Making sense of COVID-19 Statistics

Some people are led to believe that 5 in 100 people (5%) are dying. When you go to a site like this: https://www.worldometers.info/coronavirus/, that certainly could appear to be the case at first glance. But is it? Let’s look at the data to assure you that 5% of people are not dying. The data shows that it is not even close to 5%. Are 5% of those sick with COVID dying of it? No, the data says that isn’t accurate either.

We are getting closer to 8 billion people in the world, and if 5 out of 100 died, that would mean that 400 million people would be dead or are going to die. COVID hasn’t killed that many, nor does the data suggest that it will kill that many.

Let me help you with the data and numbers, so you aren’t overly scared. You can be adequately scared, but you shouldn’t be overly scared because you were either didn’t understand the data or the data was misrepresented to you. Is COVID bad? Sure. It has killed an estimated 460k people as of today, so yes, it is a bad sickness, especially for those who experience the worst symptoms, but bad is not something data determines, it is something the reader of the data determines.

So when creating reports, it is all about proper data. Grouping the data is important. So let’s group the data first because that action alone will give us a clearer picture.

FYI (I am going to avoid any complex algorithms, and stick with basic math so anyone can understand this. However, feel free to comment with more advanced statistics.)

Grouping Humanity in the Statistics

So let’s create groups of people so you can properly understand the statistics.

• All humans. All 8 billion of us. This group isn’t very useful in our data, so let’s break it up into smaller groups.
  Note: The estimates are 7.8 billion, but I’m going to round up because recent studies in third-world countries have proved the population estimations in high-density areas have been low.
  • Group 1 – Has died from COVID.
  • Group 2 – Has been sick enough to go to the hospital, get tested, and tested positive for COVID but hasn’t died.
    We have a limited number of tests, so you only get tested if you are sick enough.
  • Group 3 – Has COVID, goes to the hospital, but symptoms are not severe enough to be tested, so the individual is sent home.
  • Group 4 – Has COVID but is asymptomatic or has such minor symptoms that the individual never went to the hospital.
  • Group 5 – Has been exposed to COVID but did not catch it.
  • Group 6 – Has never been exposed to COVID.
  • Group 7 – Has COVID and dies from it without ever going to the hospital or being diagnosed.
  • Group 8 – Died without COVID and was misreported (either accidentally or intentionally).

So now we have some valid groups, we can start to understand the data correctly.

There are other ways to group humanity. We can group it by age groups. The CDC does this, which is nice, as we can get information by age group.

Percentage Chart

Percentage	Quantity
100%8,000,000,000
10%800,000,000
1%80,000,000
0.1%8,000,000
0.01%800,000

What is the 5% (5 out of 100) statistic about?

Who are 5 in the 5 in 100 (5%) statistic who die? That is Group 1 (those who died from COVID)

Who are the 100? That is the sum of Group 1 and Group 2 (Those sick enough to get tested and tested positive). That means the number of Group 1 added to the number of Group 2.

Group 1 / Group1 + Group 2
460,671 / 460,671 + 8,241,079 = 0.05294 or 5%

(Note: The above is based on data pulled 6/19/2020 from https://www.worldometers.info/coronavirus/)

It isn’t 5% of all humans

When you hear 5% are dying, many people are led to believe that includes 5% of all humans. Clearly, the data shows this is not the case. As mentioned earlier, 5% of all humans would be 400 million. Only 8 million have caught the disease. So the data shows that only 0.1% of the population has been reported on the statistics as having COVID.

Group 1 and Group 2 only don’t even represent a full percentage of the people in the world. No, Group 1 and Group 2 together are only 0.1% of the 8 billion people in the world. 99.9% of the world is excluded from Group 1 and Group 2.

5% of 0.1% have died. That means of all the people on earth, COVID is causing a death rate of .005% of people on earth, assuming accurate data.

It isn’t 5% of those exposed

If a person understands it isn’t all humans, that person may still be led to believe it is all humans who have been exposed to COVID. Again, that is not the case. Most people who are exposed don’t catch the virus.

Let’s look at some examples of exposure that are facts, and use those factors to extrapolate data.

The Jazz have 15 players on their roster. Rudy Gobert and Donovan Mitchell both tested positive for COVID. Every single player on the team was exposed often.

(Here is an opinion, not fact, I will share: Had Rudy Gobert not been a star athlete for an NBA team, both he and Donovan Mitchell would likely have been in Group 4, but due to the power and wealth of the NBA, a minor sniffle as Rudy Gobert called it was enough to get the whole team tested. This is good for our stats as we have some numbers we can use to extrapolate data from.)

