THE COVID-19 ERRORS

Many mistakes were made in the determination of what needs to be done in the Covid-19 outbreak:

1. Science has not predicted what has actually happened.
2. Trump's predictions in the virus behavior were based on what his scientists told him.
3. New strains of the Coronavirus have appeared.
4. Mutations may have made masks and distancing less effective.
5. Mutations may have made COVID-19 less lethal.
6. Discoveries of what to not do to treat COVID-19 have made it less lethal.
7. Democrats are much more afraid of COVID-19 than Republicans are.
8. Democrats want the economy to fail from COVID-19 to get a Socialist economy.
9. Democrats are using COVID-19 to try to steal the election.
10. The Positivity Rate is a flawed measure of the spread of COVID-19.
11. There are two different kinds of COVID-19 tests: infection and antibody. They have different results.
12. Sports are being played, though COVID-19 is playing hob with schedules and outcomes.
13. The scariest part of Halloween is that it was cancelled.

The Covid-19 Virus is Changing:

With every reproduction of the virus in every infection, mutations are possible.

Mutations in viruses are more likely because the virus is using the replication process of a different organism, increasing the probability of errors.

Natural selection is choosing the viruses that are most successful at reproducing:

1. The virus that kills the host does not reproduce. It dies off.
2. The virus that in some cases can get through masks and social distancing reproduces more than the one that does not.
3. The virus that causes very few symptoms does even better. It thrives.

Nobody is to blame because we have no way to know all of what is happening.

Two kinds of COVID-19 tests:

The infection test detects the presence of live COVID-19 viruses in the body.
- The person testing positive is infected and is contagious.
- The person testing negative either never had the virus or have recovered.

The antibody test detects COVID-19-fighting antibodies in the blood.
- The person testing positive is immune if the infection has ended.
- The person testing negative either never had the virus or has not yet made antibodies.

The positivity rate depends on the infection test.

Nobody is to blame. The newscasters just want something to report.

Making sport of sports:

Whether or not a given sporting event is allowed to play depends on state and local permissions at the time.

If players on one team test positive, that team forfeits. No sense of fairplay at all.

Government determines how many spectators can attend (cardboard facsimiles???).

All of the players must stay 5 feet apart.

Football will have two kinds of face mask penalties.

The final season champion depends on chance as much as skill.

Nobody is to blame. The sports addicts just want to watch sports.

The Covid-19 Positivity Rate:

The Positivity Rate is being used to determine how much normal activity the government allows. But there are many errors in both the positivity rate and interpreting it.

Calculating the Positivity Rate: Two methods

1. Divide the number of positive cases (people) by the number of people who have been tested
2. Divide the number of positive tests by the number of total tests

However these are also fraught with error. The causes of the errors are:

• The rate assumes that the tests are randomly distributed across the population.
• The tests are often refused to people who are not showing symptoms. This makes the positivity rate higher than it would be with a random sample.
• People who are not showing symptoms are often told to not get tested. This makes the positivity rate higher than it would be with a random sample.
• People who are not showing symptoms have a right to not be tested. When they do not, it makes positivity higher than it would be with a random sample.
• Often people with the disease are tested multiple times until they test negative. This makes positivity higher than it would be with a random sample.
• Covid-19 tests are not 100% accurate. There are false positives and false negatives.

Now we compare the various possibilities (US data from 09/09/2020):

Notice that the positivity rate is based on only those tested. But the real positivity rate of the country depends on all of the population. For the positivity rate of 22.29% given, the real positivity rate can range from 2.01% (if all untested are negative) to 38.41% (if the untested are 40% positive). The false assumption is that the untested are infected at the same rate as the tested are infected.