Did the vaccine save 20 million lives?

Hypothetical models with wrong assumptions cannot prove any causality.

Jan 22

Eric Feigl-Ding, and others, spreads vaccine propaganda with supposedly scientific models. I explain why this is clearly unscientific.

Eric Feigl-Ding @DrEricDing

8) to be absolutely clear—vaccines averted 14 million #COVID19 deaths to 20 million excess deaths during the pandemic. Don’t spin anything anti-vaccine please. Vaccines save lives. But now we need updates vaccines to save more lives against #BA4 & #BA5. thelancet.com/journals/lanin…

In less than an hour and with a few lines of R code, I recreated a similar model - which is based on false assumptions.

So how does it work? Quite simple, it is based on the - never scientifically proven - assumption that vaccination protects ~90% from death. This allows us to create a model that calculates the case fatality rate (CFR) with no assumed vaccine effect.

Here I used a Vaccine Efficacy (VE) against death of 90%. CDC, currently, lists 94% on their website.

With this modeled CFR, we can now calculate how many people - supposedly - would have died without vaccination. We can see, that the model predicted 3.9M deaths without vaccination for the US. That implies, that vaccination saved almost 3.1M lives. Of course, it's a MODEL, and cannot predict or prove what would’ve really happened.

In summary:

The claim that vaccination protects against death has never been scientifically proven.
How the pandemic would have developed without vaccines remains unclear.
Only a comparison of all-cause mortality between vaccinated/unvaccinated could prove an effect.
The case numbers do not rely on a statistically representative sample. These are clearly influenced by the number of tests, who was tested and other factors...

Prof. Norman Fenton @profnfenton, also explains well, why these models are obviously flawed: