| There is a slippery joint conditional probability here. The article talks mostly of: Pd1 = Prob(death GIVEN infected AND vaccinated) vs Pd2 = Prob(death GIVEN infected AND NOT vaccinated) Which makes it easy to lose site of: Pi1 = Prob(infected GIVEN vaccinated) which is very very small compared to its opposite: Pi2 = Prob(infected GIVEN NOT vaccinated) Because Pi1 is so much smaller than Pi2 there are several consequences for Pd1 and Pd2: - The small counts for "numerator" of Pd1 (zero in some cases) means large uncertainty in the ratio and that the centroid of the distribution is not particularly meaningful. Statistical fluctuations (just one more or one less death) will change Pd1 substantially. - Statistically significant deviations between Pd1 and Pd2 do not point to a cause. For example, it could be that those contributing to Pd1 all got a much higher viral load in order for the virus to break through the vaccine's defenses and high viral loads are known to correlate with death so once vax protection is defeated it is game over. The distribution of viral load exposure may even be the same in the Pd2 case, but for the unvaccinated a lesser load can be fatal. This explanation is consistent with P1d possibly being greater than P2d AND consistent with the given anecdotes of vaccinated tweeters saying covid is just the flu, bro. The main take away is still: you do NOT want to get this shit and vaccine AND masking will help achieve that goal. And, unless you are a sociopath, you do NOT want to give this shit and vaccine AND masking will help achieve that goal. |
It's a given that you do not want to contract COVID-19. Vaccination and wearing a mask will help.
You also do not want to give COVID-19 to others. Again, vaccination and wearing a mask will help.
So this article is just pedantry over a statistical quirk.