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April 10, 2020 - Real Coffe - Scott Adams
54:41
Episode 904 Scott Adams: Today I Blow Your Mind. Goes Well With Coffee

My new book LOSERTHINK, available now on Amazon https://tinyurl.com/rqmjc2a Content: Population density and herd immunity A gigantic range of uncertainty and models Differences between states The status of hydroxychloroquine testing? --- Support this podcast: https://podcasters.spotify.com/pod/show/scott-adams00/support

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Hey everybody, come on in.
It's time for a coffee with Scott Adams and the Simultaneous Sip and you came to the right place.
Because if you'd like to enjoy the Simultaneous Sip, all you need is...
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Fill it with your favorite liquid.
I like coffee. And join me now for the unparalleled pleasure, the dopamine hit of the day, the thing that makes everything better, including pandemics.
It's called the simultaneous sip.
Go. Mmm.
Extra good. A little extra good today.
Well, let's talk about stuff.
Number one, how in the world is our government going to reopen the economy in any kind of irrational way without telling overweight people to stay home?
How does that work, exactly?
Because it would be easy if the government said, hey, if you have one of these health conditions, let's say you have diabetes or asthma, you should stay home for a few months.
And I would be in that category and I'd say, okay, that's pretty objective.
It seems fair based on data.
I think I'll stay home.
But what happens if the government says, if you're fat, you ought to stay home and you can't go to work?
I mean, you could, but it'd be bad for the country if you did, because your weight would make you extra likely to end up in the ICU, which would be a problem for our healthcare system.
So please, if you're overweight, don't go to work.
It's a real question.
I'm not saying this to be funny.
I don't know how a country tells people to stay home if they're overweight.
And if they don't, if whatever guidelines come out of the next phase, I'm assuming that the guidelines for going back to work, whenever that happens, will be some kind of a filtered system where it's not everybody, it's the people who are safe.
How are you going to tell fat people not to go to work?
I mean, seriously, how are you going to do that?
I'm not joking. I'm not making fun of anybody for their weight.
I don't do that. I'm just saying, how do you do that?
Just from a policy practical perspective.
I don't know how that's going to work.
Alright, let's talk about the models.
Everybody wants to talk about the models that are so darn wrong.
So let me ask you this.
Do a little math. What percentage of the total population of the country is in New York City?
Well, I have the answer. It's about 2.6% of the whole country.
Now I'm just talking about raw population.
So of the whole country, New York City is 2.6% of all the people.
So what would happen if the rest of the country experienced infection rates like New York City?
Now I'll get to the point where you say there's a different density and the rest of the country is different.
So I'll address that.
But just Let's do the math first and then we'll adjust it.
So if the rest of the country got infections, let's say, in the same ratio as New York City, I'm not saying they will.
Just bear with me until I make my larger point.
But if they did, how many people would die in the whole country if the whole country became similar to New York City?
And I know you think that's not a good comparison, and I'll get to that.
Just hold that complaint for a moment.
So just doing the math, if New York City has over 7,000 deaths as of today, and they are 1 38th of the whole country, then if the whole country went the way New York City has gone, how many people would die?
And the answer is 38 times a little over 7,000 people.
And that would look like a national death rate of 269,000 people.
So if the rest of the country goes the way New York City goes, I'm not saying it will.
This is just for sizing things, all right?
I'll get to the point. It would be over a quarter million people would die.
You would call that a big problem, right?
Now I know the next thing you're going to say is, but Scott, Scott, Scott, New York City has more travel, has more density.
They got a later start.
So let's calculate that all in.
What I'd like to compare is a mitigation strategy versus none.
Now New York City is interesting because they are fully mitigated.
We're close to it.
But they got kind of a late start.
So you can't say that New York City is fully mitigated.
You could say it's It got a late start, but then it did a good job.
So it's maybe partially mitigated, half mitigated, something like that.
So the 7,000 deaths, if they had not mitigated, we all agree would be much higher, right?
But we don't know how much higher.
Would it be double? Would it be 10,000?
Let's say it was double.
Let's say the problem in New York City would be double, twice as many people dying, If they did no mitigation.
Is that fair? Would you say double?
Because the mitigation is pretty extreme.
It's like cutting out the whole economy, basically.
So I would say double seems reasonable.
And we're just sizing things, right?
I'm not saying that's accurate.
