COVID cases from winter and testing

Based on COVID SIR model, fitting data to (a) best information about unknown/known case ratio, (b) portion of declining mortality attributed to including less critical cases in reported data, (c) projections which fit incoming new data.

I have a background in safety and modeling the combination of human behavior and complex systems (spacecraft, transportation, etc.) to determine accident or crash rate. Since late March I’ve been modeling COVID, gradually developing models as sophisticated as any available.

In July I became aware that the relative number of unknown cases was diminishing fast enough to undermine projection accuracy. I went on vacation for a month instead of looking into it, as I was totally burned out.

Recently the US and European media have been reporting “spikes” in cases and talking about severe lockdowns. That scared me, because I think lockdowns are more damaging that people realize. According to one paper, half as many people died from the lockdown in the US in March and April as from COVID for reasons such as having heart attacks and not going to the ER.

A seasonal rise in cases – similar to the flu – was baked into COVID from the start. This was WELL KNOWN by April. Many studies were done based on temperature and humidity and several papers were published. The average seasonal effect for the US is 20%, but colder regions like NY have a 30% effect.

Spikes over the summer were from “easing.” Spikes now are likely to be from cold weather.

But the spike now, should it be so large? Where I live (Houston) I do not see any “easing” going on. It gets tighter every week for the last two months.

So reluctantly I began two weeks ago to look into the changing case ratio. If you do a lot of testing, the number of reported cases goes up, even if the “actual” number of cases goes down or remains the same or only goes up slightly.

It is easy to check this. If less critical cases are included in the totals, mortality should look like it is going down. It has, in the US from over 8% of reported cases to only about 1%.

Of this factor of 8, by fitting projected model data to actual new data coming in, it appears a factor of 4 is due to increased testing, and a factor of 2 is due to improved medical understanding of and handling of critical cases. Not everyone needs intubation, and steroids keep the body from killing itself. COVID blocks a friend/foe identifier on lung cells, and the body attacks itself and dies even while the virus load is declining.

The results are startling. Our lying, hateful president is finally right about something, like a stopped clock is right twice a day. Who’d have thought.

We should not go into a severe lockdown. Instead we should skip phase 3 trials and immediately start vaccinating people. Approximately 20,000 people in the US will die for every month we delay.

We’ve never had a situation like this is vaccination history. We’ve had situations where the number of people who might die from a bad vaccine was a few hundred or thousand, and the number of lives saved by the vaccine was lower, maybe a few dozen. But in this case the numbers are reversed. Dramatically.

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