So, I get up this morning and go through my usual routine.  I begin by looking into the COVID charts from around the country and the rest of the world.  I typically resist looking at any of the “news” sites because I have learned that they are more interested in developing my perceptions than providing information.  However, I am curious about any new antibody studies and hit google.

This article from Newsweek pops up.

My first thought is, wait, that can’t be right.  From what I have read and been observing in the charts, we are absolutely making good progress towards herd immunity.  And then I remember, oh yeah, Trump has some new guy who seems to like the herd immunity concept, so it has to be the worst thing in the world, and obviously will not work.  The media will be obsessed with attacking the concept, thus the headline.  Thanks, Trump, now we can’t have an honest conversation about herd immunity.  But I am going to try anyway.

Let’s take a closer look at the results of the study.  Here is the link to the study on Lancet if you want to read it yourself, but I will give you the highlights. 

  1. 9.3% of the US Population had protective COVID antibodies by the end of July.
  2. The percentage was highest in the Northeast (27.2%) and lower in the rest of the country.
  3. 9.2% of those who have antibodies were diagnosed with COVID.

We will begin by looking closer at that third number.  9.2% of individuals who have protective antibodies were diagnosed with COVID.  Meaning, only 9.2% of people who were infected are confirmed cases.  You see, confirmed cases are only a small percentage of overall infections.  So, 90.8% of people who become infected with COVID do not get tested.

The 9.2% number is based upon research from Johns Hopkins but has been reinforced by studies around the world.

Now, if we want to determine the number of total COVID infections for an area, we have to determine what number we multiply the number of confirmed COVID cases by to get to 100% of total infections.  Let’s do a little algebra.

9.2 (confirmed cases) * X = 100 (total infections)

X = 10.87

If you take the number of confirmed COVID cases and multiply it by 10.87, you will have a reasonable estimate of total COVID infections for a given area.  And the number of total COVID infections indicates the number of people who have protective COVID antibodies after recovery.

For example:

  • New York had 415,767 confirmed cases of COVID at the end of July.
  • If you multiple that number of confirmed cases by 10.87 you would have the number of total infections in New York.
  • New York had 4,519,387 total COVID infections at the end of July.
  • The population of New York is round 19.44 million.
  • 23% of New York residents were infected with COVID and had developed antibodies at the end of July.

The study found that 27.2% of individuals in the Northeast had antibodies.  So, it is safe to assume that our method of determining the total number of infections is very accurate.

23% of New York residents having antibodies is outstanding news.  Why?  Because there is a good chance that New York reached a good herd immunity number by July.  Let me show you a chart from about the spread of infections in New York to highlight my point.

Were they still having new infections after July?  Yes.  But they seem to have reached a level that kept the spread to a minimum.

Now, I realize that the next thing everyone says is, “well yeah, that’s because they are locked down.”  Or, “it’s because of masks or social distancing.”  Well, read my previous article to understand why this is all a myth.  It is the level of infected individuals that is the biggest brake on infection spread, not the mitigation efforts.

Here are a couple of other Northeast states.

See how the pattern continues?  These states all had significant early outbreaks.  But now, they are not having any significant outbreaks.  They had enough infection spread early and now the people with protective antibodies are a brake on infection spread.  As I say all the time, the only way to stop infection spread is to have infection spread.  You just don’t want spread to the vulnerable populations.

Now, we get to the really good news.  As we just discussed, the study revealed that 27.2% of those living in the Northeast had developed antibodies which is why they were not having significant outbreaks.  But, the antibody numbers were much lower in the South, Midwest, and West. 

However, keep in mind, this was at the end of July.  Some of our more populated states in those other areas had significant outbreaks in August and September.  

Here are a few visual examples to show you what I am saying.

These areas had their outbreaks after the study was completed.  So, the number of people in those areas who had antibodies at the time of the study were lower. But that is no longer the case.  Now, more areas have joined the Northeast in having a higher number of recovered people with antibody protection.  

And keep in mind, these areas controlled infection by opening up and allowing infection, not by locking down.  They allowed spread to control spread.  Florida is completely open now and still not having any significant outbreaks.

The more areas that reach the threshold number of infections, the more people who will have protective antibodies, the more brake on infection spread we have, and the closer we are to the end of COVID. 

Let’s pull this all together.  With all those additional outbreaks taking place and subsiding in August and September, the total number of US confirmed cases is nearly twice as high as it was in July.

