No statistical significant effect on all-cause mortality by COVID-19 vaccination status. Higher Rates observed in COVID-19 vaccinated during COVID-19 attributed excess mortality periods.
Denis Rancourt and colleagues have shown that there never was a pandemic or any kind of public health emergency.
Several groups have explained that massed testing using PCR-based diagnostics are invalid measures & are props to a deception.
Given the foregoing, no “countermeasures” were ever appropriate. Not lockdown, not masks, not business closures, not border restrictions, not mass testing of the population whether sick or well, not massed injections.
As a long time former big pharma & biotech research executive, I understand the drug design process more than adequately. Not one atom or compound is in a finished product without having been chosen to be there & there’s always a rationale for inclusion. Looking at the design of these injections masquerading as vaccines against a non-existent health threat, I can discern several, independent mechanisms of toxicity and others have found others.
Bottom line, someone applied effort and industry knowledge to build these substances with the intention of causing harm, some of which inevitably would lead to deaths. Additionally, there are features built into at least the mRNA-based products designed to reduce fertility in survivors.
Unfortunately, where we can see the epidemiological evidence, we find injuries and deaths following injections, by several modes of toxicity.
I don’t understand how anyone can conclude other than a long planned attack upon humanity is underway, nor that there can be any other expectation than that there’ll be further attacks.
I have not observed any of the institutions designed to protect the people from harm actually doing their jobs, implying they have all been captured.
Thus, no one is coming to save us.
We can save ourselves and those who are prepared to plan to not be immediately vulnerable to whatever crisis is next visited upon us.
I think our best hope of survival as a free species is to refuse to comply with the next set of instructions. The worse the threatened sanctions for non compliance, I submit the more important it is to resist.
Thank you for your effort. Torturing the data working, with bizarre definitions asserting unvaxxed status until 2/52 post hoc jab, and covering for an unaccounted number of deaths attached to fatal AESIs prior to 2/52 is soul destroying work.
Some comments: Weekly excess deaths above the 2015 -2019 mean (oecd.stat) remain @ 15%. The excess deaths observed in Australia and New Zealand since 2020 track each other in near perfect concordance. Note that there is no concordance of Oceania with Sweden. Whatever the shot composition variables of the uncontrolled, data obfuscated experiment being run Down Under, they do not appear the same as Scandinavia.
As you and me both know this is about population control.
You’ve suggested 10b tops for the planet. How would you go about maintaining numbers there if you couldn’t go to fraudulent pandemics and vaxxes? Jules Radich the Mayor of Dunedin said to me that countries like Sweden and most of the West had births at lower than replacement levels in a response to discussion we had about climate change so he knows it too. But capitalism seems pretty keen on replacing the slowness of local births with immigration. Is capitalism capable of handling lower than replacement birth rates? If it’s not then why are they all supporting the hell out of the WEF.
People were considered unvaccinated until a few weeks after their vaccination which is the most likely time someone dies from a vaccine. My uncle died within 48 hours of vaccination but will be in the records as an unvaccinated death. The jab has caused widespread harm in the vaccinated and hospitals are full of them. The hdc were warning people a few weeks back of delays as so many staff off sick in summer. Schools have had to send kids home as too many teachers off sick getting covid.
Many of the vaccinated are getting sick every 6 months. For them the pandemic is still happening and Michael baker says it’s not over
The thing is there is a high amount of excess deaths but it all depends on how the person doing the math calculates it. It’s pointless only looking at statistics from 2020 onwards without looking back. It’s the excess deaths. It’s the reports from funeral directors and those of embalmers that are the reality
Denis Rancourt has also found high excess deaths in the vaccinated in the entire southern hemisphere and his research matches with the reality on the ground.
The Vaxxed are wandering around with brain fog bewildered as to why they are always sick...
Meanwhile I feel absolutely fantastic!!! Lots of energy -- keeping fit in the gym and on my bike... no cancer... no stroke.. no heart issues.. no issues at all... I just feel so good. When I am around Vaxxers I make sure they know it.
Doesn't matter - they still think I'm gonna die cuz I ain't Rat Juiced
Not being able to "show papers" and to prove the status inevitably leads to label "unvaccinated". That's the case in each emergency situation. There's no way to tell whether someone is jabbed or not and how many times since the certificate is not carried around 24/7 any more like during the coercion episode. They can count whatever fits their narrative. Kiwis were easy to coerce into vaccination because of their isolated location.
I agree, we must maintain a conscious mind. However, that's all we got, in the end, until people give us more data. It could also be through whistleblowing.
Curious to know if vaccination status as defined by the NZ Ministry of Health adheres to the CDC definition. I'm guessing that it does. And if that's the case, the ACM for "unvaccinated" is most likely inverted or at least seriously distorted.
I have had a fair bit of back and forth correspondence with the MoH and Medsafe regarding their definitions. They confirmed for me that a vaccinated person can die from/with covid weeks after their jab and still be classed as unjabbed. I describe the correspondence in the Misclassification section of my Latest Stats substack (I spent a year or so extracting daily data from the cumulative data released by the MoH). The data was pretty erratic. Sometimes hundreds of dead people would just disappear overnight with no sensible explanation.
I've confirmed it, thanks to epi contacts within NZ. Both the CDC and NZ MoH initially defined "fully vaccinated" as having completed the C19 vaccine's primary series, i.e., 2 shots. The status of being fully vaccinated was considered to be in effect 14 days after receiving the 2nd dose of a 2-dose vaccine series or 14 days after receiving a single-dose vaccine, like the J&J vaccine. So anyone who died before that 14-day limit, even if they received the injection, was considered unvaccinated. Many elderly people died within 14 days of the 1st and 2nd shots, most likely as a result of those shots (as the large Hulscher et al. autopsy review revealed). This means that you'd have to somehow account for this fraudulent definition in your analysis, which looks next to impossible. If only they had defined vaccination status to account for serious adverse events occurring after the first injection.
"The status of being fully vaccinated was considered to be in effect 14 days after receiving the 2nd dose of a 2-dose vaccine series or 14 days after receiving a single-dose vaccine, like the J&J vaccine. So anyone who died before that 14-day limit, even if they received the injection, was considered unvaccinated."
