There is a lot of controversy about whether or not wearing a mask helps reduce the number of infections.  How about we look into how effective the masks have been? 

In full disclosure, I am a supporter of mask-wearing.  They are not the end-all and be-all, but I believe they do reduce the number of infections.  However, there is undoubtedly some downside to wearing a mask. 

In a recent article, I discussed a study by the CDC and the Navy that had some interesting results.

There is science on both sides of this discussion, and I am not going to wade into all of it.  However, I have to admit frustration with the trust in mathematical models that continue to incorrectly predict this and that disaster.  In this case, they predict things like 70,000 lives will be saved by everyone wearing masks.  These models have proven inaccurate over and over, yet people use them to support their arguments. 

As Mark Twain said, there are lies, damn lies, and statistics.  You can make these models say whatever you want by feeding in the information to get the desired result.  If the data fed into the algorithm is flawed, the results will also be flawed.  These models being flawed should be obvious by this point because of how many times they have been wrong.

So, instead of the mathematical model damn lies, we will use real statistical information to test the effectiveness of wearing masks.

Currently, in the United States, there are 19 states not mandating mask use.  This group includes media punching bags Arizona and Florida, amongst others.  That leaves 32 states (including DC) that are mandating mask use.  Let’s look at what is happening in those two categories of states.

As of today, August 12th, we will look at the number of states that are trending up or trending down in their daily number of new infections.

  • 10.5% of the states without mask mandates (2 out of 19) are trending upwards in the number of new infections.
  • 21.8% of the states with mask mandates (7 out of 32) are trending upwards in the number of new infections.

Yes, you are seeing that correctly, the data shows that states with mask mandates are twice as likely to be trending upwards in the number of new infections.

Am I saying that masks are useless?  Of course not, I am very much pro mask when used correctly at the correct times.  But the nonsense that the media is propagating is not accurate.  They are trying to drive a hysteria instead of informing the public.

Look, remember a few weeks ago when the media was attacking states like Arizona and Florida repeatedly. Those states and their leaders were going to kill everyone, not only in their state but everywhere else.  Why do you not hear so much about that now?  Let’s take a closer look at how those states are doing.

Here is the chart of Florida and its progress against COVID.

And here is the chart of Arizona and their progress against COVID.

According to the media, their experts, and the models, Arizona and Florida Governors were trying to get people killed.  But the results prove otherwise.  Why is the media not touting their success at this point?

The bottom line is simple and increasingly obvious.  It has gotten to the point where you can pretty much assume any assertion in the media regarding COVID is inaccurate and designed to exaggerate, not inform, especially when they back it up with some “model” or “expert” opinion, without any actual statistical reference.  At what point do we wake up and realize that the media is not trying to inform us, they are trying to scare us.

Do you want to know why people do not believe everything reported about COVID, including the use of masks?  Because they have been lied to over and over.  You cannot trust the untrustworthy, and the media has proven to be untrustworthy.

I am pro mask.  But with the ongoing media campaign about the need for masks, I am becoming more and more skeptical.  I am pro mask, but I understand the science is not definitive, despite the depiction in the media. 

If you want to know more about why we all need to be skeptical of the media, please read and share my book, the FEAR-19 Pandemic.  It goes into detail about how the media led a campaign of deception early on in the pandemic to create a false perception.  COVID is a terrible and deadly virus, but the COVID boogie man created in the media is just a mythical creature carefully created and continually cultivated to terrify the populace.

There are reviews and a free sample of the book on Amazon.  Here is the most recent review.

#fear19  #covidphobia

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.