There is a lot of controversy about COVID deaths, so let’s do a deep dive.  There are plenty of theories about how we are undercounting COVID deaths, and there are theories about how we are over counting COVID deaths.  I am not going to get into all of those theories at this point.  Instead, I will see if there is a method by which we can test the accuracy of the COVID death numbers.

There is a concept called mortality displacement.  Here is a clip from Wikipedia:

Yes, I realize that Wikipedia is not dependable, but this is a good definition of what I am going to try and identify.  We are going to look into the average or expected mortality rate for the United States over the last four months and see if there was any excess mortality or displacement.  This approach is the best shot at quantifying COVID deaths without depending solely on the COVID death counts that have had a lot of problems.

Here is a look at the mortality numbers for all causes in the United States since 2015.

Pretty shocking, right?

First, there are a few things to identify.  This is not a chart of COVID deaths, this is a chart of deaths from all causes in the United States.  They are still counting for weeks over the last month because those numbers take time to come in, and they will certainly be much higher than they are now.  So, we can only use the data up and until June 1st to test the numbers accurately.

We will use March 9th as a beginning date.  That is a pretty good starting point for COVID.

The first step would be identifying the number of expected or normal deaths per month over this time (March 9th – June 1st).  The easiest and best way to do that is to see what the average increase in deaths is year over year.  As our population increases, we have more deaths each week.  Using the data from the last four years, 2015-2019, the average increase year over year is approximately 783 deaths per week.

We can add that number to the number of deaths per week in 2019 to approximate how many expected deaths would have occurred during 2020.  The total for the period beginning March 9th and ending June 1st is 668,716.

Next, we can total up the actual deaths from all causes in that same period.  That total comes to 772,338.

The difference in expected deaths from all causes during this time and the actual deaths during this time is 103,622.

The count presented by the different sources had us eclipsing 100,000 COVID deaths on approximately May 27th.  If you add in another 3,622 over the next five days getting to the June 1st end date of our little math experiment, you find that the numbers are pretty much spot on.

What does this mean?

If you have the theory that the numbers presented are low and we are undercounting, you are most likely wrong.

If you have the theory that the numbers presented are high and we are overcounting, you are most likely wrong.

I admittedly went into this expecting there to be a discrepancy.  What did I find, nope, there is not one.

However, a couple of points moving forward. 

On June 26th, several states starting counting what they call probably deaths.  What this did show is we are probably going to have inaccurate numbers moving forward, because the current methods seem accurate.  We shall see.

Second, there is another portion of the definition I gave you before that is relevant.

This concept of harvesting, while gruesome, is a strong possibility.  If the overall number of deaths now declines over the next months, it would indicate a forward shift in mortality rather than an accurate measure of COVID’s effects.  This harvesting effect is a distinct possibility because of the high percentage of individuals over 80 and in poor health, which this virus most affected.

I will revisit this math experiment in the future as the numbers keep coming in.  But for now, you can pretty much drop all the over counting and undercounting theories and go with the count presented as accurate for the number of people we lost to COVID.

 

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes:

<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>