Canada's biggest covid vaccine pusher believes that modeling is fact. This is the model that he presented to prove how many lives the covid vaccine saved:
Covid 19 vaccines prevented 14.4 million deaths..
Great study if you need something to confirm your own biases.
A scientific mind will question this study, though:
- In our effort to provide impact estimates globally, we introduced various assumptions into our model.
Interesting that they're making assumptions in a study published on June 23, 2022. They could have used actual real stats, as we're 2.5 years into this thing and the stats are plentifully available. Perhaps modeling is a way to present the vaccines better than they actually are to further the agenda of the author's bias?
- What kind of assumptions did the model make? Dozens, of which one particular one really stood out after a quick scan: we assume that all vaccinated individuals have a 50% reduction in infectiousness for breakthrough infections.
You're still pushing this in June, 2022, eh? When the assumptions are way off, the model will be way off.
- Now why would an author of a study misrepresent the numbers? Maybe there is a financial incentive for him to do so?
When Canada's biggest vaccine pusher posted this as his proof about how good the vaccine is, I told him that this is the type of study that would be funded by a company like Pfizer. Now, after a further inspection, I was wrong; it was funded partially by GlaxoSmithKline - The author received personal consultancy fees from GSK. The author is also on the Scientific Advisory Board at Moderna. Hmmm? Conflict of interest much?
But, yes, believe the modeling, just like retards believed this one.
EDIT: Tuchodi is having a fit. My criticism of this model is really bothering him. So I'm gonna throw out one more criticism to make him go crazy:
Models are used mainly to predict future outcomes, as was the case with this guy's model, which happened to be way off. There's no need to model past events when you already have ample statistics to report. Be wary of anybody modeling past events when they can directly report statistics.
Consider this analogy - Economists often model future macro economies. They're not often right, but they provide some indication as to where the economy is heading. Let's say they want to compare the past to the future. They can directly report past GDP, past unemployment rate, past inflation, etc and then create a model to compare it to future economies.
Economists don't model the past because they have actual statistics. If they did, we would supsect that they had an agenda, as modeling the past is unnecessary.
They made assumptions because there were no stats. Where would you suggest they get these non-existent stats?
Because it's true. "Vaccine reduces transmission in breakthrough cases" https://news.harvard.edu/gazette/story/2021/12/vaccinated-who-get-breakthrough-infections-less-contagious/ "secondary transmission of SARS-CoV-2 was significantly less common, and viable virus was detected for a shorter duration in fully vaccinated individuals than in partially vaccinated or unvaccinated individuals." https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2792598
lol
I specifically mentioned 2022 because that’s the current year.
So where are the stats you claim they didn't use?
And May 2022 isn't?
May, 2022, talking about the delta variant from last year, dummy.
So, like V&C1, you see dirty deeds being done if the study isn't published the day after the last sample/number is collected. Never mind that the data has to be collated, analyzed, discussed by the team, conclusions drawn, implications considered, report written / submitted / accepted, peer reviewed and perhaps revised after feedback, and eventually published.
Still waiting for those stats you claim they didn't use.