1/Why there is no such thing as a "healthy" immune system -- Tesla Autopilot version

I have a Tesla. Best car I've ever owned, by far.

Only flaw is that Elon Musk is a complete asshole.

Part of his assholery is selling a fantasy that a car can drive itself
2/It can't. And if you give the the chance to drive itself, it's going to kill you

The autopilot in my car is made up of hardware -- the stuff that drives the brakes, the steering wheel, the accelerator, the battery

And the "eyes" -- the cameras that look around for threats
3/All of that is pretty straight forward. We've known how to make motors, servos, electronics -- even ccd cameras for a long time

The problem is that all of that is brought together and controlled by...

4/Specifically "Artificial Intelligence" running in the computer(s) in my car

The computer takes what it "sees" -- information from the cameras, speedometer readings, etc.

And makes decisions about what to do. Hit the brakes or the accelerator? Turn the wheel?
5/It can handle things when they are optimum. The lighting is right, the road has well-defined lanes, it can recognize people, other cars, etc.

But things are never optimum. So it hits the brakes when it shouldn't, it turns the wheel when it shouldn't, etc.
6/The human immune system is a lot like my Tesla's autopilot

It consists of hardware that is well known and understood.

Your skin, the hairs in your nose, snot, fever, diarrhea, etc. these are all parts of our innate immune system -- the hardware of my Tesla
7/When people talk of having a "healthy" immune system, this is what they talk about (even if they don't know it)

Keeping our vitamins, our exercise, etc. all at a level that this front line of defense (the innate system) is in good shape.
8/But there is another part of our immune system: the adaptive part.

This is the computer. It's where the intelligence is.

It consists of an elaborate pattern matching system that looks for things in the body that should not be in the body -- cancer cells, viruses, bacteria
9/And when it matches one of those, it attacks it. Both with things called T-cells, which kill our own cells (thus are very effective at fighting cancer), and B-cells, which neutralize (kill) the invader virus itself

Just one little problem...
10/Often the computer part of our immune system makes a mistake.

It doesn't recognize a threat, letting a pathogen run free. This is what HIV does -- it makes the computer blind

Or it recognizes a threat where there isn't one. The computer becomes paranoid and over-reacts
11/This is what an autoimmune disorder does. It causes the computer to trigger an immune response where its not needed

This is what my late wife died from. She was perfectly healthy, but her immune system felt otherwise.
12/Her body had found the enemy. It was her body, itself

Don't let anyone fool you. We know next to nothing about how the adaptive immune system works.

We know how to shut it down (steroids) and we know how to speed it up (therapeutics).
13/But we don't know how to make it make the right decisions. We don't even know why it makes the wrong ones

The medical community has invented a lot of fancy-sounding words for "your immune system is malfunctioning, but I don't know why"

Reumatism. Reumatoid. Idiopathic
14/It is estimated that autoimmune disorders are the third largest cause of death for women (as they were for my wife).

We don't really know because we don't really know much about women's health. We know a little more about men's health, but not much more
15/I want to leave you with one thing, here

There is no such thing as a "healthy" immune system -- at least not at the adaptive layer.

So the next time some COVID denier tells you he doesn't need to wear a mask because he's so healthy...

Tell him he's full of shit
Here's a picture of my late wife and our son at the Cleveland Clinic on the day that the doctors there examined her and said "Probably not serious."

I exploded: "She can't walk across a parking lot!"

She died, two weeks later. Her "healthy" immune system killed her

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More from @greg_travis

4 May
Case study: Michigan

Michigan currently has the highest deaths per day (per capita) of any US state.

It is an instructive case in both the effectiveness of lockdowns as well as the non-seasonality of COVID
Michigan, like many states in spring of 2020, had an explosive first wave. Lockdowns were put in place but not soon enough to prevent the first wave from generating the highest deaths per day of all three weeks

But notice how the sharp uptick in deaths is followed very quickly
by a sharp downtick.

This is a shape similar to what Belgium experienced -- a very "pointy" (steep and high) initial wave of deaths

This is a common pattern that we see when:
a. There is a comprehensive attribution of COVID deaths -- for instance Belgium confirmed COVID cases
Read 12 tweets
4 May
There are those of us who have worked with "the data" for some time, but who are not data scientists

And there are those who know all about data, statistical analysis, etc. but who have little "boots on the ground" experience

There is a natural antagonism between the camps
Which is counter productive

The boots on the ground folks, of which I include myself, need to get over their natural fear of being talked down to by the scientists

And the scientists need to acknowledge that those of us who have been slogging through the shit for decades...
probably gained some insight along the way

Demographic data and health data is UNBELIEVABLY dirty, balkanized and full of characteristics that make it very difficult to coalesce -- example: longitudinal data recorded across different time frames
Read 9 tweets
3 May
1/Some quick stats (consider these tailings off work I've done today)

Fattest county/city in the United States:
Owsley County, KY (men), Issaquena County, MS (women)

San Francisco County, CA (men) (except when I am visiting my mother), Falls Church (women)
2/Least physically active county/city in the United States:
Owsley County, KY (men), Issaquena County, MS (women)

Teton County, WY (men), Routt County, CO (women)
3/Shortest life expectancy:
McDowell County, WV (men), Perry County, KY (female)

Fairfax County, VA (men), Marin County, CA (female)
Read 6 tweets
3 May
Can anyone name a single pollyannish prediction about a country or region by @MLevitt_NP2013 that didn't turn into bodies stacked three deep in mass graves?

Because I am very worried about India
Seriously, help me out

Israel? Predict: 10, Actual: 6,366
USA? P: 170K, A: 600K
Brazil? P 98K, A: 408K
Italy? P: 20K, A: 121K
Peru? P: 14K, A: 62K
Russia? P: 13K, A: 109K
Bangladesh? P: 5K, A: 12K
Indonesia? P: 3K, A: 46K
Argentinia? P: 2K, A: 64K
Ukraine? P: 2K, A: 47K
Nigeria? P 840, A: 2063
Armenia? P: 666, A: 4K
Sudan? P: 615, A: 2350
Los Angeles? P: 3506, A: 24K
El Paso? P: 190, A: 2658
India? P: 33K, A: 220K
World: P: 700K, A: 3.2 Million
Read 4 tweets
3 May
1/COVID and Obesity

For a primer on BMI and the ranges used here, see:

Objective: I wanted to find a way to easily understand the relationship between body mass index (BMI) and COVID severity
2/Executive summary:

The underweight represent 1.5% of the US population and 2.4% of those admitted to hospital

Normal: 26.10% of US pop & 19.70% of those admitted

Overweight: 30.00% and 27.80% admitted

Obese: 33.20% and 36.20%

Severely obese: 9.2% and 14% Image
3/In other words:

Those with a normal or overweight BMI are admitted to hospital at a lower rate than their population prevalence (75% and 92% respectively)

The underweight, the obese and the severely obese are admitted in excess of their population prevalence (160%/109%/152%)
Read 7 tweets
2 May
1/BMI/Obesity primer

In advance of talking some more about this in a bit, I thought it would be helpful to know what we mean in a clinical sense when we say things like "Obese, Overweight, Underweight and Normal"
2/These clinical categories are calculated from a very simple formula:

Your Gender -> How much you weigh -> How tall you are

The result is something called the "Body Mass Index," or BMI
3/BMI is divided into ranges:

A BMI of 0-18.5 is considered underweight
18.6-24.9 is normal
25-29.9 is overweight
30+ is obese
Read 7 tweets

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