A new preprint by Wilson N. Sy, PhD, Director of the Biotechnology Unit at Investment Analytics Research located in Australia, finds that excess deaths in Australia in 2021-2022 were likely due to mRNA injections, not COVID-19 mortality.
Summary of Key Facts
- Australian study entitled “Australian COVID-19 Pandemic: A Bradford Hill Analysis of Iatrogenic Excess Mortality” proposes that Australian excess deaths are caused by the COVID-19 vaccine.
- The author also suggests that influenza and pneumonia deaths were misclassified as COVID-19.
- A strong correlation (74 percent) was found between primary series doses and deaths five months later.
- This five-month lag was also found between booster doses and deaths.
- Other explanations for this correlation are also plausible.
At first, Sy didn’t intend to investigate the link between excess death and vaccination. He set out to assess whether the COVID-19 cases and deaths in Australia should be considered a “pandemic.” When investigating the excess deaths, the probable cause was also analyzed using the Bradford Hill criteria. His conclusion is provocative.
The Australian pandemic, Sy contends in his analysis, is caused by vaccination, not disease.
How to Define ‘Causation’
“In what circumstances can [one] pass from [an] observed association to a verdict of causation?”
Sir Austin Bradford Hill asked this insightful question when he gave the first President’s Address in 1965 to the Section on Occupational Medicine, which had just been formed.
His nine criteria to establish whether an observed epidemiological association is causal are now foundational principles in epidemiology. Causal inference is the potential association between exposure and disease—is it just coincidence, or is it likely that the exposure caused the disease?
The nine criteria are:
- Strength of association
- Temporality
- Biological gradient (or dose-response relationship)
- Consistency
- Specificity
- Plausibility
- Coherence
- Experiment (or reversal of disease with removal of exposure)
- Analogy (be accepting of weaker evidence for another or similar association if strong evidence exists for another related agent)
The Bradford Hill Criteria Applied to Australian Deaths
The Bradford Hill criteria, as applied by Sy, drew heavily on the first six criteria: strength, temporality, biological gradient, consistency, specificity, and plausibility.
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Strength
Finding a strong correlation may suggest a causal relationship between exposure and outcome. In this case, strength of association hinges on assessing the correlation between vaccine doses being administered and a surge in excess deaths.
Why might vaccination increase the risk of death? Sy suggests that there is a “pathogenic priming” whereby initial inflammation due to vaccination may cause death, and a lagged effect of immune suppression by boosters causing death later. This immune suppression could be caused by boosters via “antibody dependent enhancement” which makes the body less able to fight infection with antibodies, enabling viral entry into cells instead of blocking them.
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Temporality
The temporality argument is satisfied by a strong correlation (74 percent) between the initial vaccine doses and deaths.
This graphic also shows that the time period from the first dose to death lagged by five months, and the time lag between booster doses and deaths, also lagged by five months. (See Figure 8 below.)
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Biological Gradient
Another Bradford Hill criterion, biological gradient, is noted in the statistically significant correlation between the number of doses and the number of deaths. In other words, more doses equals more deaths. (See Figure 9 below.)
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Consistency
Consistency over time is complicated by varying data collection practices in other countries. A similar analysis was conducted using data from “Our World in Data,” using data by country, with average doses (percent of population vaccinated) compared to monthly excess deaths. A weaker correlation (31 percent) was found.
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Specificity
Specificity of the suspected causality is also important. Is there another competing explanation for the excess deaths? The vaccinated, Sy concludes, had approximately double the likelihood of death compared to the unvaccinated by mid-2022.
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Plausibility
Plausibility is substantiated by numerous studies showing the spike protein (coded by vaccines) can damage the heart, blood vessels, and the immune system.
Several Limitations
This paper raises interesting questions and provides a framework for considering the pressing question of excess mortality during the pandemic. This is a question being urgently considered in the United States as well.
However, while the paper applies a useful construct for evaluating excess mortality in Australia, it did not present a limitations section as is customary in an academic manuscript.
Several claims must be parsed before blame for excess deaths can be squarely placed on a vaccination campaign. The following findings were informed by consultation with an infectious disease expert having experience in disease classification at a large hospital during the pandemic.
