Hey Albert thanks for this analysis which I would say complements ours. It is pretty clear at the start or our article that there are excess deaths in New Zealand and those deaths are (mostly) accounted for by the change in age demographics (an issue that has not yet been resolved).
Our article was merely to demonstrate that the cohort in the "whistleblower" data as recorded by Mongol (which is presumed to be the original data although may have been further obfuscated) and analysed by us had a slightly lower death rate than the background rate for New Zealand as a whole during that time period. That lower rate was easily accounted for by missing death data, which the "whistleblower" would likely not have access to.
In other words, to claim that that data showed a massive death signal (or any at all) was inaccurate and did not help the cause of exposing the excess deaths associated with the COVID interventions (which include but are not limited to the gene therapy vaccine rollout).
Whether we are "pro-vaccine" or "anti-vaccine" is as irrelevant as whether we are "pro-Pepsi" or "anti-Pepsi". What we are is very much against pharmaceutical corporations and governments lying about the safety and efficacy of their products and forcing them on people who don't want them or don't need them.
As for the NZ data not showing excess deaths, in NZ we saw isolated jab events ( pop up clinics /tents where people came to get jabbed) showing unusual death rates shortly after the jab. My small town of 200 had 3.5% deaths within 6 weeks of the jab and 17% AER ( cancer and heart issues clearly) unknown how many have other issues not disclosed. There were 4 jab centres 2 Drs clinics but most people didnt get them there, as the Drs did very few face to face clinics. A pop up tent (not using trained nurses to administer jabs) and the local "Maori" had a jab centre they were paid to run, also not using medical staff. Lots of deaths occured suddenly, but we were not allowed autopsies or able to refer to coroner. My daughter working in Care home saw many detahs post jab and from having a waiting list of weeks to get a room, now the care home has sometimes 50% occupancy. All anecdotal right?. ..
Anecdotal except there are so many anecdotes like this it becomes impossible to ignore.
Steve Kirsch did one thing right which was to challenge the government to release data which could be audited by the people themselves.
All that would need to happen for this is for each registered NZ vaccinee to receive a unique code from the government (SMS or letter) so they could check their entry on a publicly published and anonymised registry. For each person there would be the hash code, the date of each vaccine, and the date of death if any. The government would have to endorse whichever data set they published. If it differed significantly from the NZWB data set then that would show that the NZWB data set not authentic and they would have no case against Barry Young. But, if there were any family members who found errors in the data base or missing death data, they should be able to bring a case for malfeasance. The government, of course, will not do that until they are legally forced to.
The jabbed do have a record, either paper or digital, ( digital under a scheme called "my Health" which can be checked at any time) yes there are a few errors ( not too many considering no trained people were admisitering the jab), but if family tries to get info after a death the Govt comes out with the standard "privacy act" in refusing any info. Of interest we cannot sue for any Health related events , errors or mistakes done by Govt health workers ( or contracted workers)
The data is real...the proof is the Govt has NOT denied anything released. Something they would have done from day 1
I didn't make any changes to the CSV file that I uploaded to my GitHub (but that I deleted after McKernan's MEGA account got nuked). You can run this to download the original files (about 1.3 GB):
Another useful file on the server is `data-transparency/New Zealand/time-series summaries/month_dose_week_single_age.txt`. It shows the number of person-days and deaths for each combination of dose number, single-year age group, calendar month, and week since vaccination.
Yeah we got similar person days - IIRC about 1.4bn. I would caution against publishing the access keys and/or to direct people to any existing copy given the injunction.
Our point since this story has started has been the same.
- Why New Zealand ?
- Why is it "allowed to leak", then Streisand-effected as hard as possible (and so poorly) ?
We don't need that for anyone to be unable to argue about the approval process or the argued safety under which these products have been mandated. Neither do we need Kirsch permanently distorting data - as he did, in my domains - in the Pfizer clinical trials, pushing fake death figures and refusing to rectify them (while the real picture was bad enough).
I don't see exactly which point of our analysis you felt was wrong ?
The age column is the age on approximately December 2nd 2023, or at least that's the date when I got the most people whose date of birth matched the age column.
You wrote: "Barry/Kirsch whistleblower’s data only has 39 kids from 0-4yrs old that were vaxxed (0 deaths)?" But actually it's 140 if you look at age on the day of vaccination:
The reason why the number of 95-99-year-olds in your table is 106% of the NZ population is because you used the age from the age column. When I calculated how many person-days there were under each age and I divided it by the average person-days per person, I got only about 79% of the total NZ population included in the 95+ age group (when I used 2021-2022 average population figures): https://mongol-fi.github.io/moar.html#Representation_of_age_groups_in_the_dataset.
I think the younger people appear to be underrepresented because ALL the shots in 2021 are underrepresented, and not many younger people came back in 2022 for boosters.
I just posted a vid in my notes from a doc and a Australian doc chatting about the data. They mentioned that the mortality data in the 30-40 years was quite significant at 0.6 whereas the background rate for that age is something like 0.06, not huge numbers but very significant. I'm still trying to figure out how to use Substack, I'm sorry that I am not yet able to share it properly. All the best and thankyou for helping.
Hey Albert thanks for this analysis which I would say complements ours. It is pretty clear at the start or our article that there are excess deaths in New Zealand and those deaths are (mostly) accounted for by the change in age demographics (an issue that has not yet been resolved).
Our article was merely to demonstrate that the cohort in the "whistleblower" data as recorded by Mongol (which is presumed to be the original data although may have been further obfuscated) and analysed by us had a slightly lower death rate than the background rate for New Zealand as a whole during that time period. That lower rate was easily accounted for by missing death data, which the "whistleblower" would likely not have access to.
