In 1932 the famous US Supreme Court Justice, Louis Brandeis, wanted to highlight one of the amazingly important, but often overlooked, aspects of the governmental structure of the United States: the tripartite separation of “rights and power” between the People, who start with all the rights and all the power according to the Preamble of the Constitution, and the Federal Government, which is only supposed to be granted the power that is written down, enumerated, in the Constitution, and the States, which is the default place for powers not specifically granted to the Feds on the one hand and specifically granted by the People through their state legislative bodies.
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The ‘Laboratory of Democracy’ has spoken: States without stay at home orders and should COVID-19 be renamed the “Acela Virus”
1. The ‘Laboratory of Democracy’ has spoken: States without stay
at home orders and should COVID-19 be renamed the “Acela
Virus”
In 1932 the famous US Supreme Court Justice, Louis Brandeis, wanted to highlight one of the
amazingly important, but often overlooked, aspects of the governmental structure of the United
States: the tripartite separation of “rights and power” between the People, who start with all the
rights and all the power according to the Preamble of the Constitution, and the Federal
Government, which is only supposed to be granted the power that is written down, enumerated,
in the Constitution, and the States, which is the default place for powers not specifically granted
to the Feds on the one hand and specifically granted by the People through their state legislative
bodies.
What did Judge Brandeis say?
Source: Library of Congress
2. “A single courageous State may, if its citizens choose, serve as a laboratory; and try novel social
and economic experiments without risk to the rest of the country.“
What does this have to do with COVID-19 you ask?
The experiment of NOT sheltering-in-place and shutting down businesses.
It turns out that seven states did not shut down businesses for the COVID-19 pandemic while 43
states did. [To be clear however, schools were shut down in 49 of 50 states. This despite the
known facts that COVID-19 in children is either mild or asymptomatic and deaths are much
lower than for influenza.]
So in seven states, lives were disrupted because childcare instead of school was a new necessity
for people with children to deal with but nothing else changed. No businesses were closed, no
restaurants shuttered, churches were unaffected, etc. If political science was a science it would
frame this situation as a hypothesis; to wit:
Based on our understanding of COVID-19 infectivity, we hypothesize that the states that did not
restrict its citizen’s movements would have either a higher rate of infection (cases per week or
month) or a higher number of infections (total cases cumulatively) or both.
The Figure below is taken from the excellent COVID-19 website maintained by Johns Hopkins
which can be found here: Daily cases per 100,000 citizens from Jan 1 to Jun 9
For orientation what you are looking at are the individual states with their two letter
abbreviation, a squiggly line for the three day moving average number of cases per 100,000
population and a color code of green, where cases are going down and red where cases are
going up. I am purposely not going down into the weeds in each state because we are looking
for BIG signals which should be visible at this level of looking at all the states as a group. For
now, please ignore all those states in the big blue box.
3. The seven states with the red boxes around them are the seven states that did not lock their
citizens at home. What jumps out at you about these seven states when you compare them to
the other states is…nothing! What I mean is that they look pretty interchangeable with the
states that completely shut down. Nebraska seems to have the biggest cumulative cases but it
looks a lot like Minnesota, Illinois, and Michigan in total area under the curve. As you are well
aware, those states really restricted their citizens.
So based on this data, you would have to conclude that your hypothesis is proven to be wrong.
Could the lack of cases in these states be due to factors like population density, lack of large
public transportation systems (see below), or any one of a number of other factors. Sure, and if I
was in a university we could sit around and have lively facility lounge debates on this for months.
But if you are making public policy decisions that are weighing shutting down a state’s economy
for months you should be absolutely sure of your facts because your actions effect millions of
lives and livelihoods. This was a colossal mistake.
Should SARS-CoV-2 be renamed the ‘Acela Virus?’
Now let’s focus on the blue box. When I was studying this chart without the blue box which I put
there I was puzzled about some of the state results. For example: New York and California have
very similar demographics, big cities, etc. yet their COVID-19 cases on a population basis could
not be different. One obvious difference is that Californians get around in their cars while New
Yorkers us a lot of public transportation.
But other unexpected states jumped out. For example, what’s with Rhode Island seeming to be
almost as bad as New Jersey? I love Rhode Island but it doesn’t have the ‘feel’ of New York or
New Jersey for me, at least. And Delaware, the same question comes up.
And then it hit me, what is the Acela Train Route and which states does it go through?
Source: Acela Route
![“A single courageous State may, if its citizens choose, serve as a laboratory; and try novel social
and economic experiments without risk to the rest of the country.“
What does this have to do with COVID-19 you ask?
The experiment of NOT sheltering-in-place and shutting down businesses.
It turns out that seven states did not shut down businesses for the COVID-19 pandemic while 43
states did. [To be clear however, schools were shut down in 49 of 50 states. This despite the
known facts that COVID-19 in children is either mild or asymptomatic and deaths are much
lower than for influenza.]
So in seven states, lives were disrupted because childcare instead of school was a new necessity
for people with children to deal with but nothing else changed. No businesses were closed, no
restaurants shuttered, churches were unaffected, etc. If political science was a science it would
frame this situation as a hypothesis; to wit:
Based on our understanding of COVID-19 infectivity, we hypothesize that the states that did not
restrict its citizen’s movements would have either a higher rate of infection (cases per week or
month) or a higher number of infections (total cases cumulatively) or both.
The Figure below is taken from the excellent COVID-19 website maintained by Johns Hopkins
which can be found here: Daily cases per 100,000 citizens from Jan 1 to Jun 9
For orientation what you are looking at are the individual states with their two letter
abbreviation, a squiggly line for the three day moving average number of cases per 100,000
population and a color code of green, where cases are going down and red where cases are
going up. I am purposely not going down into the weeds in each state because we are looking
for BIG signals which should be visible at this level of looking at all the states as a group. For
now, please ignore all those states in the big blue box.](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)