Just to size things. So, if the rest of the country went like New York City, and if, unlike New York City, they had not mitigated, what would it look like?
I think the numbers coming out of New York City suggest that it would be about half a million people or more would die.
If we didn't mitigate...
And it looked a lot like New York City.
But then you say, okay, but now you get to the good part, Scott, where you say the rest of the country is not at all like New York City.
So first of all, there's no density.
It doesn't matter. It doesn't matter.
Do you get why it doesn't matter that New York City is dense?
And the other ones don't, even though the density, of course, makes a big difference in how many people spread it, right?
Here's why. Because the time.
If you're not mitigating, the rest of the country has time to get just as infected as the people in the elevators in New York City.
In theory, if nobody mitigated, it would go like this.
New York City would very quickly get infected, because there's more density in travel and elevators and all that stuff, subways.
So New York City would quickly get to, let's say, 60% infection, at which point a little bit of herd immunity would start kicking in, and then the virus would start slowing down because so many people had been infected that you couldn't necessarily spread it as easily.
You'd be running into people who already had immunity.
So New York City would rather quickly get to herd immunity, but at the cost of tens of thousands of deaths.
A smaller place with less density would still get to 60%.
It just would take longer.
But remember, in both cases, there's no mitigation happening.
So the undense place will still get to 60%.
It just might take a month instead of a week.
So if you're comparing New York City's outcome to a less dense place, I would say the only difference is how long it takes to get to herd immunity, but they would both get there.
It would just be a difference of weeks.
So that's the first thing.
So I think that you could say, based on how many people have died in New York City, that the risk of not mitigating was probably somewhere in the half a million range.
Half a million people dead.
Now, the people who are saying that this is still flu-like levels of death, how do you explain the fact that they're doing mass burials in the park in New York City?
Have we ever had to do mass burials in the park because of the flu?
Are you still not ready to admit there's something different about this one?
It's a little extra deadly?
I gave this example last night, but I'd like to do it again, which is there are two ways that a virus can get you.
One is if it's extra deadly, but the other is if it's extra viral.
Because if it's extra viral, but not especially deadly, it's still going to kill a lot of people because so many people get it, that even if a low percentage die, so many people have it, that it's still a lot of people dying.
Compared to one that's really extra deadly, but it doesn't travel very far because the host dies so quickly.
Well, you can still get up to a lot of deaths because they die as soon as they get it.
So there are two ways.
Extra viral or extra deadly.
And those are your really bad situations.
But there's one that's worse than all of them.
What happens if it's extra viral and extra deadly?
What do you do? Well, that's at least a possibility that was presented early on.
When our experts were looking at China, correct me if I'm wrong, but when we were first looking at China and we didn't have good data and we were just sort of observing and not believing what they're telling us, did it not look like this might be the blackest of all black swans and the one that would be extra viral and extra deadly?
Now, I don't think it's going to turn out that way as more information comes in.
I think it's going to be extra viral, but not extra deadly.
It's still very dangerous, but probably lots of people didn't get a problem with it.
So, if the experts were looking into this fog of war and thought, we can't yet rule out that this is the worst of the worst kind, extra viral and extra deadly, because it's sort of looking like it.
We're watching them, what they're doing in Wuhan, and that's not normal.
They're not acting like it's some kind of normal thing.
So, was it reasonable for our experts to say, you know, shut down the country?
Because we don't know yet, but whatever's happening in China, that might be extra viral and extra deadly, and we've never seen one of those.
That could be like the big one.
So I don't blame the experts for being extra cautious.
If it turns out that that's what happened, they were extra cautious.
Because there were unknowns.
And certainly there was at least reason to believe that this was the big one, even if it turns out it's not.
But even if it's not the big one, let's say the big one would have killed tens of millions of people, I think this one would be, without mitigation, maybe half a million people.
And that's just multiplying New York City's population by the rest of the country, and making the assumption that New York City would get it faster, but if you didn't do any mitigation, eventually the whole country would have the same rate of infection eventually.
So what about the complaint that the models are completely broken and corrupt and wrong, And we made all the wrong decisions because the models were so flawed.
One of the people getting a lot of attention for that point of view is ex-New York Times writer Alex Berenson.
A number of you had been asking me, what about that guy that he's saying?
And he's saying that, you know, we've made this drastic change to shut down the economy, but it's based on modeling that doesn't line up with the realities.
