Ontario and the great DENOMINATOR LIE

Or how Ontario doctors the case rate numbers.

Great care must be taken when dealing with government data. People often hold the false belief that just because someone, somewhere in the government could theoretically pull the aggregated health card data from every person living in Ontario and tell us with great accuracy the population demographics within the province, then the numbers must be built on the same data. That is not how government works. So when one of my dear readers noted the paradox of case rates by age in Ontario, my first instinct, without even looking at the data was that the assumptions they used to build their data were wrong. That’s not me being clever or even paranoid — that’s just good analytical advice from someone with a background in economics. Always start by attacking the assumptions because the assumptions are almost definitely wrong (at least in my field).

In this case, I recalled that Ontario was highly vaccinated in the oldest age groups. While it is relatively easy to estimate the amount of vaccinated people in the population, the amount of unvaccinated people is tricky because we are, ultimately, using estimates. When a certain population is highly vaccinated, errors in the estimates become more prominent and the data less reliable because the population of concern (unvaccinated people) can be easily under-reported.

Let’s look at how Ontario is making the vaccines look better than they really are.

First of all, what is the paradox?

(Credit to Ms. P: I had actually been taking the Ontario vaccination percentages at face value before she pointed this out)

In the Ontario data, the vaccinated and boosted have higher case rates in every single age group except those over the age of 60 where the trend inverts. In fact, the inversion is large, significant, and implausible. See the image below.

Well, here’s the rub. It seems implausible because the data has been manipulated as per usual. There is a simple reason for this, in fact. The unvaccinated population is grossly under-estimated because Ontario is using population estimates from 2020. They even rolled back their population estimates on December 1st in what can only be seen as an attempt to make the case rates in the vaccinated population look better. That’s right, throughout the entire omicron wave, even though the data showed the vaccine failing badly, things were actually worse than Ontario was reporting.

For perspective, here is vaccinations by age before the switch (this particular screenshot is from October 1st) where we can see 95.2% of those 80+ are fully vaccinated. At this time, they noted that 646,820 were fully vaccinated suggesting that the total population in this age group was approximately 679,432 (ie., 32,612 unvaccinated).

Yet, after the change, when only 13,069 more people in that age group were fully vaccinated, they claimed that 100% of that population was fully vaccinated.

Any time you see 100% of people being vaccinated, it is easy to spot a lie. The thing is… the roll back of the numbers is even worse. The first numbers were based on 2021 numbers and, with an aging population, that age group grows by 15-20,000 people every year. Instead of 0 people being unvaccinated in that age group as they are now suggesting, or 19,543 based on the 2021 number (32,612 originally unvaccinated-13,046 new vaccinations), the true number of unvaccinated may be nearly 35-40,000. Ontario, in other words, has doctored the numbers so it is impossible for the unvaccinated to have lower case rates in that age group. This is not limited to those 80+, the population of interest, or those 60+, grows by over 100,000 on a yearly basis, so instead of 2.3% of that population being unvaccinated (or about 83,000), more like 7.7% of that population might be unvaccinated (or closer to 283,000)!!!

That is an ENORMOUS error.

The error would, of course, also be projected onto the entire population as a whole. Ontarios (vaccine eligible) population rises by over 200,000 nearly every year; though, the majority of the error would be concentrated in those 80+ as that age group is growing due to the age demographics rather than immigration (which may have been slowed due to the pandemic).

Do these people have no shame?