As of September 28th, we stand at 7,013,825 confirmed cases of COVID in the United States.  Using what we have learned about total infections, that number indicates there have been approximately 76,240,278 actual COVID infections in the United States.  With the United States’ current population being around 330 million, approximately 23% of the US population probably has some level of protective antibodies.

Man, that is excellent news.  23% of the population with some level of protection is a good brake on infection spread.  You can see that on the charts above regarding the northeast.  We are nearing the threshold number of infections, no matter how many times they tell us it “remains out of reach.”

Of course, we are not out of the woods yet.  There are still areas of the county that are more isolated or continue to delay opening up entirely.  Plus, infections can come in from other countries.  But even if they do, the ability for COVID to spread is being disrupted, which means we are closer to having this pain in the ass under control than we are from having significant outbreaks.

Remember, what made COVID so dangerous was that it was a NOVEL coronavirus.  It WAS novel but is not now, and never will be again.  The headline from Newsweek could not be any more wrong.  We are coming ever closer to the herd immunity threshold, which is outstanding and uplifting news.  The big question, do we get there before they try to make everyone take a vaccine?

There is one absolute.  The media will continue to develop the perception of how terrible everything is.


What if we don’t need a vaccine for COVID-19?  All the experts have told us repeatedly that the only way to stop the spread of COVID is the development of a vaccine.  What if they were wrong?  Let me show you why we may not need a vaccine to get rid of COVID.

We must begin by explaining the purpose of the vaccine.  Here is an image from the CDC, Understanding How Vaccines Work.  It is a good read but I will give you a few highlights.

The vaccine will provide immunity to the virus.  But vaccines are not the only way to develop immunity.  This section, about how the body naturally completes the same process, is from the same CDC report.

The second way to build immunity is to become infected and recover.  Your body fights off the virus and develops the ability to fight the virus in the future.  So, there are two methods for an individual to develop immunity to a virus, infection recovery or vaccine. 

Next, instead of just considering immunity individually, we can look at virus spread from a macro view and discuss herd immunity.  The herd immunity concept is pretty simple.  If enough people become immune to a virus, it is unable to spread within the “herd.”  People with immunity become a BRAKE on infection because it cannot use them to spread to others.

Now, determining the threshold for herd immunity is not a simple process.  It is very convoluted, involves a lot of math, and different methods will give you different answers.  In the end, it is not a precise number; it is an estimate based upon the information at hand and the method used.

When COVID first began circulating, the typically accepted number for herd immunity was 60%.  60% of the population needed to be immune before the infection would lose the ability to spread.  At this point in time, that number has proven to be highly inaccurate.  If you want to read it, here is one thorough explanation about why the herd immunity number may be between 10-20%

You do not need to understand all of that science and math to see that the herd immunity percentage is not near 60%.  I can show you why the lower number is more likely to be correct with a bit of observation and a lot less math. 

We can begin by discussing one of the worst outbreak areas in the United States.  New York was the first big hot spot in the United States.  The infections rose at an alarming rate in New York, and especially in New York City.  Let’s look at a chart of the number of new COVID infections in New York over time.  The chart is provided by with data from Johns Hopkins.

And here is the chart of COVID deaths in New York. 

Both charts have that distinctive pattern.  Now, many people will tell you that the lockdowns are what stopped COVID from spreading and killing people in New York.  But I can show you why that is incorrect. 

Let’s begin with an extensive antibody study completed in New York back in April.  They tested large samplings of people for COVID fighting antibodies.  As we discussed above, you develop the antibodies by becoming infected and recovering.  The results of this study were stunning.  In New York City, over 20% of individuals had antibodies, and the number statewide in New York was 13.9%. 

Now, if you look back at the charts above, the number of new infections and deaths from COVID both declined to a very low level in New York.  There are two possible causes for this.

  1. New York implemented lockdowns and a mask mandate and these measures acted as a brake on the spread of COVID.  Or,
  2. New York reached the herd immunity threshold which acted as a brake on the spread of COVID.

By April, approximately 13.9% of New York State individuals had contracted COVID, recovered, and developed antibodies.  That falls right in line with the 10-20% needed for herd immunity suggested in the article above.  Think about that.  If that number (10-20%) is correct, it was herd immunity, not lockdowns, that stopped COVID from spreading in New York State.  If correct, the lockdowns accomplished nothing.  Well, except for causing additional damage.

So, how can we determine whether it was the lockdowns, or immunity, that was the brake on infection?  Well, we need a control group.  We need another location that we can use to compare to New York.  We need somewhere that had a significant outbreak like New York, but did not utilize a lockdown to “stop the spread.”  We can then compare results to see if there is a difference. 