So he's saying that the models are not showing to be correct, and therefore it was a giant mistake to use the models to make decisions.
But here's what Alex Berenson and almost all of the rest of the public does not understand, unless they watched me last night on my periscope.
Prediction models are not designed to predict anything.
If you thought they were, you would agree with Alex Berenson, and you would agree with all of the people who said, hey, you predicted it would be this, it's way off, and you've already changed your prediction from 100,000 worst case to 60,000, and those are not really that close.
So therefore, your model was always wrong, and you've proved it by changing it so much, all the way down to 60,000 deaths.
Obvious, right? If you said 100,000, but now you've revised it to 60, well, clearly the 100,000 was totally wrong, right?
Because 60,000 and 100,000 are not really very close.
Common sense, right?
Wrong. And now watch me.
Blow your mind.
It's a little thing called context.
So when we saw the original estimates, there was one curve that said if you do no mitigation, maybe a million at one point.
There was some model that said two million, but I think we fairly quickly got to a million people dying at the high end in the United States.
The low number with mitigation was 100,000 originally.
Not originally, but for a while.
And then more recently, it dropped to 60,000.
Here's the context you're missing.
If you consider the gigantic range of uncertainty, is 60,000 and 100,000 really different?
It really isn't.
They're practically the same number, if you consider the wide range.
Now, I get that both of these are with mitigation.
But do you think there's anybody in the world...
Who knows how to model mitigation in the United States?
It's never been done.
How could you possibly model mitigation?
You don't know how well people are going to do it.
You don't know if it's different in different places.
You don't know if there's a cultural problem.
You don't know if people keep with it.
You don't know if they're washing their hands too.
I mean, how could you possibly model this?
I mean, seriously. If you could get this close...
With mitigation and say, look, we said it'd be 100,000, but you came out at 60,000.
Is that a mistake?
No. If you've done modeling for a living, as I have, and by the way, ask anybody else who has ever done modeling for a living.
If this were the outcome, you had predicted 100 at the low end, but we did good mitigation and it came in at 60, would you tell your boss that you missed it and you were completely wrong and, you know, I quit because it's so embarrassing, I was so far off?
No. You would go in and tell your boss you needed a raise.
Because out of all these possibilities, you said, with mitigation, we're going to be about here, and you got pretty darn close.
You got pretty close.
I'd call that a home run.
That is as good as a model can be.
Here's the kill shot on my point.
Nobody in the world can predict the future with a complicated model with lots of variables during the fog of war.
Now, you can sometimes predict how things will go If the thing that's going to happen is very, very similar to a thing that happened before, and the thing that happened before and before.
So I've used the example, let's say you're a home builder, and you build one home, and you say, oh, it costs me this much per square foot.
Then you build a second one, it's a different home, but the square footage comes out about the same cost.
And then you build the third one, Do you think you could make a good estimate of your square footage cost for the third one?
The answer is probably.
Yeah, you'd have comparable things you could look at.
So yeah, it's a lot like those other ones, so I'll use the same process.
Yeah, you could get pretty close.
But if you're in the fog of war, let's say the first week of the Iraq war.
In the first week of the Iraq war, Were there any modelers who could put in their variables and tell you how it was all going to come out?
Of course not. Of course not.
In the fog of war, you can't make any kind of a model that predicts the future.
That's not a thing.
Nobody's ever been able to do that.
There's no model that can do that.
There's no model that'll ever be able to do that.
It's not logically possible.
And if you're still wondering if there are some people who can make models and predict the future and the chaos, you think those people exist?
Here's how you could spot them if they exist.
They would be living on their trillion dollar yachts.
If anybody could build a model to accurately, or even more accurate than randomness, predict the future based on the chaos of the fog of war of any situation, whether it's this one or some other, if anybody could do that, they would be a trillionaire.
Because it isn't something that can be done.
So, if you say, Scott, Your prediction model was wrong because it was not accurate?
Then I say to you, hey you, apparently you don't know what a prediction model is because you thought it was for predicting.
It isn't. The reason it's not designed to predict is because it can't.
It's not a thing.
It's just not a thing.
You can't do what's not a thing, by analogy, because I know you like analogies.
I do this sometimes just to annoy people.
If you had a bicycle and your bicycle could not fly, it could only pedal on the ground, would you say, that bicycle is broken?
