Of course I know the reference (I generally follow the viral stories, but also tend to have read into what's behind them). I'm sure there was some effect, but "infecting all the at-risk at once" is (as I said) not a very serious comment.
Yes they put recovering covid patients into nursing homes, because they needed hospital capacity. Omit…
Of course I know the reference (I generally follow the viral stories, but also tend to have read into what's behind them). I'm sure there was some effect, but "infecting all the at-risk at once" is (as I said) not a very serious comment.
Yes they put recovering covid patients into nursing homes, because they needed hospital capacity. Omitting such context is part of the partisan circus. Analysis failed to show a connection between nursing home death rates in the NYC region and patient discharge. NY reported average time in hospital of 9 days before discharge and evidence is pretty clear that infectiousness has typically plummeted by then (10 days the standard safe cutoff).
I don't want to get in the way of partisan hackery, go ahead with it, just personally more interested in the scientific topics. I'm well aware that most of these online discussions are more about political ax-grinding than science. Sometimes takes a pass to sort which is which.
If "the virus was far more widespread than we thought" and the nursing homes all claim they already had covid-19 circulating before receiving patients, then it wasn't really the recovering patients driving the NYC death count.
Also, note that you can't easily have both – if the NYC curve *was* driven by government policy, then "virus is gonna virus" is falsified.
Can maybe just amend the formal statement of Hope-Simpson theory: "rules or policies cannot affect covid epidemics, except in the case of Democrats if the effect is negative in which case they dominate". Which is fair game as it is testable, though I don't know how much confidence I have in it.
(This is a common dilemma in science contrarianism. Any theory that seems to go against the mainstream scientific view is popular and needs to be amplified, but often these contrary theories also contradict one another, leaving a painful choice of having to promote one or the other.)
Of course I know the reference (I generally follow the viral stories, but also tend to have read into what's behind them). I'm sure there was some effect, but "infecting all the at-risk at once" is (as I said) not a very serious comment.
Yes they put recovering covid patients into nursing homes, because they needed hospital capacity. Omitting such context is part of the partisan circus. Analysis failed to show a connection between nursing home death rates in the NYC region and patient discharge. NY reported average time in hospital of 9 days before discharge and evidence is pretty clear that infectiousness has typically plummeted by then (10 days the standard safe cutoff).
I don't want to get in the way of partisan hackery, go ahead with it, just personally more interested in the scientific topics. I'm well aware that most of these online discussions are more about political ax-grinding than science. Sometimes takes a pass to sort which is which.
If "the virus was far more widespread than we thought" and the nursing homes all claim they already had covid-19 circulating before receiving patients, then it wasn't really the recovering patients driving the NYC death count.
Also, note that you can't easily have both – if the NYC curve *was* driven by government policy, then "virus is gonna virus" is falsified.
Can maybe just amend the formal statement of Hope-Simpson theory: "rules or policies cannot affect covid epidemics, except in the case of Democrats if the effect is negative in which case they dominate". Which is fair game as it is testable, though I don't know how much confidence I have in it.
(This is a common dilemma in science contrarianism. Any theory that seems to go against the mainstream scientific view is popular and needs to be amplified, but often these contrary theories also contradict one another, leaving a painful choice of having to promote one or the other.)