Analysis of the effect of severity of containment policy

This one will be a bit short. No one seems to care much about COVID-19 policies. Rather, no one really cares if they worked or not unless the answer supports the policy and judgement of their team. Sad decade for fans of critical thinking and problem solving. Not you, dear reader; of course you are one of the good ones, just like me….

Anyhoo, now that we are mostly vaccinated and the pandemic is mostly over in the US, I have one more analysis to share. No one reads so I’m not bothering to post sources (I lost the link- duh). I found a site that looked pretty legit and did a ranking of US states on how strict they were with lockdowns. The ranking combined severity and time. I did not check their methodology; that’s part of my trying to reduce bias. That is, I didn’t look at their rankings and have a gut level agreement or disagreement with it. They had graphs that looked real and there was more red at the top than the bottom and let’s just go with it.

You may recall last time that I had a brilliant idea for comparing states’ policy performances. The idea is that different states start with different natural advantages (climate, population density, culture) and these must be accounted for when comparing how successful their extra policies were.

Every state did something. Every person could read the news and take precautions. National business conferences were shut down for everyone. So we all start with a lot of transmission reduction measures and factors and the real question is, what additional effect did longer lockdowns and strict masking policies have in reducing deaths? This is the “extra” I mean.

But you can’t just look at death rates and say, for example, that California’s policies were better than New York’s, because New York might have independent factors that doomed it. New York pretty much always has a worse flu season than California. Why? Dunno- winter? NYC population density? Less healthy lifestyle? Older population? Whatever. You would naturally expect California to have fewer COVID deaths per population than New York.

To strip out these other factors, as in my recent analysis, I checked how well each state did versus the average of the previous five flu seasons. This was expressed as a multiple. How many times more deaths did COVID cause than the average flu? By this measure New York was not as bad as it looked. Hawaii actually had fewer COVID deaths than average flu deaths. Benefit of being an island I suppose.

So here is my graph of lockdown severity (rank 1-50 with 50 being the least containment measures) vs multiple of COVID19 deaths vs an average flu season.

I’m not even going to do a linear regression on that. That is a friggin’ scatter plot. Yes there are a couple, three points showing highest containment with lowest multiple (one of those is Hawaii) but then you have essentially a rectangle in the middle and two outliers with super high multiples that were towards the middle of the range in terms of containment measures.

So, I’m going to say, as I predicted at the beginning, some measures and factors that were common to most states had the large effect and all the extra pain we subjected ourselves to didn’t rise much above background noise.

As always I am happy to be contradicted with some data and logic.

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