That bicycle is a piece of garbage because it can't fly.
No, you would not. You would say, well, that doesn't make sense.
You're not evaluating it as an airplane.
A bicycle is intended to pedal on a road, so let's evaluate it for pedaling on a road.
Oh, okay, it looks pretty good if you look at it that way.
So if you're looking at these models, the virus models, and you say to yourself, hey, these models are all broken and defective because they did not predict the future accurately, then you don't understand what a model is because they're not designed to predict the future.
They can't.
It's not a thing.
Nobody would try to design a model to predict the future because you know in advance it's not a thing.
It's not a thing.
So you're wondering, well, why is everybody acting like it is a thing?
I mean, literally everybody is acting like the model should have told us what the future looks like.
And they didn't.
So something's wrong, right?
No, models are not intended to predict the future.
Here's what they're for. Persuasion and rough sizing of a problem.
Did the models roughly size the problem?
And here, the size can be very approximate, because all you're trying to do is persuade people to act differently to get that number lower.
So did it size the problem as a big old problem that you should treat as a special problem?
I'd say yes.
The New York City numbers seem to indicate that the degree of panic about this was probably well warranted, because even with mitigation, They lost 7,000 people, and if you extended that to the whole country and imagined no mitigation, it could be half a million people, just based on what we do know.
So, was it appropriate to use prediction models to persuade us to act differently, and also sized it as a big old problem that we don't know if it's a million or a hundred thousand, but let me tell you, it's a big old problem if you don't do anything about it.
I would say the models not only were useful and good, but some of the best of all time.
Because missing the bottom number by that little when you did mitigation is pretty darn good.
And if it did what it was supposed to do, which is persuade us to act differently, did it do that?
Yeah. Yeah, those models persuaded me.
I'll bet it persuaded most of you, too.
And did it size the general size?
I think yes. Now, your critics will say no, that that's exactly the problem.
It did not size the problem correctly.
It missed the size of the problem by a mile.
Did it? Did it?
Because that doesn't look like a mile to me.
That looks like of all the possibilities, and of course that's mitigation, no mitigation versus mitigation.
But if you could come that close, With this level of uncertainty, I'm pretty impressed.
I'm totally impressed.
This would be a world-class...
If it turns out that 60 is a real number, I actually think it's going to be lower.
If it goes down to 30, then I'm going to join the chorus of people saying, these models may be not as helpful as they could have been.
But at 60, it's sort of a rounding error.
Somebody says, wrong.
Obviously, you're new here.
What happens when people just use the one word?
Wrong. That's what happens.
That's one way to learn.
Learning it the hard way. Somebody says there's no proof that any lives were saved.
Alright, so let's take that point.
I think that point agrees with a lot of people.
Because the point is, can you demonstrate...
That what we did actually saved lives.
Like, how would you know? Well, here's what I would look to.
I would look to every year before in New York City.
Can you list for me the number of years that they had to do mass outdoor burials because they had too many corpses?
Can somebody, a historian, Tell me, when was the last time we had so many corpses in New York City that they had to use bulldozers to make a trench to temporarily bury them in the park?
If that's never happened before, would you agree with me something different is happening in New York?
Because if you don't get that part, nothing else makes sense.
Then in New York City, because they were a little late on the mitigation, That they're burying people in mass graves.
That doesn't look like there's a big problem.
So anybody who says that the models are out of whack with what we're actually observing, that's not what I see.
To me, I see the models said there's a really big problem and we want to persuade you to act differently.
If you're burying people in mass graves...
In just the first state that was a little late on the mitigation, I feel like they were right.
That was a big, big potential problem that we may have done a heroic job at decreasing.
I've always been on the side that says that human ingenuity, once we're all focused on the same problem as we are, is hard to predict.
And it's also one reason that prediction models are useless.
Because the human ingenuity can't be predicted.
You just know it's going to be probably surprisingly good, but you don't know how.
And somebody says, still hasn't happened.
Well, it hasn't happened.
They're burying people in the park right now.
They have pictures of it.
All right. Somebody said, I saw a trench.
Not sure they're really going to bury bodies there.
I saw the bodies in the trench in containers, but did I see a fake picture of an Italian hospital or something?
But this morning I did see an aerial picture of the trench with what looked to be temporary caskets in it, you know, sort of pine boxes sort of thing.
Somebody says that is not fully correct.