Can we be certain that all 15 players on the team were exposed to COVID? Yes. How often? A lot (sorry, this number is hard to get, so lets use numbers we have). Rosters have 15 players and 1 head coach. There are assistant coaches, staff, medical professionals, trainers, etc. Let’s only count the 15 players and 1 head coach and 4 assistant coaches for a total of 20 individuals.

• Number exposed: 20
• Number who caught COVID: 2
• Number who were asymptomatic: 1
• Number with minor symptoms: 1
• Number exposed but didn’t catch it: 18

So extrapolating from the Utah Jazz experience, only 2 in 20 exposed caught it. That means you have a 10% chance of catching it, right? Wrong! It is much, much lower than 10%. We used simple numbers, the 15-player and 5-coach NBA team for that calculation. But everyone exposed is a hard number to quantity. Rudy Gobert and Donovan Mitchell surely exposed many, many more people in the Jazz organization and in their personal lives who didn’t catch it. The estimate is likely ten times the number of Jazz team members. So the chance of catching it when healthy and when exposed is significantly lower than 1%.

If we estimate very conservatively (extremely low estimate) that every person exposes at least 20 others, then the number of exposed is 20 times greater. That takes the death rate of those exposed from 5% to .2%. But that was a conservative number. It is likely that those with COVID exposed many more than 20 people. COVID is supposed to have a long gestation period and be contagious before symptoms, meaning the average person could expose hundreds of others. That puts the death rate at far less, closer to .04% to .02% of those exposed.

Now, also take into account the number of interactions? How many times did Rudy Gobert and Donovan Mitchell interact with the rest of their team? Well, in a single practice, there are over 100 interactions, between bumping, fouling, defended, communicating, sharing the same ball, etc. The contagious period is supposedly weeks. That means that 13 players and 3 coaches didn’t get the sickness despite likely hundreds (perhaps thousands) of interactions. This exact number of exposures is hard to quantify. But let’s conjecture that there were 1000 exposures. That means 18 players were exposed 1000 times and didn’t get it. That means your odds of being exposed and getting it is somewhere less than 1 in 1000, or .1%.

Now, the Jazz are a healthy group. Not all statistical variations are in your favor. You can be sure that a person with an unhealthy lifestyle is more likely to get sick than a healthy Jazz player. Remember, the Jazz have a lot of people in their organization that had many interactions with the Rudy Gobert and Donovan Mitchell and didn’t get sick, suggesting (but not proving) that extreme healthy lifestyles vs average healthy lifestyles may not play a significant part in whether the disease is caught or not.

It isn’t 5% of those who have COVID

We have limited testing. So only those with the worst symptoms are getting tested.

• What about Group 3 (Has COVID, goes to the hospital, but symptoms are not severe enough to be tested)?
• What about Group 4 (Asymptomatic).

How many of these are there? Well, extrapolating from the Utah Jazz, two out of twenty on the team would have been in these groups. So nobody in the Jazz would have been in Group 1 or Group 2, which means that those exposed who reach Group 1 and Group 2 combined is less than 1 in 20. It appears that for every 1 person sick, there are at least 2 that are asymptomatic or have minor symptoms. That means that the death rate of those who catch COVID is at least 1/3 the reported value.

It is only 5% of those sick enough to be tested?

The 5% death rate is only among those who both caught COVID (which the data show is a rare .1% of the population) and also have symptoms bad enough to be tested. This only includes Group 1 and Group 2.

The data clearly shows that 5% of those with the worst symptoms are dying.

What are your odds of catching COVID?

Well, right now 0.1% of people in the world are listed as having it. Looking at the Jazz extrapolation, with hundreds of interactions, few people caught it. So any given person could have hundreds of interactions with a contagious COVID carrier and not get it.

The numbers aren’t there, but if 0.1% have it, and you can interact with them a hundred times without getting it, then that puts the odds around .001%. But these odd don’t take into account the type of interaction.

Is the data accurate?

No. Sorry. The data is what we have. It isn’t accurate. How inaccurate is the data? It is next to impossible to know.

Let me list you some inaccuracies:

1. 1. Many people never go to the hospital. People could be dying without diagnoses. How many? There is no way to know. But this is rare, and it wouldn’t significantly change the numbers
   2. What about Group 7 (Died of COVID but never went to the hospital). This number is in favor of deaths being higher.

