Throwback: Ontario's manipulated COVID data

Or how we can know for sure intent to lie to the public existed.

Regular readers will notice I have, for the most part, stayed away from COVID data lately. Aside from the fact that governments have taken taken a black marker to anything the least bit revealing, I also feel like that battle has been won. The vaccine enthusiasts are not going to concede that their miracle drug was not, in fact, a miracle drug. Reasonable people, on the other hand, now either freely admit that the vaccines did not live up to the hype or at least they do not care anymore. Additionally, punishing the data manipulating public health officials has always been a pipe dream partly because evidence of intent is finicky.

For example, is it reasonable to suspect that public health officials knew including those vaccinated less than 14 days ago in the same category with the unvaccinated was data malpractice (for multiple reasons)? Yes.

Can we prove that? Well, probably not.

There may not even be an evidence trail. More likely, public health officials just followed Pfizer’s lead on misclassifying the data. It is not unreasonable to assume that most people in public health completely lack the ability to see the myriad of problems that come with introducing a known bias into their calculations. That’s the difficultly in determining intent when reflecting on the gross data errors that occurred during the pandemic. While the errors by-and-large only went one way, they have the benefit of claiming reasonable doubt for any one error.

However, there was one case that will always stand out to me: the case of Ontario’s data fraud. I’ve written about this previously, but I wanted to circle back to it. The thing about Ontario’s case is there is no room for reasonable doubt. If someone were to use freedom of information channels, they may even find a paper trail. Simply put, they got sloppy.

Looking at the most recent deaths by vaccination status data in Ontario, one might assume that the vaccine still has benefits against ‘severe disease’. According to the data, boosted people over the age of 60 are still four times less likely to die than unvaccinated people. That’s a result of smoke and mirrors, and the important part is we know why.

Until December 1st, 2021, Ontario was using 2021 population estimates to calculate the case rates by vaccination status. On December 1st, they started to use 2020 population estimates without explanation as to the rationale.

One of the notable features of their data prior to the change was that they broke down case rates by age groups above 60. In other words, there were case rates for the following age groups:

• 60-69;

• 70-79; and,

• 80 and older.

After the change, these three age groups were combined so that there were only case rates for those 60 and older. Combing the age groups was necessary when changing population estimates because using the 2020 population estimates meant that vaccination rates in those 70-79 and 80 and older were now greater than 100%. We can still observe this in Ontario’s data today. Despite the fact that almost no one new has taken a vaccine since last year, vaccination rates in those 70-79 are 101.1% and 103.3% for those over 80. In fact, Ontario claims that just 3,556¹ of those over 60 are not vaccinated in the entire province. In other words, case rates for the unvaccinated in those age groups taken alone would necessarily be considered undefined mathematically since the province considered zero people to be unvaccinated.

Screenshot of the data set available in Ontario’s Data Catalogue

Now, think about that for a second. They knew the numbers made no sense and made the change anyways. Someone actually sat down, looked at the numbers and asked themselves “How can I manipulate this data to cover up the fact that the conclusions are mathematically impossible?”

There is no other way to explain it. It is not something that can be attributed to an accident and it falls well outside the realm of reasonable doubt. By changing the population estimates, Ontario purposefully misled people who were using that information to try to make an informed decision on whether to get vaccinated or not.

If Ontario had chosen to use the July 2021 population estimates, they would currently consider 114,581 people over the age of 60 to be unvaccinated. With July 2022 population estimates, that number becomes 223,422. Both are orders of magnitude higher than the current estimate they are using to calculate rates².

Latest version of Ontario population estimates courtesy of Statistics Canada

We can argue about technicalities to get closer to the correct number, but the fact is they chose to use a number they knew was inaccurate in order to fool the public. The only question remaining is where does the beanstalk lead? Did someone order the data manipulated or was it the work of an activist public servant?

1. In fact, the number they are using may be an old population estimate which is 6,600 lower than the current 2020 estimate. So, even the 2020 estimates they are using lead one to believe that the case rates are almost three times higher than they should be.

2. It should be noted that only the 2022 population estimate has a higher population in those over the age of 80 than the current population they consider to be vaccinated, lending plausibility to that estimate.