1. Misclassification of Influenza and Pneumonia as COVID-19 Is Unlikely
The first limitation of this argument is the suggestion that influenza and pneumonia deaths were misclassified as COVID-19 deaths.
The social restrictions and contractions of society all but eliminated influenza during the winter of 2021–2022.
Although Sy disagrees, it is very unlikely that a positive polymerase chain reaction (PCR) test was picking up influenza or other endemic coronaviruses, as people sick with these common cold viruses are diagnosed frequently, according to infectious disease experts, even when they are negative for SARS-CoV-2.
It is very unlikely that a positive polymerase chain reaction (PCR) test was picking up other endemic coronaviruses, as people sick with these common cold viruses are diagnosed frequently, according to infectious disease experts, even when they are negative for SARS-CoV-2.
2. The Five-Month Lag May Not Be Solely Caused by Vaccine Adverse Events
The five-month lag between doses and deaths likely has more to do with immunity from vaccination waning than from a massive cluster of serious adverse events and immune suppression. Sy contends the primary cause of excess deaths is the lagged effect due to immune suppression causing vulnerability to disease rather than immediate adverse events associated with fatal inflammation.
The Australian government enforced strict lockdowns and mask-wearing from March 2020 up to the Delta wave that occurred in mid-2021. As Delta trailed off, a national vaccination campaign was initiated in September 2021, and within two months, 80 percent of the population had been fully vaccinated.
When Omicron surged in December 2021 and January 2022, a surge of cases occurred and continued spreading for much of 2022, as depicted below.
Given the strict lockdowns, an exponential increase in first infections should have been expected during the Omicron wave. Any residual protection from a September–October primary series based on the ancestral vaccine formula would be expected to wane against the immune-evasive Omicron variant over four to five months, leaving higher-risk people vulnerable precisely as Omicron emerged.
In fact, a recent meta-analysis of 65 studies published recently in The Lancet showed that natural immunity alone is more protective against hospitalization (approximately 90 percent through at least 10 months) than the bivalent booster (31 percent through 4 months), according to the latest data from the Centers for Disease Control (CDC), leaving those who were vaccinated, but lacking natural immunity from prior infection, vulnerable to Omicron.
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What should we make of the correlation between excess mortality and a five-month lag after vaccination? Within five months, antibodies have substantially waned and individuals are vulnerable to a primary (and necessary) infection. The Omicron variant was highly transmissible and immune evasive, capable of causing infection and severe disease, even among the vaccinated.
It’s possible that excess deaths were not seen during the lockdowns because the higher-risk individuals were less likely to be exposed, even though they had no immunity. Thus, despite vaccination, higher-risk individuals who eventually contracted Omicron when their antibodies waned, would be expected to disproportionately experience more serious illness.
3. Differing Cause of Death Definitions
Another challenge, not unique to this study, is to settle on a case definition of a COVID-19 death. In the United States, hospitals report their deaths to the state, after which the state may apply its own definition to count COVID deaths. For instance, one criterion might be a positive SARS-CoV-2 test within 30 days of death.
The CDC’s COVID Data Tracker, in turn, relies on these reports from states. However, the official CDC death toll (a different reporting system) relies on death certificate data, which is thought to be more accurate, although this has not yet been studied.
Some states, such as Massachusetts, have standardized a variety of metrics to differentiate admissions “from” versus “with” COVID-19. A positive PCR is indeed, not sufficient. However, not all states have standardized an algorithm to count COVID deaths reported by hospitals, and the potentially more accurate death certificate data is often lagging because it requires coroner review.
◇ References:
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Hill AB. The Environment and Disease: Associate or Causation? Proceedings of the Royal Society of Medicine. 1965 May;58(5):295-300.
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UK Health Security Agency SARS-CoV-2 variants of concern and variants under investigation in England. Technical Briefing: Update on Hospitalization and Vaccine Effectiveness. for Omicron VOC-21NOV-01 (B.1.1.529)
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Schöley J, Karlinsky A, Kobak D, Tallack C. Conflicting COVID-19 Excess Mortality Estimates.Lancet. 2023;401(10375): 431-432.
COVID-19 Excess Mortality Collaborators. Estimating Excess Mortality Due to the COVID-19 Pandemic: a Systematic Analysis of COVID-19-Related Mortality, 2020–2021. Lancet. 2022; 399: 1513-1536
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