives.
Please link the RCTs showing vax effectiveness against death and hospitalisation. I only know of RCTs with symptomatic infection as end point. As far as I know, all others are observational studies. Thanks.
Once the vaccine is deemed effective (the primary endpoint of the original RCT was for symptomatic covid) then it is unethical to take something that is highly protective and deny it to a control group. The RCTs you seek can't ethically be run any longer, especially now we have all sorts of other evidence that it is protective against death and hospitalization. Here are 54 studies (just a drop in the bucket) of observational studies that show the vaccines are protective hospitalization (but can do the same with other endpoints):
10.3389/fpubh.2022.873596
Now why don't you lend ANY credence to the same type, and more importantly, level of evidence that we used to prove that smoking is bad for you? This isn't one study on coffee and aneurysms, this is HUNDREDS upon HUNDREDS of studies across all epidemiological modalities coming to the same conclusion. So you only trust RCTs, and completely uncontrolled highly-confounded population-level data on crappy blogs done by amateurs that throw around the semi-relevant statistical terms rarely seen in the professional statistical literature? Do I have this right? But rounding up a bunch of patients and checking for their outcomes, that is not to be trusted even if hundreds of these types of studies all say the same thing? Do I have your position correct?
Are you shifting goalposts? You brought up RCTs, not me.
Engaging in ad hominem does not make your arguments more persuading.
You are straw-manning my position. I never said I don't lend ANY credence to observational studies.
Which semi-relevant statistical terms have I thrown about, which are rarely seen in professional statistical literature?
Why have you offered no explanation for the population data showing shifting trends in effectiveness?
The meta-study which your google search yielded includes 54 studies in its meta-analysis and and uses person days for calculating odds/hazard/incidence ratios. It claims 87% PVE against infection (Pooled Vaccine Effectivess) and apparently makes no consideration of waning effectiveness over time. Really?
This is a meta-study performed by Germany's RKI (Robert Koch Institute)
https://www.frontiersin.org/articles/10.3389/fimmu.2022.940562/full
It considers waning effectivess over time. The ranges of effectiveness are to my mind are very concerning (going negative as time progresses).
Do you lend ANY credence to concerns about repeat dosing with mRNA products (never done before)?
Do you understand an intervention or treatment can demonstrate positive effectivess against particular endpoints AND potentially still result in greater incidences of all-cause mortality? This is why, for example, population-level data is of interest and can be important.
Did any of the studies in your meta-analysis compare at all-cause mortality rates???
Oh, well... Bronwyn has not replied and seems to have blocked my DMs?
I have posted the figures from NZ Ministry of Health for comparison: https://twitter.com/_shloka/status/1627989967866568705?s=20
I calculated the cumulative Boosted Population Total from NZ MOH's Vaccine Data, available for download here: https://www.health.govt.nz/system/files/documents/pages/covid_vaccinations_01_02_2023_updated.xlsx
Thanks for bringing this to our attention. It seems it should be a huge story, but I'm sure it will be buried by the mainstream media. Yet another data point proving the "unvaccinated" were right all along.
Thanks for the info - no wonder Jacinda Ardern resigned?
👏✊️👏💣💣💣🤜🙈🤛
The UK excess death data by jab status is due to be published tomorrow (after we’ve waited 8 months for it). It’s worth noting NZ was about 8 months behind the UK, in roll-out, so expect a clear pattern in autoimmune disease will be evident by you experts out there, pretty soon. Tragic. Thanks for your commitment to the cause.
The Daily Beagle goes further and reveals how the ONS data is a complete fudge:
thedailybeagle.substack.com/p/fudgegate-ons-caught-fudging-mortality
It is instructive to look at the 2 graphs above - ACM per 100k and "Deaths with Covid" per 100k, to deduce the "non-Covid Deaths" number. I.e. NCD = ACM - DwC.
When that is done, and I did it with the July peak data, you see that Boosted are suffering massive non-Covid deaths. Even "Fully Vaccinated" has far more non-Covid deaths than "Unvaccinated".
Even if the vaccines reduce Covid deaths (IMO doubtful), vaccinated are dying from non-Covid diseases (strokes? heart attack? cancers?) by a huge margin.
We MUST stop the vaccination campaign IMMEDIATELY until we can prove that the vaccines are not causing EXCESSIVE mortalities.