As someone who collects and analyses data to evaluate systems for a living, the confounding caused by calling the first 14 days 'unvaccinated' is, in itself, enough for me to know the whole thing is a joke and a fraud, that no'one at the top actually cares about anyone's health. Wanting feedback about how an intervention performs and baking confounding factors into the raw data are contradictory, cannot both be true. If you are scared you'll be proved wrong and blamed, this is a tried and tested way to provide wiggle room and allow some after the fact hand-waving.
Incidentally, what you do if you care is you don't even have a binary column of 'vaccinated' or 'not' - at the record level, you simply, for example, record a list of dates the injections took place. Then, people down the line can make whatever model they want. Maybe 14 days makes sense, maybe it doesn't - we can all find out. By implicitly placing a model into the raw data, you make this impossible. Only people who don't want to actually know what is happening - and in fact want to prevent anyone ever finding out - bake models into record level data like this.
Same in the Netherlands. The institutes did a re-analysis to compare the effect of the 2 weeks (sometimes 4) of 'wait' time. About 20.000 deaths shifted from unvax to vax group. According to the institutes it gave roughly the same image and did not change the 'safe & effective' narrative.
There's usually 3 or more weeks between the second dose and first dose, so there's usually 5 or more weeks from the day of the first dose until two weeks after the second dose. So of course if deaths during the first 5 weeks from the first dose are not counted, then it will reduce the total number of deaths in vaccinated people (https://www.cbs.nl/nl-nl/longread/rapportages/2024/covid-vaccinatiestatus-en-sterfte/2-methode).
When people are counted as vaccinated immediately after the first dose, then the first death in vaccinated people is on week 5 of 2021, but the first death is only on week 10 when people are only counted as vaccinated 2 weeks after the second dose (or after they are otherwise considered fully vaccinated according to the criteria which were used by the CBS): https://i.ibb.co/PrW3Zmx/dutch-cbs-asmr-by-vax-status-different-definitions.gif.
Nice work Ben and I'll thank my numbers main man Joel "Metatron" Smalley for pointing me to your stack.😉😊
After 4 years of this BS statistical shell game, I frankly don't give a flying fig anymore about their quantitative 14 day definition of what denotes "vaccination status. It's a performative, statistical hand job, masquerading as "science". An insult to science, humanity, to Archimedes, a and anyone else that really understands numbers.😤🤐🤦♀️
I'm wanting hard numerical data on the 5mth-18mth gap between when the shots were initially given, to when someone "dies suddenly". The pattern is there anecdotally. It's there in the numbers. If we don't match the pattern with real world data, then millions of people will never be given justice. They will never be acknowledged as being part of a militarized, iatrogenic democide, as it will come to be known as. They will be written of as "tragically died young" due to one of the myriad of shot induced side effects that already happen to be diagnosed. Turbo cancers, prion disorders, suicides, car accidents, strokes, ad nauseam.😤😭🤐
Those that died within 56 days of receiving the shot, will be ultimately acknowledged as being "tragic victims of a terrible mistake". But that number of people, is no where near the terrible and horrifying number still to be calculated as the ultimate mortality rate.😐😐🤔😭😤😤🤦♀️
Thanks for doing these, we have an official inquiry coming up, the new deputy PM we voted in is on our side, but we need to get rid of the inquiry commissioners appointed by Ardern. These analysis would be helpful
Of note, yes like <20 died with covid in 2021, injection to the public started in July, ramped up to high gear from September, using a dead Polynesian man and family, had a Super Saturday event in early October, mandates 15th November, vax passport kicked in December, and healthcare workers and teachers were forced to take boosters before February. Freedom occupation and protest started in Feb and ended by govt violently in early March, where unvaxed did most of mass gathering while vaxed deaths were doing the spiking
Funny how unvaccinated were dying during the vax rollout, when covid only took less than 20, others have pointed out the vax status delays, wink wink
The lab leak hoax is another distraction, the only way to create a worldwide pandemic is to clone lots and lots of virus and spread it all over the place.
You wrote: "Despite these facts the original delta strain was appearing all over the world without any mutation for six months at the beginning of the so called pandemic."
Hwoever Delta was first detected in October 2020 in India, but it didn't become the dominant strain until mid-2021. And by that time it had already acquired several mutations from the earliest Delta sequences.
This table shows all mutations at GISAID which reached a frequency of 30% or above during one or more months of 2020: https://i.ibb.co/BnKXgb3/gisaid-2020-heat.png. There's a total of 15 mutations. By March 2020, the B.1 strain which includes D614G and three other mutations was already found in the majority of GISAID submissions.
And if WA1/proCoV2 is used as the root, then the three mutations of lineage B would've already become dominant by January 2020, so there would be a total of 7 mutations which are not included in WA1 but which were already found in the majority of submissions with a collection date in March 2020.
You wrote: "JJ Couey has found there were less than 10 amino acid differences over a period of 6 months, by comparison SARS-CoV-1 had between 33 and 50 amino acid differences per patient." I addressed Couey's claim here: sars2.net/nopandemic.html#Claim_that_SARS1_was_evolving_at_a_much_faster_rate_than_SARS2. Almost all human SARS1 sequences have 0-20 nucleotide changes from the Tor2 reference genome (and therefore an even smaller number of amino acid changes since many nucleotide changes are synonymous). The sequences that have more than 20 nucleotide changes are mostly lab-created strains like wtic, ExoN1, and MA15, or they are sequences which were supposedly collected from civets.
In the scenario that VOCs like BA.1 and BA.2 were released deliberately, it doesn't prove that natural spread is impossible. Because there could still be natural spread following an artificial release like in the case of the HIV.
In Rancourt's paper about southern-hemisphere and equatorial countries, he had a long list of possible explanations for why different countries over the world had a spike in excess deaths around January or February 2022, but I criticized him for failing to consider the scenario that BA.1 was released deliberately at multiple locations around the world: sars2.net/nopandemic.html#Dismissing_the_possibility_of_a_deliberate_release_of_Omicron.
