Dr. Julie Ponesse speaks with former physics professor Denis Rancourt about the recent CMAJ study that unfairly attacks and degrades the unvaccinated population.
On April 25, 2022, the following study was published in the Canadian Medical Association Journal(CMAJ): “Impact of population mixing between vaccinated and unvaccinated subpopulations on infectious disease dynamics: implications for SARS-CoV-2 transmission.” The mainstream news stories that resulted from this study emphasized that the unvaccinated are dangerous and should be feared, which further strengthened the COVID-19 narrative.
I spoke with Denis Rancourt, former physics professor and current researcher at the Ontario Civil Liberties Association (OCLA), to get a better understanding of the study and to learn whether or not the statements being made by the mainstream media were correct. Denis, along with Joseph Hickey, wrote an article published on the OCLA website critiquing what they believe are some fundamental flaws in the study.
During our conversation, we discuss the complexities of the study and how they can easily lead, especially those without a scientific background, to a great deal of misinterpretation. One of the very complicated aspects of this study is that it uses medical modelling to essentially create a simulation of what is happening in the real world. The results of any simulation are highly dependent on the information that is inputted into the computer program used. Denis recites the popular computer science quote, “Garbage in, garbage out” to emphasize just how important the quality of the data used is to the outcome.
We discuss the critique Denis and his colleague have made on the structure of the model used in the study and how they believe there is a fundamental error in the model structure that reveals the main conclusion of the study (that the risk of infection among vaccinated people can be disproportionately attributed to unvaccinated people) is not accurately reflected in this model.
Denis describes how it would be very difficult for journalists to understand the modelling used in these studies and almost impossible for them to pick up on the fundamental criticism of the mathematical structure that he and his colleague point out.
We discuss where the data comes from that are used to derive the study parameters, which are then inputted into these medical models. Denis points out some of the numerical discrepancies used in the study to reflect community transmission and vaccine efficacy.
We also touch on the biases conveyed by the scientists who openly reveal their point of view around limiting freedoms, as opposed to just presenting the scientific results.
Finally, we look at some of the bigger societal powers and influencers at play and how narratives purposely get created and followed, especially when there are economic incentives or benefits to status involved.