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'Definite causal link' between all-cause mortality and Covid vaccine rollouts
A new study of 17 countries finds vaccines associated with net harm
“The COVID-19 vaccines did not save lives and appear to be lethal toxic agents.”
This is the strident position of a new paper by Denis Rancourt et al., analysing all-cause mortality (ACM) in 17 countries in the Southern Hemisphere and equatorial region.
The authors find a “definite causal link” between peaks in all-cause mortality and rapid vaccine rollouts across four continents and a broad range of vaccine products, inlcuding the mRNAs, Covaxin, Sinovac and Johnson & Johnson.
The paper, which is 180 pages long and is yet to be peer-reviewed,* attempts to quantify the fatal toxicity risk per injection, which appears to be “exceedingly large in the most elderly.”
The authors conclude that, “governments should immediately end the policy of prioritizing elderly people for COVID-19 injection.”
All-cause mortality best metric to measure effect of vaccines at population level
It has been proposed by experts, including Professors Martin Neil and Norman Fenton, that the most accurate way to measure the risks and benefits of Covid vaccines is to compare the ACM of vaccinated against unvaccinated, “since it not only avoids most confounders relating to case definition but also fulfils the WHO/CDC definition of "vaccine effectiveness" for mortality.”
There is a dearth of ACM data stratified by vaccination status, so Rancourt et al. take a variation on the ACM approach - analysing ACM mortality peaks at population-level across multiple countries.
The authors state, ”All-cause mortality by time is the most reliable data for detecting and epidemiologically characterizing events causing death, and for gauging the population-level impact of any surge or collapse in deaths from any cause.”
The countries analysed in this paper include Argentina, Australia, Bolivia, Brazil, Chile, Colombia, Ecuador, Malaysia, New Zealand, Paraguay, Peru, Philippines, Singapore, South Africa, Suriname, Thailand, Uruguay, all within the Southern Hemisphere and/or equatorial region.
Vaccine-dose fatality rate (vDFR)
The authors set out to calculate the vaccine-dose fatality rate (vDFR), arriving at a figure of approximately 0.05 % (1 death per 2,000 injections). However, this number is exponential with age. From analysis of age stratified data from Australia and Israel, the authors find that the vDFR doubles at every additional five years of age, reaching approximately 1% for those 80 years old and over.
“The clearest example is that of a relatively sharp ACM peak occurring in January- February 2022 in Australia, which is synchronous with the rapid rollout of Australia’s dose 3 of the COVID-19 vaccine; occurring in 5 of 8 of the Australian states and in all of the more-elderly age groups,” state the authors.
One might argue that for the Australian analysis, the sharp peak in ACM ties in with the spread of Covid throughout populations for the first time (particularly in Western Australia, Queensland and South Australia) and that therefore these deaths are Covid deaths, not vaccine deaths. I am not convinced that Rancourt has sufficiently addressed this counter point in his previous papers on Australian ACM.
However, an analysis of Queensland mortality data by Dr Andrew Madry showing the start of the upward trend in ACM at the primary series rollout, and nine months before the spread of Covid in the community, lends weight to the authors’ hypothesis.
There are other Australian data points that provide additional support to the thesis that the vaccines were not working as advertised, and were doing damage to the health of Australians, and possibly driving ACM. These include:
The fact that most Queensland Covid deaths were fully vaccinated (and some boosted) when the state borders first opened in December 2021/January 2022;
Excess deaths were recorded in Australian states in 2021 when the vaccine rollout was in full swing, but many states had no Covid;
Unprecedented high rates of adverse event reporting in relation to Covid vaccines in Western Australia in 2021, when most of the population was vaccinated, but there was no Covid. 57% of those who reported an adverse event presented at hospital, suggesting the severe nature of the events.
New South Wales data showing that those with more doses of vaccination died or presented in hospital and ICU with Covid at higher rates than those with 0-2 doses. These data were not age stratified and so cannot be taken to categorically indicate negative vaccine effectiveness, but no one in the Department of Health has been able or willing to demonstrate effectiveness by publishing the full age stratified data. In fact, they have gone to extraordinary lengths not to.
A Bradford Hill Analysis of Australian ACM by analyst Dr Wilson Sy, from which he concluded, “Strength of correlation, consistency, specificity, temporality, and dose-response relationship are foremost Bradford Hill criteria which are satisfied by the data to suggest the iatrogenesis of the Australian pandemic, where excess deaths were largely caused by COVID-19 injections.”
