## Saturday, October 24, 2020

### Normalizing risk

"Normalizing" is a word used by engineers when they divide some unknown by a known, easy-to-visualize parameter.

Examples might include reporting acceleration rates in "Gs", or the acceleration rate of gravity, or reporting the velocity of a flying object in "Mach" the speed-of-sound in air under normal conditions.

I chose the US average death-rate due to traffic accidents as the denominator when normalizing the risk of death-by-Covid.

On average, there are 11.2 deaths per 100,000 people due to traffic accidents in the United states in a year.

There are 107,000 residents in Eaton County, Michigan. We are credited with 11 deaths due to Covid since March, 2020. That yields an annualized rate of 15.4 deaths per 100,000 people.

Normalized against the rate of traffic fatalities, you are one-third more likely to die from Covid in Eaton County than you are to die due to a traffic accident.

1. I am not an engineer, you are so I sill defer to your knowledge in this ,but, isn't comparing deaths per 100,000 in Eaton County to unrelated deaths nation wide like comparing shark attack deaths in the U.P. to the national average? ---ken

1. That is a valid concern.

National death-rates due to traffic accidents includes accidents from extremely rural areas (including collisions with livestock) to deaths in urban areas to deaths on freeways.

Eaton County has all of those risks although not exactly in proportion to the national exposure.

If I looked at just traffic deaths in Eaton County I would run into the problem-of-small numbers. The number would jump around every year.

By using the national number, it stays more stable. It also incorporates the fact that drivers from Eaton County drive to Detroit Metro Airport and to other urban destinations. It is a risk that we are comfortable with and willingly take, most of us on a daily basis.

That makes it a good number for the denominator.

The fact that I am compared mortality due to a communicable disease with mortality due to traffic accidents might not seem intuitive. The reason to put them both in the same basket is so decision-makers can reference Covid risk to a "Platinum yardstick" that is easy to access emotionally.

2. Gotcha. I see the point about it being easy to access emotionally. We can all relate to traffic accidents thereby having a "yardstick" which makes it fit into our personal tolerance level of acceptable risk. I didn't think about commuting to the Big Cities. Around here going to Houghton is as risky as it gets and I don't even like to do that anymore. They are up to 5 stop lights there now. Too much traffic for me! ---ken

2. Garbage in...garbage out. There is abundant evidence that the proclaimed covid deaths are not accurate.

1. Agree. The test include a majority of "false positives"
the deaths "due to" - and nothing else, are 6% of the total, according to the CDC.
The guy who died in a motor bike accident who'd "tested positive" the week before was recorded as a corona virus death.

The whole barrel of nonsense is about much more than the WuFlu.

3. More importantly- who is doing something about these shark attack deaths in Michigan...both in the U.P. and lower Michigan ??? Sounds like a job for the Female Body Inspectors- if they can tear themselves away from their work of running a coup against the President and investigating the unauthorized copying of VCR tapes and DVDs.

4. Shouldn’t your conclusion be “with Covid” rather than “from Covid”. CDC admits on average there are 2.6 co-morbidities per death and last time I looked approximately 12,400 of the 207,000 deaths were caused solely by Covid. As of 10/21 this information appears on CDC website: “ Table 3 shows the types of health conditions and contributing causes mentioned in conjunction with deaths involving coronavirus disease 2019 (COVID-19). For 6% of the deaths, COVID-19 was the only cause mentioned. For deaths with conditions or causes in addition to COVID-19, on average, there were 2.6 additional conditions or causes per death. The number of deaths with each condition or cause is shown for all deaths and by age groups.” https://www.cdc.gov/nchs/nvss/vsrr/covid_weekly/index.htm

5. Dr. Frederick Frankenstein : [to Igor] Now that brain that you gave me. Was it Hans Delbruck's?

Igor : [pause, then] No.

Dr. Frederick Frankenstein : Ah! Very good. Would you mind telling me whose brain I DID put in?

Igor : Then you won't be angry?

Dr. Frederick Frankenstein : I will NOT be angry.

Igor : Abby someone.

Dr. Frederick Frankenstein : [pause, then] Abby someone. Abby who?

Igor : Abby... Normal.

Dr. Frederick Frankenstein : [pause, then] Abby Normal?

Igor : I'm almost sure that was the name.

1. Why shankyou, Doctor

6. Here's my beef with your normalizing study, Joe:

IF you are using "U.S." government data, then I don't trust the source. Just like Justice Scalia wrote of the Obamacare debacle- "Words mean things". And numbers (with units) mean things to engineers and scientists, but not to the public servants that live off tax proceeds.

The use of computer modelling to "crunch numbers" and promote false narratives has ruined all things federal. Or U.S. Or national.

Rather than trying to model the risk of the narrative Woo-Floo, may I suggest getting confessed up, and in a good light with the Creator. None of us are getting out of this alive.

Peace on Earth to men of Good Will.

Readers who are willing to comment make this a better blog. Civil dialog is a valuable thing.