The Omicron, Alpha, and Delta VOCs all emerged in a saltation event where multiple novel nonsynonymous spike mutations appeared simultaneously out of nowhere. If you compare the spike protein of a consensus sequence of XBB.1.5 Omicron sequences to Wuhan-Hu-1, there's a total of 41 nonsynonymous mutations but only 1 synonymous mutations, which results in a dN/dS ratio of 41, even though among 100 SARS1 sequences the average dN/dS ratio was about 3.6 and in H1N1 samples from Finland from 2009 it was around 0.2-1.2. If the spike of Wuhan-Hu-1 is compared to BANAL-52, there's 176 synonymous mutations but only 20 nonsynonymous mutations, so the XBB.1.5 consensus sequence has over double the number of nonsynonymous mutations. In the nucleocapsid protein of B.1.1, Alpha, BA.1, and BA.2, there's an unusual series of three consecutive nucleotide changes at positions 28,881-28,883, but a similar phenomenon was not previously known to occur in nature, so the authors of a Japanese paper had to coin a new term called "en bloc exchange" to describe the phenomenon.
As an amateur sleuth you may have to help me translate into layman's terms. So you agree a single lab leak in China followed by natural spread is bullshit and there have been multiple deliberate releases all over the world?
I'm not sure, because the mainstream explanation that VOCs are derived from chronic infections also seems somewhat plausible. For example Ryan Hisner has found one chronic infection sequence which had 36 mutations in the spike but 34 were non-synonymous (x.com/LongDesertTrain/status/1635062054473306112).
Trevor Bedford has suggested that the BA.1, BA.2, and BA.3 variants all developed inside the body of a single immunocompromised individual over the course of approximately a year, which seems a bit wild, but the BA.1 and BA.2 have so many common mutations that had not documented earlier that there needs to be some explanation for why they appear to have shared evolutionary history (x.com/trvrb/status/1349774308202094594).
And I also don't know how a chronic infection would explain the series of 3 consecutive mutations in the N gene at positions 28881-28883. The mutations were discussed in this Japanese paper by Tetsuya Akaishi, which was much better written than the paper that went viral a while ago, but somehow the worst papers always seem to become the most popular: jstage.jst.go.jp/article/tjem/260/1/260_2023.J010/_html/-char/en.
Great work, I think the viral spread that stopped abruptly at national borders points towards multiple releases and there are so many inconsistencies in the lab leak story is just makes no sense to me. The whole thing seems to have been carefully planned in advance and deployed worldwide. The synchronicity between all the governments reaction and terrible policies they all used is highly suspicious. That and their deployment of Midazolam, Morphine, Remdesivir and ventilators which is obviously mental when all people needed was vitamins and antibiotics!
Any significant difference between the NZ dataset and the historical recorded rates is a big red flag.
Even appearing in the ONS dataset provided immortality benefit to those individuals in the dataset. Hence thousands of deaths were missing.
(you cite an old article of ours, on an old blog, attributed solely to Norman which analysed reporting delay. We switched to miscategorisation as the most likely explanation. We revealed dozens of studies worldwide that relied on this 'cheap trick'.
The efficacy level is a statistical illusion manufactured by deploying the cheap trick. Even a negative efficacy vaccine (that gives you covid) would not only meet but would exceed the WHO 50% threshold.
Yes, I was looking into comparing to at historical averages. But guess, what NZ does not publish data by date of death age, and month (or week). Unbelievable!
For example in ages 80-89, when I did a linear regression for the CMR in 2015-2019 and I extended the trend to 2022, the average CMR in 2022 was about 6764. But you used 8500 as your historical CMR for ages 80-89.
My plots show that in ages 18-39, 40-49, and 50-59, the people who are included in the ONS dataset have much lower CMR than the general English population. It might be because unvaccinated people are underrepresented in the ONS dataset and unvaccinated people have a higher mortality rate than vaccinated people.
However in the three highest age groups, there is not much difference between the general English population and the people who are included in the ONS dataset.
In table 9, the column labeled "Historical mortality rate in 2016 (approximate)" seems to be quite far off from the actual mortality rates in England in 2016. For example you listed the mortality rate for ages 70-79 as 3000 but I got 2547 instead:
Table 9 also showed that in February to May 2022 in unvaccinated people in ages 18-39, the CMR increased from about 21 in the July 2022 version to about 29 in the February 2023 version. I also got about 21 as the mortality rate in the July 2022 version, but it was about 44 in the February 2023 version and about 53 in the August 2023 version. The mortality rate in the February 2023 version should be (99+91+78+87)/(192631+210888+202665+208452)*1e5. So you may have made some error.
---
In the plot from the mysterious colleague who wishes to remain anonymous, the reason why the increase to the previously reported ASMR values was bigger in unvaccinated people than vaccinated people was probably because unvaccinated people are younger than vaccinated people and younger people have a longer registration delay than elderly people. If the August 2023 version is compared to the February 2023 version, unvaccinated people also have a bigger increase to the previously reported ASMR values than ever vaccinated people: https://i.ibb.co/MNSzjdn/ons-unvaccinated-vs-ever-vaccinated-asmr-three-versions.png.
Table 9 shows that in ages 60-69 in February to May 2022, the mortality rate decreased from 1061 in the July 2022 version to 906 in the February 2023 version.
I also got 1061 as the mortality rate in the July 2022 version but in the February 2023 version it increased to 1354:
Your post also includes a plot which shows that in ages 18-39 in April 2021, the mortality rate was about 59 in vaccinated people and 32 in unvaccinated people (based on eyeballing from the plot). However actually it should've been about 88 in vaccinated people and 33 in unvaccinated people based on the February 2023 version, or about 90 and 35 based on the August 2023 version which I used here: sars2.net/stat.html#Plot_CMR_and_excess_mortality_by_age_group. The figure of 88 is from (18+194+19+15)/(40183+166571+42438+30337)*1e5.
No, I can't stand modern websites, and sites like Substack and Medium are even worse than earlier blogging platforms. Oldschool static websites are better. And Substack doesn't even support Markdown, but I can easily edit my website as Markdown files in Emacs. But I'll maybe add a dedicated page about the ONS data on my website.
Can you recheck your calculation for the mortality rates in February to May 2022 in the February 2023 release? For example you got 29 as the mortality rate for unvaccinated people in ages 18-39, but I think it should be about 44:
This is interesting. Thanks for doing this but admittedly I'm troubled. I'm only coming from a layman's perspective but the phrase "no significant difference" seems to explain away massive deaths from the Covid-19 vaccines. Looking at the initial graph, it seems about 45 extra people per 100,000 died in that 15 month period post 2021 - not a lot but raising it to the population vaccinated size of New Zealand (let's say 80%) of a 5 million populace or so, that yields 1,800 deaths.