That is where they have done the unclaimed body burials for years.
Well, I don't think we're talking about unclaimed bodies.
If that were the case, sure.
Scott, Scott, Scott.
Big cities have mass graves regularly.
Every morgue is full of unclaimed bodies.
Your point being that New York City is not experiencing an unusual number of deaths?
Because that's something that you and I could just check, right?
Do you think that the mayor of New York City and the governor of New York don't know, but you do, but you know it, but the governor of the state and the mayor of New York City, they don't know that the number of deaths is just the normal number?
Is that your point of view?
That the mayor hasn't noticed?
And he just thinks there's a lot of deaths, but he just is counting it wrong.
Really? Really?
Is that what you think? Somebody says it's a fake picture.
It could be a fake picture. So, let me say this.
Some people are doubting the number of deaths.
Those of you who are doubting the number of deaths, do you believe that there are 7,000 deaths?
That although they had comorbidities in many cases, they probably wouldn't have been dying this week or these weeks.
Just because they had diabetes, not many of them were going to die this week.
So let's put it on the facts.
Let's say that you and I don't have to decide right now whether New York City is experiencing an unusual number of deaths.
Let's just look it up.
Look it up. If it turns out that New York City is experiencing a normal amount of deaths for this period, well then I'd say you're probably quite right.
You're quite right.
But if it turns out that they're experiencing an unusual number of deaths, even after we're not getting any deaths from traffic accidents, and even after all the normal Sporting accidents and things that normally would fill your hospital, even after you take them out, if we still have to bury people in mass graves and refrigerated trucks in New York City, that's telling us something, right?
Right?
Okay.
So we're also looking at the differences between states.
And there are so many variables that seem to go into determining whether there's a high death rate or not, or a high infection rate.
But there are a few that I haven't seen talked about as much, and so let me mention them.
Now, of course, California has probably lower density, so that might make a difference with New York City.
We're a very international state, but probably nothing is as international as New York City, I would guess.
So, as connected to the rest of the world as California is, probably there's nothing like New York City, so that would be one difference.
And, of course, fewer elevators and people are commuting in cars by themselves and stuff.
So there's a lot of difference in California.
But somebody said, oh, but I also wanted to add this to the mix.
I think California has one of the lowest rates of obesity and cigarette smoking.
I think we're in the top 10% of thinnest people.
So if all you did is compare New York City to California, would there be a difference in average weight?
New York City is actually kind of a thin city, so I don't know if that would hold up.
But if you looked at the country in general, Californians are way thinner.
I mean, a lot thinner.
If you've ever traveled from, let's say you're taking a flight and you have a layover in Dallas and you're walking around in the airport looking at the people, and then you land in Los Angeles, LAX, and then you walk around and look at the people, they don't look the same.
In LA, you'd have to look pretty hard to find anybody who's overweight.
It's actually kind of rare at the airport.
Because at the airport is higher income people.
The lower income people have a little more weight problem.
But if you go to Dallas and you walk out in the airport, 75% of the people are overweight.
So we should look at that.
The weight of different states, that should be a factor.
And smoking rates, that should be a factor.
And somebody pointed out on Twitter that Colorado also has...
they're having some problems.
And so it might not just be weight because Colorado...
Coloradoans?
People in Colorado are also not overweight.
But they are having a high problem with infections and deaths.
And so I looked up their humidity.
And it turns out that Colorado has very low humidity.
Which is one of the variables that would cause you to have more infections.
So California has relatively higher humidity than Colorado.
So I'm wondering if we're coming to the point where we can identify, I don't know, seven different variables that are the most important ones and it would explain everything we're seeing in the different death rates.
So we've got, you know, age and comorbidities and living in the same households and, you know, density, humidity, Weight, rates of smoking, all those things.
All right. Europeans are...
So here's a question I asked yesterday.
I still don't have an answer.
Somebody suggested Sweden.
But in the same way that I'm saying that New York City might tell us a little bit about what the rest of the country could have looked like if we acted differently, there must be some country...
That would make a good reference point for us.
So I'd be looking for a country that did everything that we did except for mitigation.
So if you could find something that on all the other variables, they were sort of similar to us, but they did no mitigation whatsoever.
I mean, yeah, no mitigation.
So no masks and no social isolation.
And then you let that run for a while, because they're getting infected at different timing.