But that is a challenging task.  You see, lockdowns were promoted very aggressively within political and media circles, so very few governments resisted that pressure.

Most countries gave in to that pressure and implemented lockdowns.  Here are two countries in Europe that had significant COVID outbreaks, implemented lockdowns, and had similar results to New York.  The following chart is the 7-day rolling average of daily deaths in Italy and the United Kingdom.  The chart is from

Notice how similar those two charts are to the ones from New York.  And remember, the “experts” will tell you that the lockdowns stopped the spread in all three of these areas.  But are they correct? 

What about that control group?  What about a country that had a significant outbreak, but did not implement a lockdown?  Would they still be able to get the infection under control without lockdowns, or would it just continue to spread?

The following is the chart for Sweden.  Sweden did not lockdown.  They did not close all their schools.  They did not close restaurants, bars, or even nightclubs.  They kept gyms, hair salons, and most everything else open.  They did not restrict travel into the country.  They only limited gatherings to 50 people at a time.  And at this point, they are not even recommending mask use.  So, what happened?  Let’s look at the chart.

Does that look familiar?

How about all three of these European countries on one chart. 

Notice how the pattern is the same in all three countries and is the same in New York.

The four locations, New York, Italy, UK, and Sweden, all had significant outbreaks, and their charts look incredibly similar.  However, there is one giant difference.  Sweden did not utilize a lockdown.  But somehow, they had the same results.

The only honest conclusion is that the lockdowns and restrictions were not the brake on infection; it was the number of people with immunity.  Once enough people have immunity, the spread of infection will slow regardless of a lockdown, masks, or whatever.  To stop the spread, you must have spread.  There is no way 60% is correct for herd immunity against COVID because none of these countries are anywhere close to that number.

Now, this brings us back to the question of needing vaccines.  To stop a virus from spreading, we need enough people to be immune.  If that happens, the virus can simply disappear.  Now, is there any reason to think that this could happen with COVID without a vaccine?  Well, absolutely!

To explain how this could happen, we have to go back almost 20 years.  We all know this current virus as COVID-19, but it is more precisely SARS-CoV-2.  It has a cousin, SARS-CoV-1.  That coronavirus was the SARS outbreak from 2002.  If there is any virus similar to COVID, it is SARS.

Let me know if any of this sounds familiar.  This information is from the CDC regarding the SARS outbreak.

In November of 2002, there was a report of atypical pneumonia in China.

By February of 2003, there were reports of the virus coming from other countries in Asia.

As of March 17th, there were 14 suspected cases in the US.

Doesn’t that seem extremely familiar?

SARS continued to spread around the world, and a lot of people died.  Although not anywhere close to as many with COVID.

Now, do you remember what happened with SARS-CoV-1? 

Well, it disappeared.  Yes, it just disappeared.

Don’t get to excited.  SARS-CoV-2, our COVID, is way more contagious than its cousin based upon the number of people infected.  Any theory that COVID would die as quickly as SARS would be unfounded.  However, does that mean that COVID will not just go away like SARS?  Absolutely not, COVID could just disappear, with or without a vaccine.

Let’s look at what is currently happening in the United States to show you how we may already be moving in that direction.  We instituted lockdowns in a majority of the country and have been opening back up over the last months.  My argument since March has been that lockdowns would not stop or reduce the number of COVID infections or deaths; they just delayed them.  The data is now backing that assertion up.  (Please read my recent article if you are not aware).  

Now, despite all the opening up.  Despite much of the country returning kids to school, and many colleges opening, the number of new infections continues to decline.  On September 7th and 8th, we had the lowest number of new daily infections in almost three months.  Here is the chart of new daily infections in the United States. 

Why are infections decreasing?  Shouldn’t infections be increasing with all the increased activity?  Well, no, not exactly.  You see, the number of people with immunity is also increasing, and that is creating a brake on infection spread.  You need spread to stop the spread.  As more people become immune by recovering from an infection, the virus loses its ability to spread.

Let’s look at some more data. 

Remember all the “experts” telling us that Arizona was going to kill us all by being so irresponsible, opening up and reducing restrictions.  Let’s look at their current chart. 

Hmmm, it seems that the same pattern we saw above in New York, Italy, UK, and Sweden took place in Arizona.  Most importantly, it looks like they now have a handle on the infection spread.  They ended their lockdown, reduced restrictions, and the infections are disappearing.  COVID is no longer increasing in Arizona; it is under control.  They have stopped the spread by having spread.

