COVID-19 vaccination data from the province of Ontario, Canada reports that the 7-day moving average of infection rates in people who are fully vaxed and boosted is 17.18 cases per 100,000 people, compared to 9.19 cases per 100,000 people in those who are not fully vaxed. These data show almost twice the rate of COVID-19 infections in the people receiving the most COVID-19 vaccines, flipping the expectations of vaccine effectiveness on its head. At long last, it appears that the observational evidence is now coming in supporting research findings of approximately one percent vaccine efficacy in the COVID-19 mRNA vaccine clinical trials: Outcome Reporting Bias in COVID-19 mRNA Vaccine Clinical Trials.

But at least the vaccines are keeping people out of hospitals, preventing severe cases, and helping people avoid death, right? Not so fast. The next few weeks in Ontario are likely to provide crucial data on just those expectations.

In the meantime, consider this: data from randomized controlled trials is considered the gold standard of public health evidence. By contrast, observational evidence of how effective the vaccines appear in public depends on a much lower standard of evidence which can’t control all confounding factors.

Controlling confounding factors is accomplished through randomization of participants in a clinical trial. If the gold standard evidence of a randomized controlled trial shows that the vaccines can’t even prevent minor infections, how can the vaccines possibly prevent more serious infections, hospitalizations, and deaths?