Now with 45 per 100,000 being insignificant, let's apply this insignificance to the UK (again let's just say 80% vaxxed). With a population of 67 million, there's now a real problem. The problem is 24,120 extra deaths. No significant difference?
And the USA at 332 million population? We now have 119,520 deaths resulting from that small difference starting at 45 per 100,000.
If a gas explosion wiped out a small city and Joe Biden rocked up and said, don't, worry, it's not significant, we have 20,000 settlements in the US, that's only 6 people extra dying per settlement, it's not a problem, I think there would be a problem!
I'm not actually a maths guy tbh, so there's a chance I've made a dreadfully embarrassing mistake and perhaps my working is not perfect but there seems to be big trouble with this phrase from my perspective. Please tell me where I am going wrong?
You're right. I was looking at it more from a point of efficacy. From the evidence I've seen, there cannot be any real world efficacy, and that alone is enough. We know the shot kills. It must be pulled immediately.
As someone said to me if you are in a resthome it was probably mandatory to get the vaxx. I had a couple of looks at the NZ data myself and my analysis definitely indicated a higher death rate over 60.
Death notices in the NZ Herald (goes against the narrative of more deaths a little)
But most developed countries have a decreasing trend in mortality rate within age groups, so maybe it would make more sense to use the prepandemic trend as the baseline for each age group (or to use the average mortality rate in 2015-2019 as the baseline so it's not as far from the COVID era as the year 2010).
Yes, the issues in curating interpolation methodology subreferencing age-stratified disaggregation interpolation v age-standardized age/vaccination datasets... ‘Tis a bother innit.
It would help if our nz min health here were honest & data not fraudulent- & then they wouldnt have to go after barry young would they.
I prefer to trust my eyeballs out here in the real world, & here in nz two boyhood mates- infinitely fitter & healthier than moi- snuffed it to rapid cancers post vax, not seeing 65. We all have many such stories.
“Covid?” Sorry mate, you’ll have to explain that one.
My family didnt get vaxed, never masked or locked down- instead cheek by jowl with tens thousands other un-jabbed freedom fighters at rallies from auckland to wellington
... & never had your “covid.”
& all those we know got vaxed get “covid” every other week. A constant talking point for them.
Add philip buckler’s 714 page ‘book on masks’ to yr reading lists. Even more refs confirming masking ails mis-diagnosed as “covid” or “long covid.”
I have read enough OIA’s to know everything coming from our govt is fake. “Data manipulation” too tame a phrase. Same issue here as poms with their ONS.
Dear Ben, thanks for your great work with numerous interesting findings. I notice that in the cumulative mortality graph, the differences increase during winter in the southern hemisphere (~ July). Because of the strong age dependence of the seasonal waves, this is most likely related to age differences in the vaccination rate. Aggregations over 10-20 year age cohorts probably do not resolve this accurately enough, because mortality is exponentially age-dependent (above 30 years of age), while vax quote is not.
You can at least partially solve this with an interpolation using the base points available from the data (I do this in my estimation of weekly life expectancies from rough age cohorts, and it works quite well).
It is possible that the difference would then disappear completely.
Yes, exactly. In each age cohort, vaccination rates and mortality rates obey a different age function. While mortality follows a geometric progression, the vaccination rate, for example, increases linearly. Assuming that the risk of death increases by 10% per year, the mean age of those vaccinated within a 10-year cohort differs by around 3 years from that of those who have died. In my humble opinion, this requires a corrective calculation.
Denis Rancourt and colleagues have shown that there never was a pandemic or any kind of public health emergency.
Several groups have explained that massed testing using PCR-based diagnostics are invalid measures & are props to a deception.
Given the foregoing, no “countermeasures” were ever appropriate. Not lockdown, not masks, not business closures, not border restrictions, not mass testing of the population whether sick or well, not massed injections.
As a long time former big pharma & biotech research executive, I understand the drug design process more than adequately. Not one atom or compound is in a finished product without having been chosen to be there & there’s always a rationale for inclusion. Looking at the design of these injections masquerading as vaccines against a non-existent health threat, I can discern several, independent mechanisms of toxicity and others have found others.
Bottom line, someone applied effort and industry knowledge to build these substances with the intention of causing harm, some of which inevitably would lead to deaths. Additionally, there are features built into at least the mRNA-based products designed to reduce fertility in survivors.
Unfortunately, where we can see the epidemiological evidence, we find injuries and deaths following injections, by several modes of toxicity.
I don’t understand how anyone can conclude other than a long planned attack upon humanity is underway, nor that there can be any other expectation than that there’ll be further attacks.
I have not observed any of the institutions designed to protect the people from harm actually doing their jobs, implying they have all been captured.
Thus, no one is coming to save us.
We can save ourselves and those who are prepared to plan to not be immediately vulnerable to whatever crisis is next visited upon us.
I think our best hope of survival as a free species is to refuse to comply with the next set of instructions. The worse the threatened sanctions for non compliance, I submit the more important it is to resist.
Thank you for your effort. Torturing the data working, with bizarre definitions asserting unvaxxed status until 2/52 post hoc jab, and covering for an unaccounted number of deaths attached to fatal AESIs prior to 2/52 is soul destroying work.
Some comments: Weekly excess deaths above the 2015 -2019 mean (oecd.stat) remain @ 15%. The excess deaths observed in Australia and New Zealand since 2020 track each other in near perfect concordance. Note that there is no concordance of Oceania with Sweden. Whatever the shot composition variables of the uncontrolled, data obfuscated experiment being run Down Under, they do not appear the same as Scandinavia.
Data from MOH hospital deaths in vaxx v unvaxxed shows a similar ratio, although the preponderance of deaths in hospital becomes the dominant proportion seen with > vaxxing rates. https://drlatusdextro.substack.com/p/australian-senate-acknowledges-excess
and
https://drlatusdextro.substack.com/p/new-zealand-moh-data
Happy to provide you with the NZ hospital death data from MOH.
As you and me both know this is about population control.