And Florida, remember the Chicken Little claims about how everyone was going to die?  And, how their poor decisions would lead to the rest of us dying?  Here is their current chart.

Seem familiar?  Does that graph seem like the ones from New York, Italy, UK, and Sweden? 

Again, Florida has gotten control of infection spread by removing the lockdowns and restrictions.  The virus is disappearing in Florida despite all the doom and gloom predictions.  Ask yourself why?  You have to have spread to stop spread.

And even now, the current Chicken Little claim is that college kids are going to kill us all.  But maybe, and I am just spitballing here, those college kids will move us closer to the objective of ending this virus.  Maybe they will help it disappear?  If at this point you are still listening to chicken little “experts” instead of examining the actual data right in front of your eyes, you need to ask yourself why.  The experts and their predictions have been wrong, over and over.  Their exaggerations have missed the mark repeatedly.

Despite all the doom and gloom, and attempts to terrify us all, the data is continuing to show that we are much closer to herd immunity than we are to the apocalypse.  And if we reach that level, this virus could disappear, just like its cousin did.  

The data tells the tale.  COVID is slowly going away.  Will it go away completely?  No one knows.  But, there is a reasonable chance that it merely dies off.  The real question is if that will happen quickly or slowly.

I ask again, what if we do not need a vaccine for COVID?

COVID is a bad virus.  But the COVID Boogie Man is a mythical monster created by green journalist and opportunistic politicians.  At some point, the data will reveal the truth. 

If you want more information about how we were all misled, about how the COVID Boogie Man came to be, please read and then share my book, The Fear-19 Pandemic.  There are reviews and a free sample available on Amazon.

Maybe most importantly, share this article.  At some point, people need to understand the difference between COVID and the COVID Boogie Man.

The lockdowns failed miserably in reducing COVID infections or deaths.  Let me show you the proof?

In part one of lockdown failure, we compared two states that shared geographic location, population size, population density, and size of their largest city.  These two states were Kansas and Nebraska.  The primary difference between these two states is Kansas utilized a lockdown, and Nebraska did not.  Here is a chart of their new daily cases since the beginning of the COVID pandemic.

Kansas locked down and is blue.  Nebraska did not lockdown and is orange.

As I have long argued, the lockdowns were never going to reduce or eliminate the number of infections.  All they would do is delay them.  Once you opened back up, the infections were still going to take place.  The comparison between Kansas and Nebraska proves the theory was correct.  Kansas locked down and had fewer infections initially, but once they opened back up, their infections soared above Nebraska’s.

All the damage caused by the lockdowns (please read here) was self-inflicted because it was a flawed theory that has proven incorrect.  It was an experiment that failed.  COVID did not cause those damages; our leaders did.

Now, while the Kansas/Nebraska comparison is as good a comparison you can get, there is another one just as good.  We will compare two other states that border each other, Arkansas and Mississippi.  Mississippi locked down, while Arkansas did not.

  • The two states border each other, so they share their geographic location.
  • Arkansas ranks 34th in total population, and Mississippi ranks 35th.
  • Mississippi ranks 38th in population density, and Arkansas ranks 40th.
  • The largest city in Arkansas is Little Rock, with a population of 197,000.
  • The largest city in Mississippi is Jackson, with a population of 164,000
  • Mississippi was a lockdown state. Arkansas was not.

The two states share geographic location, have a similar total population, similar population density, and comparable size of their largest city.  This is also as good of a comparison as you can get. Let’s check the results.

Here is a chart of both state’s number of new cases of COVID on a rolling 7-day average.  Can you guess which graph is the lockdown state?

It’s pretty obvious which state instituted a lockdown, right?  Except it’s not.  The only give away is the surge in the blue line, Mississippi, which took place after they ended their lockdown.

Again, these states share geographic location, population size and density, and size of their largest city.  Mississippi (Blue) locked down due to COVID, and Arkansas (Orange) did not.  Can anyone make an argument that the lockdown worked?  If you can, it will be very thin.

The effectiveness of lockdowns was and is entirely theoretical, and the data has shown that those theories were wrong.  Our governments caused us all considerable harm for what?

“But wait, the lockdowns saved lives.”

Okay, let’s check the data. Let’s look at the number of deaths in each state on a rolling 7-day  average.