But at the end of the run, could we look at, I don't know, Sweden, for example, and say, okay, Sweden is the model for if we had not mitigated, it would look like whatever happened in Sweden.
Can somebody...
Can somebody give me an example of what country we should agree today will be in the future the one we compare ourselves to?
Can somebody do that? Somebody says zero deaths on Maui.
Well, Maui's a special case.
Half the people in Maui are just there for the two weeks.
So they go home to die, I think.
New York City Mayor says park burials is fake news, per CNN. Alright, so, which is easy to believe, by the way.
It would be easy for me to believe that the park burials is fake news.
I don't know if that's true. But it doesn't change anything I said.
Because the raw number of dead is the only one that matters.
It doesn't matter where you put them.
If there are a lot of them, there are a lot of them, no matter where they go.
So, some people are saying Sweden.
Some people are saying Norway.
I don't know.
Did Sweden do mitigation?
Did they do masks? I don't know.
Somebody says the average weight of a female in New York is 150, but in LA it's more, 156.
Interesting. That's an average.
The obesity level, though, for California is actually low.
Recent report, marijuana causes bronchitis inflammation, and that's the worst case with the virus.
Could be. Somebody says Australia.
Didn't Australia do some mitigation?
Something like that.
New York is analogous to Italy.
Well, I don't know if it is, because Italy had some seriously unhealthy people.
I don't know what the Obesity rate is for Italy.
Well, why don't we find out? Hey Siri, Google obesity rate for Italy.
Okay, I found this on the web for obesity.
Let's see how the obesity rate in Italy looks.
It's considered mild compared to its neighbors.
To Europe?
Oh, European obesity is one of the highest.
I didn't know that. So Italy is not appreciably worse than other European countries, but apparently the European countries are over a third of them are obese in childhood.
Sweden has low density.
40% working at home anyway.
Yeah. Ventilators are making it worse.
Yeah, somebody's saying in the comments that ventilators are making it worse.
I don't know that that's true, but I did see a video or an article by a doctor who put people on ventilators.
And the doctor was speculating that if we've slightly misdiagnosed the problem, and that maybe the problem happens in the blood, not the lungs, and the lungs are more the result of the blood not doing its job, which would have implications for how you treat it.
One of the implications is that if the problem is in the lungs, then a ventilator makes sense.
But if the problem was in the blood, the blood failed to be able to carry enough oxygen because of the virus, then putting the ventilator in the lungs and treating it as though it's a lung problem Would cause you to set the ventilator settings at the wrong setting because you had misdiagnosed what's going on.
And then the ventilator would cause more problems than it would help.
Or at least it would cause damage even if it was helping.
So there's at least some speculation from a doctor who does ventilators and has a theory.
But it's still speculation at this point that the ventilators might actually be making it worse.
Now, I saw...
I heard a... Statistic that needs to be checked.
So yesterday somebody said something about, maybe it was just New York City, that 40% of the ventilator patients are coming off the ventilator, which seemed high to me.
So I need a fact check on this.
Because my understanding was that once you got on a ventilator, it didn't matter what the reason was, that by the time you get on a ventilator, your odds of ever getting off it I thought it was low, like in the 10% range.
But then I heard that the New York City experience, I think it was New York City, I need a fact check on that, was something like 40% of people getting off ventilators.
Now, could it be that one of the things that the emergency healthcare people are learning is that they have to adjust the ventilator settings differently?
So it could be that on day one, people were not doing so well on ventilators because maybe they had the settings wrong.
There are a lot of different ways you can set them for how much pressure it puts.
So it could be that they figured out how to fine-tune the ventilators to get the benefits without having too much pressure and causing its own problems.
Dr. Shiva says a high dosage of vitamin C drip may not require intubation.
Is that the thing you wanted me to comment on?
Because I can't really comment on a medical claim.
So, if the claim is that a vitamin C drip can do that, I would hope somebody's looking into that right now.
But I don't have a comment about whether that's true or false.
How could I? Somebody asked me, why does India seem to have relatively low infections?
I can think of two reasons.
One, They don't know who's infected.
How hard is it to find out if somebody has coronavirus if they're in some small village in India?
I mean, what's the health care look like outside of the metro areas?
So I don't know if anybody knows what the infection rate or even the death rate is in India, because I don't know how well they can report that stuff, given the size and the level of poverty and everything else.