You’ve suggested 10b tops for the planet. How would you go about maintaining numbers there if you couldn’t go to fraudulent pandemics and vaxxes? Jules Radich the Mayor of Dunedin said to me that countries like Sweden and most of the West had births at lower than replacement levels in a response to discussion we had about climate change so he knows it too. But capitalism seems pretty keen on replacing the slowness of local births with immigration. Is capitalism capable of handling lower than replacement birth rates? If it’s not then why are they all supporting the hell out of the WEF.
So many questions.
I don’t think there’s the slightest bit of evidence to support the claim that earth if beyond its carrying capacity.
We’ve been told it is for decades. There’s no evidence for the proposition that isn’t from the perpetrators.
Most demographers I’ve read that we’re around or just past peak population.
I think the perpetrators are killing for a mix of economic and spiritual (literally diabolical) reasons.
People were considered unvaccinated until a few weeks after their vaccination which is the most likely time someone dies from a vaccine. My uncle died within 48 hours of vaccination but will be in the records as an unvaccinated death. The jab has caused widespread harm in the vaccinated and hospitals are full of them. The hdc were warning people a few weeks back of delays as so many staff off sick in summer. Schools have had to send kids home as too many teachers off sick getting covid.
Many of the vaccinated are getting sick every 6 months. For them the pandemic is still happening and Michael baker says it’s not over
The thing is there is a high amount of excess deaths but it all depends on how the person doing the math calculates it. It’s pointless only looking at statistics from 2020 onwards without looking back. It’s the excess deaths. It’s the reports from funeral directors and those of embalmers that are the reality
Denis Rancourt has also found high excess deaths in the vaccinated in the entire southern hemisphere and his research matches with the reality on the ground.
The Vaxxed are wandering around with brain fog bewildered as to why they are always sick...
Meanwhile I feel absolutely fantastic!!! Lots of energy -- keeping fit in the gym and on my bike... no cancer... no stroke.. no heart issues.. no issues at all... I just feel so good. When I am around Vaxxers I make sure they know it.
Doesn't matter - they still think I'm gonna die cuz I ain't Rat Juiced
Life is fun... and good
Not being able to "show papers" and to prove the status inevitably leads to label "unvaccinated". That's the case in each emergency situation. There's no way to tell whether someone is jabbed or not and how many times since the certificate is not carried around 24/7 any more like during the coercion episode. They can count whatever fits their narrative. Kiwis were easy to coerce into vaccination because of their isolated location.
Articles like this take a lot of time, patience, and work. Thanks Ben! I appreciate it.
Thanks for the great work, but I don't trust government data. The same people who have been lying for the last 3 years are likely lying now.
I agree, we must maintain a conscious mind. However, that's all we got, in the end, until people give us more data. It could also be through whistleblowing.
Curious to know if vaccination status as defined by the NZ Ministry of Health adheres to the CDC definition. I'm guessing that it does. And if that's the case, the ACM for "unvaccinated" is most likely inverted or at least seriously distorted.
I have had a fair bit of back and forth correspondence with the MoH and Medsafe regarding their definitions. They confirmed for me that a vaccinated person can die from/with covid weeks after their jab and still be classed as unjabbed. I describe the correspondence in the Misclassification section of my Latest Stats substack (I spent a year or so extracting daily data from the cumulative data released by the MoH). The data was pretty erratic. Sometimes hundreds of dead people would just disappear overnight with no sensible explanation.
I don’t know but I’ve asked the FOIA requester.
In the dataset they have categories by last vaccination, which shows NA for unvaccinated.
But I don’t know how they handle the query at MoH.
I've confirmed it, thanks to epi contacts within NZ. Both the CDC and NZ MoH initially defined "fully vaccinated" as having completed the C19 vaccine's primary series, i.e., 2 shots. The status of being fully vaccinated was considered to be in effect 14 days after receiving the 2nd dose of a 2-dose vaccine series or 14 days after receiving a single-dose vaccine, like the J&J vaccine. So anyone who died before that 14-day limit, even if they received the injection, was considered unvaccinated. Many elderly people died within 14 days of the 1st and 2nd shots, most likely as a result of those shots (as the large Hulscher et al. autopsy review revealed). This means that you'd have to somehow account for this fraudulent definition in your analysis, which looks next to impossible. If only they had defined vaccination status to account for serious adverse events occurring after the first injection.
"The status of being fully vaccinated was considered to be in effect 14 days after receiving the 2nd dose of a 2-dose vaccine series or 14 days after receiving a single-dose vaccine, like the J&J vaccine. So anyone who died before that 14-day limit, even if they received the injection, was considered unvaccinated."
As someone who collects and analyses data to evaluate systems for a living, the confounding caused by calling the first 14 days 'unvaccinated' is, in itself, enough for me to know the whole thing is a joke and a fraud, that no'one at the top actually cares about anyone's health. Wanting feedback about how an intervention performs and baking confounding factors into the raw data are contradictory, cannot both be true. If you are scared you'll be proved wrong and blamed, this is a tried and tested way to provide wiggle room and allow some after the fact hand-waving.
Incidentally, what you do if you care is you don't even have a binary column of 'vaccinated' or 'not' - at the record level, you simply, for example, record a list of dates the injections took place. Then, people down the line can make whatever model they want. Maybe 14 days makes sense, maybe it doesn't - we can all find out. By implicitly placing a model into the raw data, you make this impossible. Only people who don't want to actually know what is happening - and in fact want to prevent anyone ever finding out - bake models into record level data like this.
John - thank you!
Same in the Netherlands. The institutes did a re-analysis to compare the effect of the 2 weeks (sometimes 4) of 'wait' time. About 20.000 deaths shifted from unvax to vax group. According to the institutes it gave roughly the same image and did not change the 'safe & effective' narrative.
There's usually 3 or more weeks between the second dose and first dose, so there's usually 5 or more weeks from the day of the first dose until two weeks after the second dose. So of course if deaths during the first 5 weeks from the first dose are not counted, then it will reduce the total number of deaths in vaccinated people (https://www.cbs.nl/nl-nl/longread/rapportages/2024/covid-vaccinatiestatus-en-sterfte/2-methode).
When people are counted as vaccinated immediately after the first dose, then the first death in vaccinated people is on week 5 of 2021, but the first death is only on week 10 when people are only counted as vaccinated 2 weeks after the second dose (or after they are otherwise considered fully vaccinated according to the criteria which were used by the CBS): https://i.ibb.co/PrW3Zmx/dutch-cbs-asmr-by-vax-status-different-definitions.gif.
