in Featured World News Vaccines Were Supposed to End the Pandemic. Excess Death Figures Tell a Different Story
Guest Post by Michael Tomlinson
The reality is that waves of infection and excess mortality continued after the deployment of the COVID-19 vaccines during 2021, continuing with two severe waves in the U.S., and peaking again at the end of January the following year.
he grand strategy (which as I have said before was neither grand nor strategic) was to lock down the population of whole countries as an interim measure “until a vaccine becomes available.”
This was a novel (and completely unproven) strategy to defeat a supposedly completely novel virus, on the grounds that no human had ever encountered anything like SARS-CoV-2 before so no one would have any preexisting immunity to it.
But the clue is in the name — SARS-CoV-2 was named after SARS to which it was closely related, sharing approximately 79% of its genome sequence according to this paper in Nature.
It is situated within a cluster of coronaviruses, and another Nature paper discussed the extent of cross-reactivity with these including the common cold viruses, and even with other families of viruses altogether. It was somewhat novel, but not unique.
So, policymakers should have been skeptical about the claims made early in 2020 that SARS-CoV-2 would produce extreme levels of mortality.
This has consequential implications for the claims that the grand strategy was a success because these levels of mortality did not eventuate. If they were never going to happen, then we did not need to be saved from them.
The deployment of vaccines was supposed to bring about “the end of the pandemic.” The clinical trials of the vaccines purportedly showed they could reduce symptomatic infections by over 90%.
At the population level, this does not add up. If over 90% of infections were supposed to be prevented by vaccination, and 270 million people in the U.S. population had been vaccinated by the end of May 2023 (out of a total population of around 340 million), then how come there were over 100 million confirmed cases by then, according to Our World in Data?
It defies belief that nearly 100 million of the unvaccinated 170 million were the ones infected. Particularly as a study by the Cleveland Clinic showed that on average the more vaccinations people had, the more likely they were to be infected:
It was assumed there would be a consequential reduction in mortality from reducing infections (which in any case does not appear to have happened), but the clinical trials did not show any differences in mortality between the groups exposed to the vaccines and the placebo groups.
The orthodox defense is that they were not powered sufficiently to detect any differences as the trial populations were not large enough.
But by the same token, we are entitled to draw the following conclusion: the clinical trials did not demonstrate the vaccines’ ability to reduce mortality.
In the quality assurance business, we evaluate the success of an intervention or program by comparing the actual outcomes with the claims made.
The reality is that waves of infection and excess mortality continued after the deployment of the vaccines during 2021, continuing with two severe waves in the U.S., and peaking again at the end of January the following year.
There was a trend of declining peaks, but it is not evident that this trend changed as a result of the vaccination campaign, as would be expected over the course of any pandemic.
Conventional wisdom would have us believe that the vaccines, while they may not have reduced overall levels of infection, somehow reduced levels of hospitalization and mortality from COVID-19.
Again, it defies belief that vaccination could be deficient in preventing infection and still be successful in reducing illness.
These claims of success do not rest on hard evidence.
A number of recent papers are smoking guns that show us that the grand strategy did not work. We need to look beneath the hood, however (to switch metaphors), because the narrative usually concludes that the strategy was a success.
The data however sometimes tell a different story. This shows that the authors are biased, and their data can be more reliable than their narratives.
Take, for example, a study by Bajema et al. based on patients of the U.S. Veterans Health Administration. They concluded:
“This cohort study showed that, during the 2022 to 2023 season, infection with SARS-CoV-2 was associated with more severe disease outcomes than influenza or RSV, whereas differences were less pronounced during the 2023 to 2024 season.
“During both seasons, RSV remained a milder illness, whereas COVID-19 was associated with higher long-term mortality. Vaccination attenuated differences in disease severity and long-term mortality.”
This seems conclusive, doesn’t it?
But the conclusions are based on the data summarised in Figure 2A, which includes: