Please note I hit send too early and the final numbers are slightly off and I will be changing them soon. It will not make a difference to the conclusion but some of the calculations need to be adjusted to reflect the "fully vaccinated" population rather than the vaccinated population.
I'm a bit confused about how you're using "New York" here. In the beginning you refer to the state, but during the rest of the piece you seem to be talking only about New York City? There's a quite large state attached to that city, which even many Americans don't know (amusingly and frustratingly to those of us who live(d) there).
Could all of this not simply be due to a long seris of compunding rounding errors and similar?
Say the root number, the one all other models and estimates build upon year after year is from 1975? Would it not then be quite reasonable to assume that the majority what you are seeing is simply accumulated rounding errors, and that due to rotation of staff over the years paired with switching from doing math to using machines to do math, this now goes unnoticed by the people collating data?
A sort of cascading, compounding flow of errors invisible becuase any user of the system starts with the system as flawed, and not from newly collected hard data (which is much more expensive to collect).
Nothing nefarious, just laziness, short sightedness, stupidity and general cheapness.
Please note I hit send too early and the final numbers are slightly off and I will be changing them soon. It will not make a difference to the conclusion but some of the calculations need to be adjusted to reflect the "fully vaccinated" population rather than the vaccinated population.
I'm a bit confused about how you're using "New York" here. In the beginning you refer to the state, but during the rest of the piece you seem to be talking only about New York City? There's a quite large state attached to that city, which even many Americans don't know (amusingly and frustratingly to those of us who live(d) there).
Could all of this not simply be due to a long seris of compunding rounding errors and similar?
Say the root number, the one all other models and estimates build upon year after year is from 1975? Would it not then be quite reasonable to assume that the majority what you are seeing is simply accumulated rounding errors, and that due to rotation of staff over the years paired with switching from doing math to using machines to do math, this now goes unnoticed by the people collating data?
A sort of cascading, compounding flow of errors invisible becuase any user of the system starts with the system as flawed, and not from newly collected hard data (which is much more expensive to collect).
Nothing nefarious, just laziness, short sightedness, stupidity and general cheapness.