Did the lockdowns save lives?  No, that is a big fat lie.  The state that locked down had considerably more deaths than the one that didn’t.  The lockdowns were theoretical, philosophical bullshit based upon flawed mathematics (“models”) that resulted in significant damage, and did nothing to reduce COVID infections or deaths.

The worst part is that the lockdowns should have never happened, or at a minimum, should have never lasted as long.  Hopefully, you read my book where I go in-depth into how and why the lockdowns happened, and why they continued well past their expiration date.  If you haven’t, you will find a link below to purchase it on Amazon.

Here are the two most recent reviews from readers.  There are more reviews and a free sample on Amazon.

Look, if you believe everything you were told I challenge you to read this book and dispute the conclusions.  It will be a epiphany for you.  Plus, it is free if you are a member of KindleUnlimited.


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

Okay, let’s look closer at whether or not the lockdowns were effective at limiting the spread of COVID, and limiting the deaths from COVID. 

To do so, we will compare a couple of states, one that did a lockdown, and one that didn’t.  The states share geographic location, population size and density, and comparable size of their largest city.  The primary difference, one locked down and one did not.

We will begin by showing you a chart comparing the two states and their “new cases” on a seven-day rolling average.  

See if you can tell which state is the lockdown state, and which is not.

Can you tell which color is for the state that locked down? 

My primary question has always been, if it is not obvious that the lockdowns work, why would we use them?

The orange line is the state that did not lockdown.  They had more infections initially, but then the state that did lockdown (blue line) had more infections later.  The infections were not decreased, they still happened.  The lockdowns only delayed the infections.

I have long argued, going back to March, that lockdowns were not warranted because all they do is delay the infections; they do not prevent or stop the spread.  And this graph completely backs up that theory.  The data is starting to come in, the theoretical and philosophical justifications for lockdowns have not stood up to the facts.  The models were wrong because they were given flawed information.

Let’s take a look and compare the deaths for each state.

Again, can you tell which is the lockdown state and which is not?

The deaths do not quite follow the same pattern as the number of “new cases,” they are a lot more random.  But again, I think the chart makes the point for me.  If you cannot tell the difference between a state that did lockdown, and one that didn’t, what was accomplished?

The lockdowns did all that damage, but there is no discernible advantage gained against COVID.  Feel free to read this sample from my book about lockdowns if you are unaware of the damages.  But beyond the damages caused, the bottom line is that the lockdowns failed to reduce the number of COVID infections or deaths.  Destruction caused, but no advantage gained.

These two states in this comparison are Kansas (blue) and Nebraska (orange).  Kansas did lockdown while Nebraska did not.  These two states share a long border, so they share geographic location.  They rank 36th and 38th for population amongst the US States.  In population density, Kansas ranks 41st and Nebraska ranks 43rd.  Plus, the largest city in Kansas is Wichita, with a population of 390,000.  The largest city in Nebraska is Omaha, with a population of 469,000. 

The two states share geographic location, have similar population size and density, and their largest cities have similar size.  I challenge you to find a better comparison. 

One state locked down, one did not, but there is no discernible difference between their results in total cases or deaths.  So, what was the point? 

The lockdowns were an entirely unwarranted experiment that was ineffective and caused more damage than COVID ever could have by itself.  We destroyed our economy, eliminated jobs and wreaked businesses, damaged children and families, increased suicides and overdose deaths, reduced the health and mental health of the entire population for what?  Absolutely nothing except lots of media and political attention.  Sorry folks, you were hoodwinked.

For more information on how and why you were hoodwinked, you can find my book on Amazon.

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.


It is amazing how our society is so fragmented and toxic that we can turn what should be a simple discussion about masks into a fight.  And just like our two-party system, we believe the reductive idea that masks are either good or bad.  As in all things, it is not that simple.  Can we all take a deep breath, look at the facts, and be reasonable?

Let’s start with the science.

The recent CDC and Navy report about the USS Theodore Roosevelt is an excellent opportunity to study a lot of aspects of COVID.  It is a rare opportunity where we have a control group to compare results.  In a previous post, I went into more detail about the study.  Here is the chart of those results indicating the reduced chances of becoming infected by different behavioral interventions.

Wearing a mask is the single most effective method of avoiding infection.  Not social distancing, not avoiding common areas, not hand sanitizer, not even washing your hands.  Wearing a mask is the #1 method of avoiding infection and reduces your chances by 20%.  That is not bad.

But remember, the primary reason for wearing a mask is to avoid spreading the infection to others.  Think about people in an operating room.  They do not wear masks to protect themselves; they are wearing masks to protect others.  Here is a doctor who tried to demonstrate the purpose of the mask.

