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the CDC is now publishing all cause deaths figures, by state, over the period from 2/1/2020 to 7/4/2020. this is literally cherry picked to show covid at its worst. they express them as a % of expected deaths. i ran this against degree of lockdown based on google mobility.pic.twitter.com/LvWTByatfK
as you can see, the results are not encouraging for team lockdown. there is significant correlation between more lockdown and higher expected deaths. in fact, not a single one of the 7 states that did not lock down is even at 100% of expected deaths. all are low.pic.twitter.com/Jz7JOyGHbp
the 7 states with most lockdown show 5 above 100% and avg 117% of expected deaths vs 95% for those that did not lock down, a whopping 22 percentage point variance. the states with <100% expected deaths averaged -21% google mobility. those > 100 averaged -38% (80% bigger drop)
i added in some of the states everyone seems to be currently worried about simply because i presumed people would ask. the tool is here (table 2) if these is some other state you are interested in. https://www.cdc.gov/nchs/nvss/vsrr/covid19/index.htm …
all in all, this seems yet another serious issue for the lockdown proponents. correlation is not causality, so this does NOT prove that lockdowns cause deaths. (though it is consistent with it) but causality with inverse correlation is a deeply iffy idea.
so it does demonstrate that locking down did not reduce all cause deaths. and, as we have seen previously, this same relationship holds for covid deaths.https://twitter.com/boriquagato/status/1261705308302270466?s=20 …
so let's all keep this in mind as panicky state governors flout decades of established pandemic response policy and chase lockdowns that are literally advised against in the epidemiological guidelines.
it's not science and it never was.
and it does not work.
#DemandBetter
ADDENDUM: as i apparently did not foreground this enough, no, this is not driven by reverse causality. covid case counts do not predict lockdown intensity with any significance. it would not invert the R2 on any of this data.https://twitter.com/boriquagato/status/1255553218014109696?s=20 …
Devil’s advocate: some, albeit not all, of the strongly pro-lockdown states got hit early and got hit hard, before they had a chance to lockdown(NY, nursing home disaster aside, is a good example). The phrase I heard was “closing the barn after the horses had already escaped.”
the issue with that argument is that when one sues actual data of death data (from the relatively few places that report it) it becomes very clear that the virus was well into decline before lockdowns even began.https://twitter.com/boriquagato/status/1266747362728280065?s=20 …
Lockdowns won't work because people still go shopping, working if deemed allowable, cheating at lockdown, etc... Your correlation sure looks better than 0.26. Seems like a 0.6 or greater with the eyeball test.
R2 is notoriously hard to eyeball. .26 is about right. .6 would now have that flat smear of no trend in the middle.
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