Ontario hospitalization data by 'vaccination' status

If you are INJECTED (that's a verb) then you are INJECTED.

With data like these tracking hospitalizations per group (‘vaccinated’ vs ‘unvaccinated’), it is vital TO PROPERLY CLASSIFY THE GROUPS so that they are distinct are true representations of each group. We are not measuring antibody or T cell responses here: we are counting the number of hospitalizations post INJECTION. Post means after. So bloody count them right, will ya? They aren’t. They classify ‘unvaccinated’ people as being injected (1-13 days out). Sorry, I blew the punchline. Keep reading.

Please head to the Province of Ontario’s (my homeland :)) website where you will be able to see and even download COVID-19 Vaccine Data. It’s quite illuminating. The file that I chose to download, since the ‘case’ data is crap in my opinion (and always will be), was the second one down entitled “Hospitalizations by vaccination status” which can be found here. I thought that it was pretty strange that they wrote the following. Why won’t they be publishing hospitalization by injection status data as of June 23, 2022? Not looking good for your products, eh?

Figure 1: Hospitalizations by injection status according to Ontario Data Catalogue. https://data.ontario.ca/en/dataset/covid-19-vaccine-data-in-ontario/resource/274b819c-5d69-4539-a4db-f2950794138c

They correctly point out that:

Comparing groups using count data (such as the number of patients) is appropriate when the groups being compared are about the same size (i.e. around mid-2021). However, now that approximately 87% of eligible Ontarians are fully vaccinated (compared to 3% partially vaccinated and 10% unvaccinated) this comparison is no longer appropriate and may be misleading.

so let’s make sure we show both charts. The population of Ontario was approximately 14,826,276 as of 2021 Q3. I calculated the percentages of injected (and uninjected) rates for the normalization using their numbers for ‘total_individual_fully_vaccinated’ people as per respective date. I subtracted the number of fully injected people from the total population to get the number of uninjected people. It’s not a perfect way to do it since there is this subpopulation of ‘partially injected’ people, but I am sure it’s more than an adequate estimate. At the end of the day, on June 30, 2022, by my calculations using their numbers, 82.5% were fully injected and 17.5% were not. This calculation of 17.5% certainly includes people with 1 injection. So in order to be as similar to their estimates as possible, I made sure the percentage uninjected by June 30, 2022 was indeed their estimated 10% (10.7% to be nit-picky.) The remainder are the quasi-injected. Oy.

First, let’s plot the absolute counts. I always like to do this.

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Figure 2: Data from the province of Ontario’s Data Catalogue showing hospitalizations for individuals who are uninjected and fully injected (at least 2 doses).

The absolute counts paint a picture of failed injectable products with regard to reducing hospitalizations which - would clearly be the case if the injected and uninjected populations were about the same size - which they unfortunately are not. Unfortunately because so many people ‘chose’ to inject themselves. It would also be clear that individuals who chose the natural immunity course would win. But the populations are not the same size. So let’s normalize and see what we get.

Figure 3: Data from the province of Ontario’s Data Catalogue showing hospitalizations for individuals who are uninjected and fully injected (at least 2 doses) normalized to uninjected and injected counts, respectively.

The weird black-fancy lines are the percentages of injected (top) and uninjected (bottom) individuals in the context of the normalized counts per hundred thousand injected or uninjected individuals, respectively. Before I tell of my observations take note that the data owners define ‘unvaccinated’ people as not having been injected at all OR injected and in the bloody 0-13 day window! Oy oy! They actually wrote it down! So potentially, ALL of the hospitalization data from the ‘unvaccinated’ group actually represent INJECTED individuals!

Figure 4: A Percentage (perhaps 100%!) of ‘Unvaccinated’ people are actually injected. https://data.ontario.ca/dataset/covid-19-vaccine-data-in-ontario

Now, to me, if I take this data at face value, I see 4 things:

1. The patterns of hospitalizations are the same, meaning, the cause is likely the same. SARS? Omicron? We know one thing that is not the shared root cause, right? It’s not due to the injections. Right? Unless, they misclassified what an uninjected person is in the hospital, or as per their stupid definition. If you have one dose up until 13 days (inclusive), then you are counted as UNINJECTED and put into the ‘unvaccinated’ group! I have written about this many times.)

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2. The counts are low for both groups (about 1/2,857 for the uninjected at peak values), but, these odds are still favorable when considering the rate of severe adverse event (SAE) reports per 100,000 in VAERS ((1/1,826 - only double-dosed Domestic data) in the context of the COVID-19 injectable products.

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   This is without considering the Under Reporting Factor (URF). If we consider an URF of 31 (how beautiful is it that I calculated this from Pfizer’s SAE rate from their clinical trial?
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   ), then this likelihood becomes 1/59. A 1/59 chance of succumbing to death, a life threatening event, disability, birth defect, an ER/ICU visit or… hospitalization. That’s a lot worse than the 1/2,857 chance of being hospitalized (presumably) with COVID-19 going the natural immunity route. Let’s play Devil’s Advocate, if the injection injury rates are so high, then wouldn’t this translate into more hospitalizations for the injected in the data, he would ask? Good question! Answer: The injected (and their doctors) are NOT encouraged (in fact it is discouraged) to associate the ‘vaccine’ injuries with ‘vaccines’ and thus, they are not reported as such. I would say the reporting rate is almost 0 for acknowledged injuries.

3. The peak rates are very similar between the groups, especially in the second peak. I imagine the 2 peaks are Omicron and Omicron the sequel. Not sure.

4. By June, the rates are approximately the same which begs the question, what will the trend be in the future? Will the uninjected win the race?

According to this data source, they won’t be publishing anymore case or hospitalization (by injection status) data so, we won’t be allowed to know. I can’t stress how VERY dangerous ignoring this data is.

What do you see?

I see ‘unvaccinated’ data that is impostering ‘vaccinated’ data. Which makes this stupid. Just for fun, I swapped 80% of ‘unvaccinated’ data to the ‘vaccinated’ data group and replotted it. I believe firmly that this is how the data looks in reality and that the injected are hospitalized far more than the truly uninjected.

Figure 5: Figure 4 and Figure data with the uninjected group represented by an 80% reduction in absolute count to attribute for the individuals who were, in fact, INJECTED.

How many more times do we have to show the same thing with entirely different international government databases?

1. I do find it odd that there is data post June 23rd published here. But it’s not like the people putting out data don’t contradict themselves all the time.

2. Pierre Kory has a lot to tell the world about this.

3. https://usafacts.org/visualizations/covid-vaccine-tracker-states/

4. Rose, J. 2021, Critical Appraisal of VAERS Pharmacovigilance: Is
the U.S. Vaccine Adverse Events Reporting System (VAERS) a Functioning Pharmacovigilance System? Science, Public Health Policy & the Law
Volume 3:100–129.