Nice work Ben and I'll thank my numbers main man Joel "Metatron" Smalley for pointing me to your stack.😉😊
After 4 years of this BS statistical shell game, I frankly don't give a flying fig anymore about their quantitative 14 day definition of what denotes "vaccination status. It's a performative, statistical hand job, masquerading as "science". An insult to science, humanity, to Archimedes, a and anyone else that really understands numbers.😤🤐🤦♀️
I'm wanting hard numerical data on the 5mth-18mth gap between when the shots were initially given, to when someone "dies suddenly". The pattern is there anecdotally. It's there in the numbers. If we don't match the pattern with real world data, then millions of people will never be given justice. They will never be acknowledged as being part of a militarized, iatrogenic democide, as it will come to be known as. They will be written of as "tragically died young" due to one of the myriad of shot induced side effects that already happen to be diagnosed. Turbo cancers, prion disorders, suicides, car accidents, strokes, ad nauseam.😤😭🤐
Those that died within 56 days of receiving the shot, will be ultimately acknowledged as being "tragic victims of a terrible mistake". But that number of people, is no where near the terrible and horrifying number still to be calculated as the ultimate mortality rate.😐😐🤔😭😤😤🤦♀️
Glad I could help ; thanks for the credits (just kidding).
Thx. I will add attribution for the first dataset :)
Thanks for doing these, we have an official inquiry coming up, the new deputy PM we voted in is on our side, but we need to get rid of the inquiry commissioners appointed by Ardern. These analysis would be helpful
Of note, yes like <20 died with covid in 2021, injection to the public started in July, ramped up to high gear from September, using a dead Polynesian man and family, had a Super Saturday event in early October, mandates 15th November, vax passport kicked in December, and healthcare workers and teachers were forced to take boosters before February. Freedom occupation and protest started in Feb and ended by govt violently in early March, where unvaxed did most of mass gathering while vaxed deaths were doing the spiking
Funny how unvaccinated were dying during the vax rollout, when covid only took less than 20, others have pointed out the vax status delays, wink wink
The lab leak hoax is another distraction, the only way to create a worldwide pandemic is to clone lots and lots of virus and spread it all over the place.
More here; https://truthaddict.substack.com/p/lab-leak-zoonotic-spillover-or-deliberate
Acute respiratory illnesses are not contagious. It came as a shock to realise that the authorities have known this for a little over a century.
Given that, I believe that pandemics of this kind are impossible and have never happened.
I completely agree. It jumps out at you from the historical record.
You wrote: "Despite these facts the original delta strain was appearing all over the world without any mutation for six months at the beginning of the so called pandemic."
Hwoever Delta was first detected in October 2020 in India, but it didn't become the dominant strain until mid-2021. And by that time it had already acquired several mutations from the earliest Delta sequences.
This table shows all mutations at GISAID which reached a frequency of 30% or above during one or more months of 2020: https://i.ibb.co/BnKXgb3/gisaid-2020-heat.png. There's a total of 15 mutations. By March 2020, the B.1 strain which includes D614G and three other mutations was already found in the majority of GISAID submissions.
And if WA1/proCoV2 is used as the root, then the three mutations of lineage B would've already become dominant by January 2020, so there would be a total of 7 mutations which are not included in WA1 but which were already found in the majority of submissions with a collection date in March 2020.
You wrote: "JJ Couey has found there were less than 10 amino acid differences over a period of 6 months, by comparison SARS-CoV-1 had between 33 and 50 amino acid differences per patient." I addressed Couey's claim here: sars2.net/nopandemic.html#Claim_that_SARS1_was_evolving_at_a_much_faster_rate_than_SARS2. Almost all human SARS1 sequences have 0-20 nucleotide changes from the Tor2 reference genome (and therefore an even smaller number of amino acid changes since many nucleotide changes are synonymous). The sequences that have more than 20 nucleotide changes are mostly lab-created strains like wtic, ExoN1, and MA15, or they are sequences which were supposedly collected from civets.
Interesting, how do you explain the japanese study of the Omicron strain evolution that proves natural spread an impossibility
In the scenario that VOCs like BA.1 and BA.2 were released deliberately, it doesn't prove that natural spread is impossible. Because there could still be natural spread following an artificial release like in the case of the HIV.
In Rancourt's paper about southern-hemisphere and equatorial countries, he had a long list of possible explanations for why different countries over the world had a spike in excess deaths around January or February 2022, but I criticized him for failing to consider the scenario that BA.1 was released deliberately at multiple locations around the world: sars2.net/nopandemic.html#Dismissing_the_possibility_of_a_deliberate_release_of_Omicron.
The Omicron, Alpha, and Delta VOCs all emerged in a saltation event where multiple novel nonsynonymous spike mutations appeared simultaneously out of nowhere. If you compare the spike protein of a consensus sequence of XBB.1.5 Omicron sequences to Wuhan-Hu-1, there's a total of 41 nonsynonymous mutations but only 1 synonymous mutations, which results in a dN/dS ratio of 41, even though among 100 SARS1 sequences the average dN/dS ratio was about 3.6 and in H1N1 samples from Finland from 2009 it was around 0.2-1.2. If the spike of Wuhan-Hu-1 is compared to BANAL-52, there's 176 synonymous mutations but only 20 nonsynonymous mutations, so the XBB.1.5 consensus sequence has over double the number of nonsynonymous mutations. In the nucleocapsid protein of B.1.1, Alpha, BA.1, and BA.2, there's an unusual series of three consecutive nucleotide changes at positions 28,881-28,883, but a similar phenomenon was not previously known to occur in nature, so the authors of a Japanese paper had to coin a new term called "en bloc exchange" to describe the phenomenon.
As an amateur sleuth you may have to help me translate into layman's terms. So you agree a single lab leak in China followed by natural spread is bullshit and there have been multiple deliberate releases all over the world?
I'm not sure, because the mainstream explanation that VOCs are derived from chronic infections also seems somewhat plausible. For example Ryan Hisner has found one chronic infection sequence which had 36 mutations in the spike but 34 were non-synonymous (x.com/LongDesertTrain/status/1635062054473306112).