However, I don’t want to get bogged down with Australia, because the larger point is that,
“In 9 of the 17 countries, there is no detectable excess mortality until the vaccines are rolled out… In the other 8 of the 17 countries, a new regime of higher mortality is initiated after 11 March 2020 and prior to any COVID-19 vaccine administration... In all 17 countries, vaccination is associated with a regime of high mortality, and there is no association in time between COVID-19 vaccination and proportionate reduction in ACM.”
The authors include many graphs demonstrating temporal association. They’re all variations on the below, for all 17 countries, by different methods of analysis.
Criteria for proving causality
The authors claim that the “robust criteria” set out by legendary scientist John Ioannidis are amply satisfied in their analysis:
“Experiment: The same phenomenon is independently observed in distinct jurisdictions, for distinct age groups, and at different times, which constitutes ample verification in independent real-world large-scale experiments.
“Temporality: The many step-wise increases and anomalous peaks in ACM are synchronous with vaccine rollouts; including in jurisdictions in which excess mortality did not occur until vaccination was implemented after approximately one year into the declared pandemic.
“Consistency: The phenomenon is qualitatively the same and of comparable magnitude each time it is observed.”
Therefore, “there can be little doubt that the mass COVID-19 vaccination campaigns caused the temporally associated excess mortality in the 17 countries of the present study, and in other countries studied to date,” they say.
Evidence in support of causal relationship between vaccines and ACM peaks
The authors refer to a plethora of evidence types in support of a causal relationship between the vaccine rollouts and ACM peaks:
Autopsies. A systematic review of 325 autopsies following deaths related to Covid vaccination up to 18 May 2023 found that, “a total of 240 deaths (73.9%) were independently adjudicated as directly due to or significantly contributed to by COVID-19 vaccination.”
Studies of vaccine-induced pathologies
An established causal link to vaccine-induced pathology, by histopathology and immunohistochemical staining of skin biopsy specimens
Secondary analysis of serious adverse events reported in placebo-controlled, industry phase III randomised clinical trials
More than 1,250 peer-reviewed publications about COVID-19 vaccine adverse effects
The known vaccine injury compensation programs of states worldwide, which include death resulting from the COVID-19 vaccines
While the above do not in themselves prove causality, but rather demonstrate plausible mechanisms and circumstances, the authors offer the the following to demonstrate the causal link, which is made in several population-level studies, including:
A survey study by Mark Skidmore (which was subsequently retracted due to intense pressure on the journal editors from parties who did not like his conclusion that, “With these survey data, the total number of fatalities due to COVID-19 inoculation may be as high as 278,000 when fatalities that may have occurred regardless of inoculation are removed.”)
Prior quantitative evaluations of vaccine dose fatality rate (vDFR) from
all-cause mortality (ACM) data in several countries (Rancourt, 2022; Rancourt et
al., 2022a, 2022b, 2023) (Access Rancourt’s papers here)
The authors state, “These findings are conclusive. The associations are numerous and systematic, and there are no counter examples. We have found no evidence in our extensive research on ACM that COVID-19 vaccines had any beneficial effect.”
Addressing counter arguments
The authors rebut several counter arguments, including that the ACM peaks are seasonal or are due to heat waves, earthquakes, other aggressive Covid countermeasures, underlying health conditions, or Covid infections.
While I am not completely satisfied with the authors’ rebuttal of the effects of countermeasures, they make a salient point in arguing why they do not believe that Covid waves could not be the driver of ACM in their analysis:
“Regarding the theory of emergence of one or more variant(s) of SARS-CoV-2, this emergence would have to cause simultaneous peaks and surges of mortality in 17 countries across 4 continents (Figure 1, Figure 2, Figure 4, Figure 11, Figure 14, Figure 18), which is a statistically impossible occurrence if we accept the theories of spontaneous viral mutations and contact spreading of viral respiratory diseases; and all the resulting peaks of mortality would have the remarkable coincidence of occurring precisely when vaccine boosters were rolled out.”
‘Vaccines saved 20 million lives’
Believers in Covid vaccine modelling will throw their hands in the air at this point, crying, ‘but Covid vaccines saved 20 million lives! Sure, ACM is up, but without the vaccines, ACM would have been way higher.’
Rancourt et al. don’t offer much of a rebuttal to this argument - presumably they think the association between vaccines and ACM peaks says it all.