In other words, to claim that that data showed a massive death signal (or any at all) was inaccurate and did not help the cause of exposing the excess deaths associated with the COVID interventions (which include but are not limited to the gene therapy vaccine rollout).
Whether we are "pro-vaccine" or "anti-vaccine" is as irrelevant as whether we are "pro-Pepsi" or "anti-Pepsi". What we are is very much against pharmaceutical corporations and governments lying about the safety and efficacy of their products and forcing them on people who don't want them or don't need them.
I hope that clarifies things.
Thanks for your explanation and viewpoint.
As for the NZ data not showing excess deaths, in NZ we saw isolated jab events ( pop up clinics /tents where people came to get jabbed) showing unusual death rates shortly after the jab. My small town of 200 had 3.5% deaths within 6 weeks of the jab and 17% AER ( cancer and heart issues clearly) unknown how many have other issues not disclosed. There were 4 jab centres 2 Drs clinics but most people didnt get them there, as the Drs did very few face to face clinics. A pop up tent (not using trained nurses to administer jabs) and the local "Maori" had a jab centre they were paid to run, also not using medical staff. Lots of deaths occured suddenly, but we were not allowed autopsies or able to refer to coroner. My daughter working in Care home saw many detahs post jab and from having a waiting list of weeks to get a room, now the care home has sometimes 50% occupancy. All anecdotal right?. ..
Anecdotal except there are so many anecdotes like this it becomes impossible to ignore.
Steve Kirsch did one thing right which was to challenge the government to release data which could be audited by the people themselves.
All that would need to happen for this is for each registered NZ vaccinee to receive a unique code from the government (SMS or letter) so they could check their entry on a publicly published and anonymised registry. For each person there would be the hash code, the date of each vaccine, and the date of death if any. The government would have to endorse whichever data set they published. If it differed significantly from the NZWB data set then that would show that the NZWB data set not authentic and they would have no case against Barry Young. But, if there were any family members who found errors in the data base or missing death data, they should be able to bring a case for malfeasance. The government, of course, will not do that until they are legally forced to.
The jabbed do have a record, either paper or digital, ( digital under a scheme called "my Health" which can be checked at any time) yes there are a few errors ( not too many considering no trained people were admisitering the jab), but if family tries to get info after a death the Govt comes out with the standard "privacy act" in refusing any info. Of interest we cannot sue for any Health related events , errors or mistakes done by Govt health workers ( or contracted workers)
The data is real...the proof is the Govt has NOT denied anything released. Something they would have done from day 1
I didn't make any changes to the CSV file that I uploaded to my GitHub (but that I deleted after McKernan's MEGA account got nuked). You can run this to download the original files (about 1.3 GB):
brew install rclone
printf %s\\n '[kirsch]' type=s3 provider=Other access_key_id=g42m54xwZS80yQpAO20Q secret_access_key=Kq77gLL47mbypnnRc0UP7sPTvrvjn6y0D5FSEK5H endpoint=kirsch.izt.world:443 acl=private>~/.config/rclone/rclone.conf
rclone sync kirsch:/data-transparency data-transparency
Another useful file on the server is `data-transparency/New Zealand/time-series summaries/month_dose_week_single_age.txt`. It shows the number of person-days and deaths for each combination of dose number, single-year age group, calendar month, and week since vaccination.
Yeah we got similar person days - IIRC about 1.4bn. I would caution against publishing the access keys and/or to direct people to any existing copy given the injunction.
Hi Albert,
It's indeed hard to confuse us with jab pushers.
Our point since this story has started has been the same.
- Why New Zealand ?
- Why is it "allowed to leak", then Streisand-effected as hard as possible (and so poorly) ?
We don't need that for anyone to be unable to argue about the approval process or the argued safety under which these products have been mandated. Neither do we need Kirsch permanently distorting data - as he did, in my domains - in the Pfizer clinical trials, pushing fake death figures and refusing to rectify them (while the real picture was bad enough).
I don't see exactly which point of our analysis you felt was wrong ?
The age column is the age on approximately December 2nd 2023, or at least that's the date when I got the most people whose date of birth matched the age column.
You wrote: "Barry/Kirsch whistleblower’s data only has 39 kids from 0-4yrs old that were vaxxed (0 deaths)?" But actually it's 140 if you look at age on the day of vaccination:
t=as.data.frame(data.table::fread("nz-record-level-data-4M-records.csv"))
for(i in grep("date",colnames(t)))t[,i]=as.Date(t[,i],"%m-%d-%Y")
t=t[order(t$date_time_of_service),]
t=t[!duplicated(t$mrn),]
library(lubridate);vaxage=t$date_of_birth%--%t$date_time_of_service%/%years()
sum(vaxage[vaxage<5])
The reason why the number of 95-99-year-olds in your table is 106% of the NZ population is because you used the age from the age column. When I calculated how many person-days there were under each age and I divided it by the average person-days per person, I got only about 79% of the total NZ population included in the 95+ age group (when I used 2021-2022 average population figures): https://mongol-fi.github.io/moar.html#Representation_of_age_groups_in_the_dataset.
I think the younger people appear to be underrepresented because ALL the shots in 2021 are underrepresented, and not many younger people came back in 2022 for boosters.
a propos of nothing in particular!
https://www.theguardian.com/world/2021/dec/13/new-zealand-authorities-investigate-claims-man-received-10-covid-vaccinations-in-one-day
Thank you for this.
I just posted a vid in my notes from a doc and a Australian doc chatting about the data. They mentioned that the mortality data in the 30-40 years was quite significant at 0.6 whereas the background rate for that age is something like 0.06, not huge numbers but very significant. I'm still trying to figure out how to use Substack, I'm sorry that I am not yet able to share it properly. All the best and thankyou for helping.
You're a genius and I thank you for putting this information out!!!