Trevor Bedford has suggested that the BA.1, BA.2, and BA.3 variants all developed inside the body of a single immunocompromised individual over the course of approximately a year, which seems a bit wild, but the BA.1 and BA.2 have so many common mutations that had not documented earlier that there needs to be some explanation for why they appear to have shared evolutionary history (x.com/trvrb/status/1349774308202094594).
And I also don't know how a chronic infection would explain the series of 3 consecutive mutations in the N gene at positions 28881-28883. The mutations were discussed in this Japanese paper by Tetsuya Akaishi, which was much better written than the paper that went viral a while ago, but somehow the worst papers always seem to become the most popular: jstage.jst.go.jp/article/tjem/260/1/260_2023.J010/_html/-char/en.
Great work, I think the viral spread that stopped abruptly at national borders points towards multiple releases and there are so many inconsistencies in the lab leak story is just makes no sense to me. The whole thing seems to have been carefully planned in advance and deployed worldwide. The synchronicity between all the governments reaction and terrible policies they all used is highly suspicious. That and their deployment of Midazolam, Morphine, Remdesivir and ventilators which is obviously mental when all people needed was vitamins and antibiotics!
One thing we did here for the ONS data was compare against historical mortality rates.
https://wherearethenumbers.substack.com/p/postmodern-science-delivers-immortality
Any significant difference between the NZ dataset and the historical recorded rates is a big red flag.
Even appearing in the ONS dataset provided immortality benefit to those individuals in the dataset. Hence thousands of deaths were missing.
(you cite an old article of ours, on an old blog, attributed solely to Norman which analysed reporting delay. We switched to miscategorisation as the most likely explanation. We revealed dozens of studies worldwide that relied on this 'cheap trick'.
https://wherearethenumbers.substack.com/p/the-very-best-of-cheap-trick
The efficacy level is a statistical illusion manufactured by deploying the cheap trick. Even a negative efficacy vaccine (that gives you covid) would not only meet but would exceed the WHO 50% threshold.
Yes, I was looking into comparing to at historical averages. But guess, what NZ does not publish data by date of death age, and month (or week). Unbelievable!
This plot shows that if you look at the CMR within age groups before COVID, there was a heavily decreasing trend in elderly age groups: https://i.ibb.co/gFHJf4V/ons-vs-england-general-population-mortality-rate-2015-to-2023.png. So it doesn't make sense to use the CMR in 2016 as the baseline.
For example in ages 80-89, when I did a linear regression for the CMR in 2015-2019 and I extended the trend to 2022, the average CMR in 2022 was about 6764. But you used 8500 as your historical CMR for ages 80-89.
I now also made line plots similar to the plots in your Substack post, except I'm using the monthly CMR of the general English population as the baseline and not the CMR in 2016: sars2.net/stat.html#Make_multiple_line_plots_for_CMR_by_age_group.
My plots show that in ages 18-39, 40-49, and 50-59, the people who are included in the ONS dataset have much lower CMR than the general English population. It might be because unvaccinated people are underrepresented in the ONS dataset and unvaccinated people have a higher mortality rate than vaccinated people.
However in the three highest age groups, there is not much difference between the general English population and the people who are included in the ONS dataset.
In table 9, the column labeled "Historical mortality rate in 2016 (approximate)" seems to be quite far off from the actual mortality rates in England in 2016. For example you listed the mortality rate for ages 70-79 as 3000 but I got 2547 instead:
> download.file("https://www.ons.gov.uk/file?uri=/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/adhocs/1343dailydeathsbydateofoccurrence1stjune2014to31stmay2023bysingleyearofageengland/dailydeaths2014to2023england.xlsx","dailydeaths2014to2023england.xlsx")
> dead=as.data.frame(readxl::read_excel("dailydeaths2014to2023england.xlsx",sheet=4,range="A6:CP3293"))
> dead=rowsum(dead[,-(1:3)],dead$Year)
> pop=read.csv("https://sars2.net/f/englandpop.csv",row.names=1)
> cut=cut(0:90,c(18,seq(40,90,10),Inf),,T,F)
> round(tapply(unlist(dead["2016",]),cut,sum)/tapply(unlist(pop["2016",]),cut,sum)*1e5)
[18,40) [40,50) [50,60) [60,70) [70,80) [80,90) [90,Inf]
56 176 391 985 2547 7826 21634
Table 9 also showed that in February to May 2022 in unvaccinated people in ages 18-39, the CMR increased from about 21 in the July 2022 version to about 29 in the February 2023 version. I also got about 21 as the mortality rate in the July 2022 version, but it was about 44 in the February 2023 version and about 53 in the August 2023 version. The mortality rate in the February 2023 version should be (99+91+78+87)/(192631+210888+202665+208452)*1e5. So you may have made some error.
---
In the plot from the mysterious colleague who wishes to remain anonymous, the reason why the increase to the previously reported ASMR values was bigger in unvaccinated people than vaccinated people was probably because unvaccinated people are younger than vaccinated people and younger people have a longer registration delay than elderly people. If the August 2023 version is compared to the February 2023 version, unvaccinated people also have a bigger increase to the previously reported ASMR values than ever vaccinated people: https://i.ibb.co/MNSzjdn/ons-unvaccinated-vs-ever-vaccinated-asmr-three-versions.png.
Table 9 shows that in ages 60-69 in February to May 2022, the mortality rate decreased from 1061 in the July 2022 version to 906 in the February 2023 version.
I also got 1061 as the mortality rate in the July 2022 version but in the February 2023 version it increased to 1354:
> t=read.csv("http://sars2.net/f/ons-table-2-2023-february.csv",na.strings=c("x","<3"))
> t=t[t$year==2022&t$month%in%month.name[2:5]&t$cause=="All causes",]
> a=aggregate(t[,6:7],list(age=t$age,vaccinated=t$status!="Unvaccinated"),sum,na.rm=T)
> a$cmr=a$dead/a$pop*1e5
> a
---
Your post also includes a plot which shows that in ages 18-39 in April 2021, the mortality rate was about 59 in vaccinated people and 32 in unvaccinated people (based on eyeballing from the plot). However actually it should've been about 88 in vaccinated people and 33 in unvaccinated people based on the February 2023 version, or about 90 and 35 based on the August 2023 version which I used here: sars2.net/stat.html#Plot_CMR_and_excess_mortality_by_age_group. The figure of 88 is from (18+194+19+15)/(40183+166571+42438+30337)*1e5.