However, others have weighed in on the matter, highlighting some glaring oversights. Most notably, the ‘20 million’ modelling paper relied on earlier Covid modelling on transmission, infection fatality rate and non medical interventions that real world data showed to be out by the order of 10-40 times. The study also underestimated the effects of natural immunity and overestimated vaccine efficacy.
Counterwise to the conclusions drawn by the modellers, an analysis of real world data from 108 countries worldwide found that countries with the highest rates of Covid vaccination also experienced the highest rates of Covid deaths, while the inverse was true of countries with low Covid vaccination rates.
Faulty data underestimates degree of harm
The authors suggest that the disparity between their findings and the official Covid data reported by governments and related surveillance bodies is because “adverse-effect monitoring, clinical trial reports, and death-certificate statistics greatly underestimate the fatal toxicity of the injections.”
I have reported extensively on these shortcomings in Australian data, including:
Double standards in the attribution of deaths to Covid (any demonstrable causal chain, even with the presence of multiple comorbidities = Covid death) vs. vaccines (no other underlying conditions, no other possible explanation, proved beyond a shadow of a doubt and confirmed by multiple parties including a coroner’s report = vaccine death)
Under reporting factor not accounted for in any official reporting of vaccine injuries and deaths
No proper follow up of reported injuries and deaths
Autopsies not required or recommended for deaths following vaccination
No active surveillance testing for subclinical harm
Medical censorship means medical professionals are both undereducated and strongly disincentivised to properly diagnose and report vaccine injuries
I have repeatedly criticised Australia’s peak actuarial body, the Actuaries Institute, for their strong bias towards explaining ACM away as Covid-related, while drastically underestimating vaccine effects. For example, the Actuaries attribute all causal chain deaths associated with Covid infection as Covid deaths, while at the same time taking the TGA’s claim that there have only been 14 deaths associated with the vaccines on face value, ignoring causal chain deaths such as Amy Sedgewick (Pfizer) and Caitlin Goetze (Pfizer).
There is also evidence of mucking around with death codes inflating Covid deaths and hiding vaccine deaths. For example, miscoding of vaccine deaths in Minnesota led to accusations of ‘data fraud’ towards the CDC.
Two waves of injury and death
Last week, in an address to EU Parliament, cardiologist, internist and epidemiologist Dr Peter McCullough said,
“There have been two waves of injury to the world. The first has been the SARS-CoV-2 infection, which preyed upon the frail and the elderly. And the second wave of injury now has been the COVID-19 vaccines.”
One explanation for the two waves is the phenomenon of ‘spikeopathy’, as elucidated in a recently published peer-reviewed article in the journal Biomedicines, titled 'Spikeopathy': COVID-19 Spike Protein Is Pathogenic, from Both Virus and Vaccine mRNA. ‘Spikeopathy’ refers to the toxic effects of the spike protein, whether confered by the SARS-CoV-2 virus, or produced by gene codes in mRNA and adenovector DNA vaccines.
The kicker is that the mRNA vaccines also introduce lipid nanoparticles (LNPs) to the body, which themselves are inflammatory, and which ferry spike-producing mRNA to parts of the body that the viral spike protein does not normally end up.
Dr McCullough has previously suggested that taking Covid ‘vaccinations’ increases risk of harm by increasing spike exposure. He suggests limiting spike exposure by avoiding the shots and using nasal washes as a prophylactic.
I read Rancourt as having a bias in focusing on vaccine harm at the exclusion of Covid infection harm, and am inclined to align more closely with Dr McCullough with his opinion that Covid and its vaccine ‘cure’ have both caused waves of injury and death - though the latter has likely caused the greater degree of harm.
Regardless, Rancourt and McCullough draw the same conclusion - the only appropriate response is to stop the shots.
Question for readers who are keen to engage:
How do you explain the existence of data sets/analyses which seem to directly contradict Rancourt’s findings, such as this analysis of ACM across multiple countries in which the author finds the vaccines to have been beneficial?
*Rancourt appears to not be bothered with the peer review process anymore, preferring to publish straight to his website. There are pros and cons to this, but in the current environment, when the integrity of medical journals is under the microscope and activist journos and academics are successfully lobbying for the retraction of research they don’t like (rather than honouring the scientific tradition of making public written rebuttals), it is understandable that some researchers are simply opting out.
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