But there's also speculation, yeah, I see it in the comments, speculation that India, being a major producer of hydroxychloroquine, I think their number one producer or the number one source for the United States for that drug, there's thought that the citizens are either, many of them are already on it because of malaria, or could easily get it, and that maybe that's part of the reason that it doesn't look like it's as big a problem there.
Ventilators can't be used if the lungs are too filled with fluid, somebody says.
Well, I don't know. All I can say for sure is that there seems to be some reason to believe that if you don't have the ventilator at the right settings, it could do more harm than good.
So maybe we just got smarter about the settings.
That would make sense. Somebody says, vitamin C is not a cure, fools.
Well, I certainly would not be saying vitamin C is a cure, and I doubt that Dr.
Shiva is saying it's a cure.
If the claim that I saw in the comments is correct, it's a very limited claim that it could keep you off the ventilator.
I don't know if there's any studies to show that.
I have no idea. Why does Russia have a low infection rate?
Well, I wouldn't trust any numbers out of Russia, would you?
Same thing. India only has a billion people, yes.
Trump said we have ventilators but not enough qualified people.
Yeah, that is a problem.
I did hear from a ventilator expert once on Twitter, so take that with a grain of salt.
And the ventilator guy said that If you wanted to go to school to be a ventilator operator, technician, whatever they're called, it might take a few years of school.
But if you wanted to quickly train, let's say, somebody who was already a nurse, so they had some background in health.
So if you took a nurse and tried to say, okay, it's an emergency, I'm going to try to train you as quickly as possible just for this one type of machine that you use in your hospital and just for coronavirus patients.
So the one person who was an expert in it said, okay, if you limit it to that, and you start with a nurse who's got some general background, and you stick with one machine, and you tell them just how to use it for this one problem, you could probably train people up pretty quickly.
I don't know if it's happening.
Vitamin D is more important, says someone.
I think we're all in the same boat.
These are all claims which have some reason to think you'd want to know more about it, but we don't.
Saying that something is not a cure because it doesn't cure 100% is loserthink.
That is, well, true, except for the word cure does imply that it works.
This does sound like a very similar condition to high-altitude edema.
And would it be a coincidence that the high-altitude places like Colorado have problems?
There are some low-altitude places that have problems, too.
Is Mexico City making mass graves or not?
I don't know anything about that.
Somebody says their wife isn't trained for the ventilators, but has made use of them.
Yeah, I think that would be common.
Yeah, so I'm seeing many of you commenting on the thing I just mentioned.
So there is some thought that's unproven.
That the problem happens in the blood and that's why the hydroxychloroquine works because the way it works against malaria is that it works in the blood, not in the lungs.
I thought the need for ventilators is down.
That is correct. My hypothesis is that the need for ventilators is down because hydroxychloroquine, or maybe something else, is working.
That is my hypothesis.
we'll find out later yeah Mexico City has 9 million people more than New York City So you have to be careful about the timing of stuff.
Because if Mexico City is just starting to get infected, we'll see.
Because I would think Mexico City is in the worst possible situation, right?
It's dense, it's polluted.
Health care is probably not as good as it could be.
Why don't we have solid data on hydroxychloroquine treatment yet?
That's a really good question.
And I don't understand that either because, correct me if I'm wrong, the whole point of hydroxychloroquine is that you would see a big difference after five days of using it or it doesn't work.
Isn't that the claim?
The claim is that you'll see a difference in five days or it doesn't work?
How many five-day periods have passed Since we first heard, the hydroxychloroquine might be worth looking into.
Quite a few, right?
How long does it take to put together a study?
I don't know. I think the problem is trying to put together a study in which you have a good control group.
Because you have to take people who willingly don't, or at least take the chance that they get the placebo, when they have a strong suspicion that the hydroxychloroquine might work.
So how do you get so many people to take the placebo, or at least take a 50% chance of getting a placebo, if they don't have to?
Maybe it's just hard to make a study.
But, do you need a study?
Or could you just say, alright, my hospital treated 400 people, 200 of them got hydroxychloroquine, and none of them got in ventilators, but the other group Even though it's not a controlled study, there were 200 of them, and 8 of them ended up on ventilators.
Wouldn't you feel like that would tell you a lot?
Don't you feel like if you saw the results of 400 people in hospital settings, and you knew that 200 of them were treated kind of early with hydroxychloroquine and the other 200 never got it, Don't you think that would tell you?