Hi Mongol
Have you considered getting a substack of your own?
Whilst it is important that all voices be heard this constant tail gateing makes for a difficult reading experience.
It would also bring with it the advantage that you could express your own ideas and conclusions more comprehensively than on a github account.
No, I can't stand modern websites, and sites like Substack and Medium are even worse than earlier blogging platforms. Oldschool static websites are better. And Substack doesn't even support Markdown, but I can easily edit my website as Markdown files in Emacs. But I'll maybe add a dedicated page about the ONS data on my website.
Emacs. Not using vi?
Party like its 1976!
Can you recheck your calculation for the mortality rates in February to May 2022 in the February 2023 release? For example you got 29 as the mortality rate for unvaccinated people in ages 18-39, but I think it should be about 44:
t=read.csv("http://sars2.net/f/ons-table-2-2023-february.csv",na.strings=c("x","<3"))
t=t[t$year==2022&t$month%in%month.name[2:5]&t$cause=="All causes",]
a=aggregate(t[,6:7],list(age=t$age,vaccinated=t$status!="Unvaccinated"),sum,na.rm=T)
a$cmr=a$dead/a$pop*1e5
a
This is interesting. Thanks for doing this but admittedly I'm troubled. I'm only coming from a layman's perspective but the phrase "no significant difference" seems to explain away massive deaths from the Covid-19 vaccines. Looking at the initial graph, it seems about 45 extra people per 100,000 died in that 15 month period post 2021 - not a lot but raising it to the population vaccinated size of New Zealand (let's say 80%) of a 5 million populace or so, that yields 1,800 deaths.
Now with 45 per 100,000 being insignificant, let's apply this insignificance to the UK (again let's just say 80% vaxxed). With a population of 67 million, there's now a real problem. The problem is 24,120 extra deaths. No significant difference?
And the USA at 332 million population? We now have 119,520 deaths resulting from that small difference starting at 45 per 100,000.
If a gas explosion wiped out a small city and Joe Biden rocked up and said, don't, worry, it's not significant, we have 20,000 settlements in the US, that's only 6 people extra dying per settlement, it's not a problem, I think there would be a problem!
I'm not actually a maths guy tbh, so there's a chance I've made a dreadfully embarrassing mistake and perhaps my working is not perfect but there seems to be big trouble with this phrase from my perspective. Please tell me where I am going wrong?
You're right. I was looking at it more from a point of efficacy. From the evidence I've seen, there cannot be any real world efficacy, and that alone is enough. We know the shot kills. It must be pulled immediately.
No worries, now I understand. Appreciate you are trying a different way in to get them to stop. Cheers
Can’t wait til you finally follow my year-plus-old advice and do a U.S. County dashboard
Also global cities
Gonna be epic
Yes, It's not as straightforward, as it's a lot of data, but I am working on it, when I'm not held up by other things, like this study ;)
Believe me, I get it :)
As someone said to me if you are in a resthome it was probably mandatory to get the vaxx. I had a couple of looks at the NZ data myself and my analysis definitely indicated a higher death rate over 60.
Death notices in the NZ Herald (goes against the narrative of more deaths a little)
https://plebeianresistance.substack.com/p/death-notices-in-the-nz-herald-over
The NZ Mortality data
https://plebeianresistance.substack.com/p/the-nz-mortality-data
2022 mortality in NZ compared to 2010 (indicates that older people are dying from the jabs)
https://plebeianresistance.substack.com/p/2022-mortality-in-nz-compared-to
There were more people in elderly age groups in 2022 than in 2010. When I looked at mortality rates and not the raw number of deaths, I got a lower mortality rate in 2022 than 2010 in most 10-year age groups, with the exception of 50-59, 80-89, and 90+: sars2.net/moar.html#The_Real_Truthers_wager_for_his_entire_life_and_any_amount_of_money_and_his_Twitter_account.
But most developed countries have a decreasing trend in mortality rate within age groups, so maybe it would make more sense to use the prepandemic trend as the baseline for each age group (or to use the average mortality rate in 2015-2019 as the baseline so it's not as far from the COVID era as the year 2010).
It was Chris Johnson who raised the FOI request.
Yes, the issues in curating interpolation methodology subreferencing age-stratified disaggregation interpolation v age-standardized age/vaccination datasets... ‘Tis a bother innit.
It would help if our nz min health here were honest & data not fraudulent- & then they wouldnt have to go after barry young would they.
I prefer to trust my eyeballs out here in the real world, & here in nz two boyhood mates- infinitely fitter & healthier than moi- snuffed it to rapid cancers post vax, not seeing 65. We all have many such stories.
“Covid?” Sorry mate, you’ll have to explain that one.
My family didnt get vaxed, never masked or locked down- instead cheek by jowl with tens thousands other un-jabbed freedom fighters at rallies from auckland to wellington
... & never had your “covid.”
& all those we know got vaxed get “covid” every other week. A constant talking point for them.
Add philip buckler’s 714 page ‘book on masks’ to yr reading lists. Even more refs confirming masking ails mis-diagnosed as “covid” or “long covid.”
I have read enough OIA’s to know everything coming from our govt is fake. “Data manipulation” too tame a phrase. Same issue here as poms with their ONS.
Dear Ben, thanks for your great work with numerous interesting findings. I notice that in the cumulative mortality graph, the differences increase during winter in the southern hemisphere (~ July). Because of the strong age dependence of the seasonal waves, this is most likely related to age differences in the vaccination rate. Aggregations over 10-20 year age cohorts probably do not resolve this accurately enough, because mortality is exponentially age-dependent (above 30 years of age), while vax quote is not.
You can at least partially solve this with an interpolation using the base points available from the data (I do this in my estimation of weekly life expectancies from rough age cohorts, and it works quite well).
It is possible that the difference would then disappear completely.
so you're suggesting, to interpolate the death data as well to single age years?
Yes, exactly. In each age cohort, vaccination rates and mortality rates obey a different age function. While mortality follows a geometric progression, the vaccination rate, for example, increases linearly. Assuming that the risk of death increases by 10% per year, the mean age of those vaccinated within a 10-year cohort differs by around 3 years from that of those who have died. In my humble opinion, this requires a corrective calculation.
Translated with DeepL.com (free version)