And yes, I realize you cannot trust everything you see of social media.  But the doctor is right about limited the spread.  Here is an example that you should not believe. It is common shared tweet about oxygen levels that is entirely misleading.

She does not say how long she wears the mask, just simplistic pictures to try to make a false point.  Here is someone going into more detail about a lot of the science about wearing a mask.  You can read the entire report, but I will sum up its primary points.

  • Yes, a mask does decrease oxygen levels.

You know what, I have to stop for a second.  Well, no shit, a mask decreases oxygen levels!  Shocking!  Wearing something over your mouth reduces airflow, which in turn reduces oxygen levels, especially over time.  How in the hell did you convince yourself that was stupid?  If you wear something that ultimately keeps out all droplets, like a plastic bag, you will not spread at all.  Of course, you would suffocate FROM A LACK OF OXYGEN, but at least you wouldn’t spread.  Did you think masks were freagin magic and only kept out COVID?  Okay, I am done with my rant.

  • There could be an increased risk of severe reaction for those who are elderly with underlying conditions.

Does the increased risk of severe infection outweigh the 20% reduction in the chance of becoming infected?  I simply do not know, but I do know it is not a simple yes or no.

Okay, so this not a simple masks are good, masks are bad discussion.  But there are reasonable solutions if you will all just stop yelling at each other.  Let’s go through bullet points.

  1. Mask use reduces your chance of infection by 20%.
  2. Mask use reduces the chances of spreading the infection to others.
  3. Extended mask use can reduce the oxygen levels in your blood, which can create other problems. Depending upon your health situation, you may need to consider this issue.
  4. If you are elderly with underlying conditions, you may need to look into the effects of wearing a mask versus not wearing a mask.

So, yes, wearing a mask can be very helpful.  But, it can also be harmful.  It is not a simple issue, no matter how much you want it to be simple.

As a HUGE critic of the lockdowns, I am not a critic of wearing a mask.  It does serve a purpose and is part of an excellent COVID fighting strategy.  Mask use is not about hype, but we do need to be smart and selective.    

The most essential concept is wearing the mask to protect those who are most at risk.  Those people include the elderly and those with underlying conditions.  So at worst, keep a mask with you and pull it up when anyone around you is older or if they are wearing a mask.  If they are wearing a mask, then they may need protection.  Don’t be an arse.

If you are young and healthy, you may not even know that you are infected, so please be careful around those who are at risk.  Again, don’t be an arse just because you are not at risk.

I would suggest not wearing the n95 or higher masks, or at least do not wear them for an extended period of time, mainly depending upon your health situation.

Certainly, where the mask where it is required.

Bottom line, stop yelling at people who don’t do what your reductive thinking believes they should.  The issue is just not that simple, no matter how much you think it is. 

Can’t we all just get along and work together?


Let’s get straight to the point, the “record” number of COVID cases touted in the media has very little to do with the number of COVID infections.  If you think those two things are the same, the media has brainwashed you. 

If you read my book, The FEAR-19 Pandemic, then you already know what I mean.  But I will do a quick review for everyone else.   The number of “cases” is just the number of people who have tested positive and that number is generally a small percentage of the total infections.  For example, here is a chart referencing antibody studies from all over the world.  This chart shows the percentage of COVID infections in that area that were never “cases” of COVID.


The percentage of infected individuals that typically get tested is somewhere around 10%.  That leaves 90% of infections that go unconfirmed.  The reason that 90% did not get tested is that they were asymptomatic (not sick), or they had minor symptoms.  They did not need to get tested.  The number of “cases” is just a small percentage of the number of infections. 

This information is why the “record” number of cases stat used by the media is just fear-mongering.  It is a useless stat without context.  If 90% of infections were going unconfirmed, all you have to do to increase the number of cases is to test more, which is precisely what is happening. 

Let me show you a chart from

It’s like they were initially counting all of the oak trees and then started counting the oak trees and the pine trees announcing that we have a “record” number of trees.

We are not having a record number of infections.  However, there is most likely an increase in infections at this point.  The best chart I have seen is from the same website,  This chart incorporates the rise in testing to adjust the numbers more accurately.

When adjusting for increased testing, you can still see an increase in infections, just not a record pace.  The “record” number of cases is entirely fake news using artificially inflated stats.

However, there is one more critical point.  The formula used for this chart incorporates the increase in testing that took place back on April 23rd, and the amount of testing has increased even more.  In the last nine days, there has been an average of 586,000 tests a day, which is yet another significant increase.  They may need to make a new adjustment to their formula to ensure that the data is accurate.

