By David Stienmier – Re-Blogged From WUWT
I’ve had this data for a month or so now and I’ve been trying to decide what to say about it. I assumed someone else would show this somewhere first and I could resume my quiet observation. But I haven’t seen it anywhere and with everyone talking about locking down again I decided I should at least put it out there with minimum comment. So here it is.
Lockdowns are intended to reduce the spread of cases and therefore the number of deaths. A known side effect of the lockdowns is an increase in unemployment. So we should be able to use the increase in unemployment as a proxy for how hard a state locked down. Figure 1 shows how cases relate to lockdown intensity as measured by unemployment. There appears to be very little relationship, but maybe it reduces the number of cases slightly.
Unemployment, however has long been associated with poor health outcomes so it’s reasonable to ask if this is the case with Covid. Figure 2 shows total Covid deaths vs unemployment increase. Do I need to comment?
While reducing total deaths is the goal, the known relationship with unemployment is with health (all cause mortality). So it’s reasonable to look at the case fatality rate. Figure 3 shows that 47% of the variance between states in case fatality rate can be explained by a simple linear relationship with how hard states locked down (and it’s not in the direction intended by the states that locked down hard). I know, “correlation is not causation”. But negative correlation is at least an indication of lack of causation.
[There are many more graphs. –Bob]