I've seen data from other sites and I believe NZ's excess deaths change of 10.5%, while already a bombshell, is relatively lower compared to other countries. I think in Germany it's around the 20%?
it depends on how the country report excess deaths - usually the figures that you see are weekly excess death (ie week 7 vs week 7 of last 5 years)
sometimes, they compare it with prepandemic (ie week 7 vs week 7 of years 2015-2019).
The full year excess deaths data will be lower because it was increasing throughout 2022 - weekly from 5% to 40% in some countries. if you average it out, it will be lower than 40%. we call the last point the exit point… exit excess death (last week of the year)
the NZ data is 10% increased deaths from 2021 to 2022 (full year). I shouldn’t call it excess death… my bad.
We are behind many other countries in terms of timescales.
Wow, this is a bombshell story.
See my comment above. I don't think those all-cause mortality rates by vaccination status per month have been calculated correctly.
you're welcome to produce your own work and compare, fully vaxed and boosted are all over-representing over time in 2022, I've been doing graphs last year and this is similar to the covid deaths results, just this time the data comes from the horse's mouth
And no age info is meaningless, lol, she mad one with covid deaths age stratefied before based on MOH data, looks s*** still for all age groups of vaxed lol
The NZ Medsafe records are available in an excel file. They had an huge number of vaccine injury reports filed almost a year ago. They are 5M people and had 78k reports 4/22. I live in a state with a similar population and we had 19k at the same time.
Hi, loved the article. Looking forward to rest of the G20's results.
The same data is being shown in Steve Kirch's substack. Going to get alot of eyes on it! https://stevekirsch.substack.com/p/new-zealand-government-data-shows
sweet!
This is science and needs to be further investigated and openly debated to be sure we aren’t doing more harm than good through the use of these drugs. Let’s discard the arrogant attitudes of the Faucis and Collins of the world who would have us believe that science is only what they claim to be true.
I can see how it is easy to argue there are problems with some of the “analysis” — maybe, those choosing to get boosted weighted to the truly sick (the opposite argument has also been made that maybe those with dementia or stage 4 cancer didn’t bother with any vaccines), or that the unvaccinated were killed off early etc but the “common man with common sense” would look at these illustrations and go “no way am I having a booster”. And ethical public health officials would go “confounded or not this signal is so large we got to look into it (and pause boosters in the meantime)”.
I agree with some of the comments below. If the data is not age adjusted it is meaningless. The higher mortality for the boosted may simply reflect that the elderly got boosted first and remain the most boosted. They are the ones who do 90% of the dying- so there is not much to see here. The interesting comparison is the 2 dose vs 'unvaccinated' who in reality are unvaccinated + people who only got 1 dose and they probably only got one dose because they had a serious reaction to it and their health is stuffed.
Also, the unvaccinated numbers ARE almost certainly under reported. The Govt uses the Health service user population which IS an underestimate. The real figure of unvaxxed is somewhere between their figure, and as much as 50% higher, so the rates per 100k could be wildly out
Three things.
1) People with dementia, Alzheimers and stage four cancer were told to be vaccinated as they were more at risk from infection. I know. My husband was one of them.
2) We have no proof of this, but someone involved in policy and risk management has leaked that the unvaccinated are at least double the numbers reported. Apparently this is deliberate, for two reasons... to persuade the reluctant that they are stupid outliers, and to make medsafe data on infections, ICU and deaths doubly incriminating for the unvaccinated by halving the numbers.
As I said, we have no proof
3) Unvaccinated include every who has had no shots, 1 shot up to 14 days after, and 2 shots up to 14 days after. There is also internal discussion as to whether or not, not fully vaccinated should include anyone who hasn't had the latest booster, since "they" say that because immunity wears off so fast those people are essentially unvaccinated.
So there is a lot of statistical jury-rigging going on.
I just looked at Bronwyns twitter and see that she has an age adjustment on the graph there (https://twitter.com/Bronwyn_Meikle/status/1627595604246560768/photo/2). As I said above the unvaccinated population cant be estimated accurately so we cant do adequate vaxxed/unvaxxed comparisons, but that does not apply to 2dose/boosted comparisons. Her graph on twitter shows that 0-59 boosted death rate was considerably higher than the 2 dose in all months since April except July. And this gets worse with the older age groups... so there is something to see here. Good work Bronwyn.
Is this an example of Darwinism?
Less useful without age-stratification and normalization.