1. The US has 50 states reporting in different ways. Not to mention every hospital may be reporting differently. then look at the rest of the world. All the countries in the world.
2. Various governments have tainted the data by offering money to facilities that report deaths by COVID. This leads to Group 8. Money is a huge motivator. It always invalidated data by creating bias.
   FactCheck.Org clearly indicates that the payments are a fact. It claims that there is no evidence of misreporting (however, this is evidence of misreporting (see here), yet other articles discuss guessing without tests but also mention Group 7.
3. The COVID testing isn’t even close to 100% accurate. Some reports are that is as low at 60% accurate. That makes this data highly inaccurate.
4. In a care center for the elderly, if one person gets sick with COVID, all deaths in the care center are COVID deaths without further testing.
5. There are more people listed as having COVID than tested that have been created, proving that many are guessed to have it based on symptoms. UPDATE: The CDC is now listed the count confirmed vs not comfirmed.
6. They can’t keep the has COVID vs has the antibodies numbers straight.

At best, the data is just less accurate than an estimate. At worst, the data is only a little more useful than a wild guess.

Fact vs Opinion: Only facts and data matter in statistics. Opinions are not helpful. Guesses are not helpful.

Facts

• Hospitals are getting paid to report COVID deaths
• Testing is not a requirement to be added to the statistics. The following CDC guidelines state: In cases where a definite diagnosis of COVID–19 cannot be made, but it is suspected, …, it is acceptable to report COVID–19 on a death certificate as “probable” or “presumed.” https://www.cdc.gov/nchs/data/nvss/vsrg/vsrg03-508.pdf. OK, so not all COVID deaths are tested. This goes both ways, though: Some who die from COVID aren’t marked, some who die without a COVID test are marked as having COVID.

Opinions: (these don’t matter in statistics)

• Hospitals are (or aren’t) abusing the COVID death payments.

Guesses:

• The number of deaths is likely higher
• The number of deaths is likely lower

The numbers are skewed heavily by age

90% of all COVID deaths are over the age of 65, according to this data (https://data.cdc.gov/NCHS/Provisional-COVID-19-Death-Counts-by-Sex-Age-and-S/9bhg-hcku).

So that 5% (which is only of the more symptomatic and sickly) becomes 0.5% if you are 52-64.
It becomes 0.2% if your age is between 35 to 44.
Ages 25 to 34, your chances of dying are 0.00029%.
15-24, you are 0.000052% of dying from COVID. Yes, there are four zeros after the decimal point.
Ages 5 to 14, there are only 13 deaths in the US. The Flu has 48.
Under 5, also has 13 total deaths in the US.

The numbers are skewed by Location

In Utah (my state), the number with COVID is 17,462 to only 158 deaths. That is only .9% and not 5%.

Perspective

In this section, we will give you stats of other issues you haven’t been worried about, so you can compare COVID to them.

1. Pneumonia deaths are still higher than COVID deaths in all age categories. Keep in mind that Pneumonia also benefited from the social distancing, so the comparison is fair.
2. Lightning deaths last year in the US is listed at 20. Ages 5 to 14 have only 13 COVID-related deaths. Your children are as likely to die from lightning as from COVID.
3. The Flu killed 46 children ages 5-14 this year, to COVIDs 13. A child is 3-1/2 times more likely to die from the flu. Again, the Flu benefited from social distancing the same as COVID. However, at ages 75-84, COVID is listed at while the Flu is list as only 1,330. The older you are, the more you should be much more concerned about COVID than the Flu.
4. Car Accidents killed 36,560 people in the US in 2019. COVID has killed a similar amount, 34,435, of people ages 85 and older in 1/2 a year. That is scary for the elderly. However, everyone under 54 years old is more likely to die from a car accident than COVID.

So one of the reasons this article was written was to help you calm down and realize it isn’t so bad. Well, if you weren’t freaking out about Pneumonia, Lightning, the Flu, or Car Accidents, then you probably don’t need to freak out about COVID. However, knowing there is a second virus as deadly as Pneumonia is disheartening.

The data shows that worrying for your children is completely not necessary. If you aren’t worried about your kid being hit by lightning, then you probably don’t need to freak out about COVID.

Zero evidence of a child passing COVID

To date, there is no evidence of children spreading COVID-19. Despite the fact that tracking where and from whom a person contracted COVID is high priority, there is still not one reported instance of a child spreading it.

Even despite the few children with COVID having significant exposure to others, there is not 1 single reported transmission from child to anyone else.

Despite numerous studies, opinions appear to rule statistics here. There is an opinion that children will spread COVID-19. The data does not support that opinion.

0 verified transmissions from a child is a statistical fact.

Conclusion

The data is presented in a way that is misleading. It is presented as 100% trustworthy data when it isn’t anywhere close to trustworthy. The scariest stats are being cherrypicked. It may or may not be intentional. Such suppositions are not what this article is about. This article is about helping those who are smart but not trained in data analysis get a better view as to what the data means.

The death rate of COVID for the earth’s population is around .005%.  .005% is a very different number than 5%.