"shows five neighboring states with vastly different rules and roughly the same curves"
Very roughly, the heights of curves can be 3x different. But again there are actually zero controls here. Why did NYC spike first? Because that's where the virus was seeded. Someone could post a comparison of NYC in that period to Chicago after NYC was…
"shows five neighboring states with vastly different rules and roughly the same curves"
Very roughly, the heights of curves can be 3x different. But again there are actually zero controls here. Why did NYC spike first? Because that's where the virus was seeded. Someone could post a comparison of NYC in that period to Chicago after NYC was first to move towards interventions, and claim it is proof that interventions *cause* covid. In fact many make those sorts of comparisons and I think the link here is a variant of this sort of reasoning.
Interventions are primarily about protecting lives and hospital capacity, not pretending they will make waves go away.
To be clear I am mostly interested in this academically. I think it has been the right choice to avoid lockdowns in the past year with vaccines, and hospitals are (barely) holding through omicron. Regardless of discussions like this, if future waves threaten hospital functioning you will likely see emergency responses including closures simply because it becomes politically impossible to do nothing if you are losing your society's health care capacity.
NYC 'spiked' first because that's where we started testing. The virus was already all over the country by Christmas 2019, and testing of bloodwork from that timeframe proves it.
They also sped up their curve by infecting all the at-risk at once. And even then, during the point of lowest immunity, the hospitals weren't overrun.
Incidentally, I went back onto my Twitter to try to dig up some predictions. Not only can I not download my data, I can only see Tweets from the last 5 months or so, and NONE of the pictures that go with the Tweets. Interesting, huh? :)
The virus wasn't everywhere immediately, you can't explain away different hospital loads with the testing handwave.
"sped up their curve by infecting all the at-risk at once" is not a very serious comment (besides contradicting your own comment on testing).
We seem pretty clearly into non-rational territory. Falsifications of your theory are ignored, fixed with 'mystery' factors we can't confirm with data.
I'm talking about them putting covid patients into nursing homes. People in nursing homes are, by and large, the ones most at risk. Cuomo and the other governors infected them all at the same time, speeding up their curve.
This is all common knowledge.
Edit: Wherever we tested for the virus in early 2020 we found it. Louisiana one such spot because of marti gras. But antibody test done IN APRIL 2020 already showed the virus was far more widespread than we thought.
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.)
"shows five neighboring states with vastly different rules and roughly the same curves"
Very roughly, the heights of curves can be 3x different. But again there are actually zero controls here. Why did NYC spike first? Because that's where the virus was seeded. Someone could post a comparison of NYC in that period to Chicago after NYC was first to move towards interventions, and claim it is proof that interventions *cause* covid. In fact many make those sorts of comparisons and I think the link here is a variant of this sort of reasoning.
Interventions are primarily about protecting lives and hospital capacity, not pretending they will make waves go away.
To be clear I am mostly interested in this academically. I think it has been the right choice to avoid lockdowns in the past year with vaccines, and hospitals are (barely) holding through omicron. Regardless of discussions like this, if future waves threaten hospital functioning you will likely see emergency responses including closures simply because it becomes politically impossible to do nothing if you are losing your society's health care capacity.
NYC 'spiked' first because that's where we started testing. The virus was already all over the country by Christmas 2019, and testing of bloodwork from that timeframe proves it.
They also sped up their curve by infecting all the at-risk at once. And even then, during the point of lowest immunity, the hospitals weren't overrun.
Incidentally, I went back onto my Twitter to try to dig up some predictions. Not only can I not download my data, I can only see Tweets from the last 5 months or so, and NONE of the pictures that go with the Tweets. Interesting, huh? :)
The virus wasn't everywhere immediately, you can't explain away different hospital loads with the testing handwave.
"sped up their curve by infecting all the at-risk at once" is not a very serious comment (besides contradicting your own comment on testing).
We seem pretty clearly into non-rational territory. Falsifications of your theory are ignored, fixed with 'mystery' factors we can't confirm with data.
I'm talking about them putting covid patients into nursing homes. People in nursing homes are, by and large, the ones most at risk. Cuomo and the other governors infected them all at the same time, speeding up their curve.
This is all common knowledge.
Edit: Wherever we tested for the virus in early 2020 we found it. Louisiana one such spot because of marti gras. But antibody test done IN APRIL 2020 already showed the virus was far more widespread than we thought.
https://newyork.cbslocal.com/2020/04/27/coronavirus-antibodies-present-in-nearly-25-of-all-nyc-residents/
This is late april. 25% of NYC already had antibodies.
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.)