Now, I will give you one more chart, which is the most important.  This chart shows why they may need to adjust their formula.  The number of daily deaths was following the trajectory of the adjusted case numbers until about a week ago, right when we again increased the amount of testing.  Once again from, it is a great site if you want to look at numbers and charts.

The number of deaths continues to drop, and we are currently lower than we were back on April 1st.  Now, ask yourself.  Why is the media touting a fake, manipulated number of “cases” instead of the fact that average deaths continue to decline?  Any chance they want you to be scared?  Any chance the media wants dramatic news more than an informed public?

The CDC released their report on antibody testing from the USS Theodore Roosevelt.  You may remember the USS Theodore Roosevelt because it was the Navy ship whose captain was fired because of his reaction to the significant outbreak on his ship.

There were several fascinating findings from the study, and I am going to share a few.  Before sharing the results, let me remind you that there are two types of tests for COVID.  The first is for the virus itself and indicates current infection.  The second type of test is for antibodies to COVID.  The antibody test shows whether someone was previously infected with COVID and has developed antibodies.

Here are some of the interesting results.  First, out of the 382 individuals tested, 228 (60%) tested positive for antibodies.  By itself, that is a shocking number and shows how much COVID can spread, especially in high-density areas.

Since 228 sailors tested positive for antibodies, that leaves 154 (40%) who did not.  Of those 154, ten more individuals were positive for the virus at the time of the testing.  That identifies 238 individuals in the survey group who were currently or previously infected with COVID.

  • 382 individuals tested for COVID and COVID antibodies.
  • 228 tested positive for antibodies (60%).
  • 154 did not have antibodies (40%).
  • 10 out of those 154 did test positive for the COVID virus.
  • That makes 238 individuals who were currently infected, or previously infected out of 382 (62%)

This study presents a unique opportunity as it provides us with the perfect control group.  We can compare the infected individuals against non-infected individuals to allow us to clearly identify the differences between the two groups and learn a lot about COVID.

Of the 238 who tested positive for the COVID virus or antibodies, 44 individuals (18.5%) reported zero symptoms; they were asymptomatic.  One in five of infected individuals were asymptomatic.  What about the individuals who did not test positive for COVID or antibodies?  Out of those 144 individuals who were COVID negative, only 54 (38%) were asymptomatic.  Yes, 90 individuals (62%) who were not infected had symptoms.

This finding is a critical point because you cannot merely assign all of the reported symptoms to COVID, or why would the 90 uninfected individuals also report symptoms.

It may come as a shock to you, but COVID is not the only virus in the world.  There are a ton of other viruses circulating all the time that will cause many of the listed symptoms.  And there are also bacterial infections and medical conditions that can account for symptoms similar to COVID. 

If 62% of the control group (individuals who tested negative for COVID or antibodies) were symptomatic, then you can assume that 62% of the individuals who tested positive for COVID had symptoms because of other reasons as well.  This detail is why you use control groups in studies, to help determine which symptoms and what percentage of those symptoms are caused by something, in this case, COVID.

Let’s look at the results from the survey of reported symptoms.  I will show you the percentage of infected and non-infected individuals who reported specific symptoms and then the percentage difference.  This comparison will allow us to determine which symptoms, and the portion of symptoms, that are caused by COVID.

Now, if you add the 18.5% of infected individuals who were asymptomatic to the 62% of symptoms that could be the result of other things, you get to 80.5% of individuals who did not have a symptomatic reaction to COVID.

And this tracks perfectly with the 19.3% difference in seeking medical care between those infected and not infected.  About 20% of COVID infections will result in symptoms significant enough to seek out medical attention.

If you read my book, this tracks pretty well with the science I have already shown you.  Actually, this number is a little low.  In the book, we used antibody studies from all over the world to show that approximately 90% of COVID infected individuals were “not sick” enough to seek out medical care or get tested.  Here is the chart.

Did more people on the Navy ship access medical care?  Yes, probably because it is much easier to access readily accessible medical care.  Out in society, that number is much closer to 90% instead of 80% in this survey.

This information again reveals the lack of severity for COVID infections in comparison to what the media has promoted.  The 0.8% of infected individuals in the study who required hospitalization also indicates the low severity of COVID in this age group.

Over 80% did not require medical attention for COVID, and only 0.8% required hospitalization.

