A study which was widely used to vilify unvaccinated individuals was not only flawed but its author had ties to Covid injection manufacturer Pfizer, according to new peer-reviewed research.
"During the COVID-19 pandemic, politicians, scientists and media organizations vilified unvaccinated people, blaming them for prolonging the pandemic and advocating policies that barred 'the unvaccinated' from public venues, businesses and their own workplaces," Brenda Baletti noted in a Dec. 22 analysis for The Defender.
Dr. David Fisman, a University of Toronto epidemiologist was the lead author of the April 2022 study in question. It was published in the Canadian Medical Association Journal (CMAJ) and claimed that unvaccinated people posed a disproportionate risk to vaccinated people.
Fisman told the media that the key message of the study was that the choice to get vaccinated is not merely personal because if you choose to be unvaccinated you are “creating risk for those around you.”
Compliant legacy media outlets ran with it.
Headlines like Salon’s, “Merely hanging out with unvaccinated puts the vaccinated at higher risk: study,” Forbes’ “Study Shows Unvaccinated People Are At Increased Risk Of Infecting The Vaccinated” or Medscape’s “My Choice? Unvaccinated Pose Outsize Risk to Vaccinated” proliferated in more than 100 outlets.
The Canadian Parliament used the study to impose restrictions on unvaccinated people.
But a new peer-reviewed study published in Cureus shows that the study by Fisman et al "was based on the application of flawed mathematical risk models that offer no scientific backing for such policies," Baletti wrote.
The new study also noted that Fisman has worked as an adviser to Pfizer, Seqirus, AstraZeneca, and Sanofi-Pasteur. He also advised the Canadian government on its Covid policies and recently was named to head up the University of Toronto’s new Institute for Pandemics.
In the new study, Joseph Hickey and Denis Rancourt show that Fisman’s “susceptible-infectious-recovered (SIR)” model, used to draw his conclusions on vaccinated vs. unvaccinated individuals, had a glaring flaw in one of its key parameters — contact frequency.
"When they adjusted that parameter to account for real-world data, the model produced a variety of contradictory outcomes, including one showing that segregating unvaccinated people can increase the epidemic severity among the vaccinated — the exact opposite of what Fisman et al purported to show," Baletti noted.
Hickey and Rancourt, researchers at Canada’s Correlation: Research in the Public Interest, concluded that without reliable empirical data to inform such SIR models, the models are “intrinsically limited” and should not be used as a basis for policy.
Fisman et al designed their study to measure the impacts of segregating two groups — vaccinated and unvaccinated people — applying a SIR model to predict whether the unvaccinated pose an undue risk to the vaccinated during a severe acute respiratory viral outbreak, based on variable degrees of mixing among the groups.
However the model, Hickey and Rancourt wrote, failed to consider the impacts of that segregation on “contact frequencies,” a key parameter in predicting epidemic outcomes.
Instead, it assumed contact frequencies among the majority (vaccinated) and socially excluded (unvaccinated) groups would be equal and constant, which “is not realistic,” Hickey told The Defender.
In other words, the model assumed the two groups would be separated, yet living the same parallel existence — socializing, working, shopping and coming into contact with others in exactly the same ways.
But in the real world, segregation meant the unvaccinated were barred from many public places, so their contact frequencies were severely curtailed.
Hickey and Rancourt implemented the SIR model again, testing for a degree of segregation that ranged from zero to complete segregation and allowing the contact frequencies for individuals in the two groups to vary with the degree of segregation.
When they ran the model using the more realistic estimation of how different segregation policies might generate different contact frequencies among the two groups, “we found the results are all over the map,” Hickey said.
By segregating unvaccinated people from the vaccinated majority, he said, “You can have an increase in the attack rate among vaccinated people or you can have a decrease.”
“Negative epidemiological consequences can occur for either segregated group, irrespective of the deleterious health impacts of the policies themselves,” they wrote.
Hickey said the variable outcomes were very sensitive to the values of the parameters in the model, namely infectious contact frequency.
But he said, in the real world there are no reliable measures for contact frequency, and without reliable measures for model inputs, the model is essentially meaningless.
They concluded that the degree of uncertainty is so high in such SIR models that they cannot reasonably inform policy decisions.
“It’s a policy based on nothing basically,” Hickey said.
Rancourt tweeted a link to the study results along with a montage of pandemic-era media clips scapegoating unvaccinated people.
The latest rigorous peer-reviewed science has now proven that these (video clip) despicable global-parasite pronouncements were wrong (=disinformation), and were therefore evil given the widespread harm caused... MEDIA NOTICE ABOUT THE ACTUAL SCIENCE: https://t.co/FrXJGWaCsF h/t… pic.twitter.com/xyV8ksCtiH
— Denis Rancourt (@denisrancourt) December 18, 2023
Publishers and Citizen Journalists: Start your Engines