There is another data set from the report that is also extremely enlightening.  The participants filled out a survey about their prevention behaviors at the time of the testing.  Here is the same chart from above with those prevention behaviors comparing the percentage of infected versus not infected.

Hand washing, hand sanitizing, and cleaning of personal areas had little impact on the percentage chance of becoming infected.  Social distancing, isolation, and face coverings had a more significant effect.  But how much?

When compared to the control group, social distancing reduced the chances of becoming infected by 16.3%.   Avoiding common areas decreased the chances of becoming infected by 13.9%.  Avoiding common areas and social distancing is similar in effect to the lockdowns.  We all know that people were still out, but not out as much as usual, and they were social distancing with more regularity.

We can use this information to determine the overall impact of the lockdowns.  We can try to determine the percentage of infections avoided.  Let’s begin by determining that number based upon this study.

  • Social distancing decreases the chance of infection by 16.3%.
  • Avoiding common areas decreases the chance of infection by 13.9%

If you think about it, the individuals who socially distanced most likely avoided the common areas as well.  However, if we want to determine the effectiveness of the lockdowns, we can be as conservative as possible.  Plus, it is easier to avoid other people out in normal society than on a ship.

We will add both of those numbers together and speculate that the lockdowns (avoiding common areas and social distancing) reduced the chances of becoming infected by 30.2% (16.3 + 13.9).  So, it is reasonable to assume lockdowns decreased infections by approximately 30%.

However, infections are not the same thing as cases.  As the antibody studies from all over the world indicated (chart above), only about 10% of infected individuals would have been sick enough to seek out medical care and get tested.  That reduces the increase in cases from 30% to 3%.  Remember, the number of infections is not the same thing as the number of confirmed cases.

With about 2.1 million cases currently in the United States, that means that we reduced overall cases by 63 thousand cases.  Yes, we shut down the majority of the country for 63 thousand fewer cases of COVID.  Not deaths, but cases of COVID.  

I keep hearing how we saved millions of lives.  How?  By what science?  They keep telling us about these hypothetical mathematical models that predicted all these deaths. However, those models used flawed theories that were wrong at the time (read the book) and have repeatedly been proven wrong by emerging science. 

The media will keep reporting that information because it backs up everything they have been saying and promoting.  But it was all based upon fake statistics.  It is only philosophy, not science.  Yes, this study was a small sample size, but it is science none the less, not the flawed theories and fake statistics behind the models.

Millions of deaths in the United States without lockdowns?  Well, bless your hearts for trying to save everyone.

Source: CDC Study


On May 25th the CDC released its most recent report on COVID-19.  There is a lot of useful information in the report, but there are a couple of things I would like to spotlight.

The first key statistic is that their best guess estimate for the mortality rate of symptomatic cases is 0.4%.  They also estimate an asymptomatic rate of 35%.  Using that rate, it would bring the infection mortality rate of COVID to 0.26%.

Here is a quick chart comparing the CDC’s current best guess infection mortality rate of COVID to some bad years of the flu.  The worst year recently was in 2018 which had an infection mortality rate of 0.13%

The question becomes if future estimates will go higher or lower.  There is little doubt in my mind that it will continue to go lower because they are projecting a 35% asymptomatic rate, which is almost certainly low.  This CDC report was based upon information through the end of April.

On May 5th, the CMMID Repository (Centre for Mathematical Modeling of Infectious Diseases) released a study reviewing the data from the Diamond Princess Cruise Ship.  Their math indicated that the asymptomatic rate on that cruise ship was 74%, and this is in a population that averaged just under 60 years of age.  At this point, we all know that COVID’s virulence decreases with age, so the overall rate of asymptomatic infections could be even higher than the 74% the CMMID is indicating.

Based on recent antibody studies, the rate may be as high as 90%, but that is not as solid as the math from the CMMID.  Let’s just propose that the rate of asymptomatic cases is 75%.  That would bring the infection mortality rate set by the CDC down to 0.1%.

In case you are not familiar with that number, it is generally associated with an “average” year of the flu.  This means that the infection mortality rate of COVID is likely to be akin to the average year of the flu.

However, the problem with COVID is that it is highly contagious.  This increases the chances of any one person becoming infected  making it dangerous to us as a whole, even if it is not more severe individually.  The good news is that it was a novel coronavirus and no longer is.  COVID will never again be as dangerous as it was because it will never be new again. 

And once we have a vaccine for the most vulnerable, it will be even less deadly.  There is hope folks, the sky is not falling, and we are not entering a new normal.