Because if you can't tell the difference with just 200 or 400 people, it's probably not working.
And if it didn't work, It would not be validating the claims that you see anecdotally.
In other words, the claims that people are making, just first person, hey, I took this drug and I got better, the claim they all make is that it's obvious it made a difference.
It was fast, it was obvious, and the people saying it are quite convinced it wasn't going to happen on its own, because taking the drug sort of marked the It was too conveniently marked the time that their improvements started after worsening for 10 days in a row.
But that doesn't mean they're right.
Could be that the people who don't get better don't go on TV and make social media posts so we just don't hear from them.
Don't rule that out.
Somebody says they think Dr.
Drew said the only way to get hydroxychloroquine was to enroll in a study.
That's what they try to make you do.
I believe that they try to get you into a study if you ask for it or you're a candidate for it.
But you don't have to be in the study, and you can make a case that you're not a good candidate for the study.
For example, I have asthma, so I would say to my doctor, yes, thank you for offering me the study, but I have asthma.
And if there's any chance that the hydroxychloroquine works, I don't want to get into a study where I have a 50% chance of getting a placebo.
So in my case, doctor, you and I, as we sit here in this room together and calculate the odds, don't you think you should just give it to me because I've got asthma and you don't want me to get it and not have access to the drugs?
So you can talk your doctor into it, but you've got to be able to make your case.
And your case has to include, there's a reason I should not be in the study.
Now, part of the reason could be, you can't comply with the study, you know, you're too busy, you got kids, I don't know.
You probably could come up with lots of reasons you couldn't be in the study.
So, there is a way to get it.
Alright. I think that's just about.
Somebody says, look for Trump to announce some study results today.
You know, until we have the study results that are an actual controlled study with a group that didn't get it at all and are scientifically selected to be representative and all that, until we have that, we're not going to know.
But the smaller studies that don't have a proper control group, I think if the drug works, it's just going to be obvious.
And if it doesn't work, probably that would be obvious too.
Yeah, there's financial disinterest in the pharma companies because it's not patented.
But I would still think that the companies that make it are pretty darn happy this year.
They're selling a lot of it. How did they ask you to be in the study if you're on a ventilator?
I don't think they asked those people.
I would not want to be Scott's doctor.
Oh, you're so right. You're so right.
In my lifetime, I can tell you that I have overridden the advice of my doctor quite a few times.
But in conversation with them, not just by myself, went home and ignored my doctor.
But there have been quite a few times, if you look at my entire lifetime, where a doctor said, try X. And I would say, well, I hear what you're saying.
But considering Y, Z, and Q, maybe we could try something else.
And I can tell you that I've talked my doctor a number of times into saying, yeah, you know, when you put it that way, all things considered, yeah, let's give it a try your way.
In fact, I just recently did that.
I just recently, dealing with my sinuses, there were two paths, My ENT said, let's take this one.
And I said, you know, there's one other thing we haven't tried that is low risk, probably won't work, but we haven't tried it yet, and it's easier than surgery.
And my ENT said, you know, good point.
I don't think this new thing will work.
You know, 90% chance it won't.
But you're right. If there's a 10% chance that it could avoid surgery, Yeah, go ahead and try it.
If you're willing to take a few more months and try it, go ahead.
That's a good risk-reward.
Now, that's a perfect example of where working with my doctor and really just talking about the odds and also what I'm willing to do, which is the part the doctor can't know.
The doctor doesn't know what's in your head, and that matters too, right?
So yes, on quite a number of times, including recently, I have overridden my doctor's recommendation...
And then my doctor agreed with me once I made my case.
It's a very normal thing. Likewise with lawyers.
I've dealt with a lot of lawyers in my life.
Trust me, being a cartoonist means a lot of lawyers for every different element of work.
And how often have I, let's say, objected to the advice of a lawyer and said, I hear what you're saying, but have you considered this argument And then I talk my lawyer out of whatever the original recommendation was.
How often does that happen? A lot.
I don't even know how many times.
It's actually common.
It's quite common.
Because sometimes you just have some insight about how you respond to things that a lawyer can't have.
Sometimes your priorities are different.
Your risk-reward ratio is different.
Your tolerance for risk.
Your intuition about something.
Your social preference for something.
So yeah, I talk my lawyers out of stuff all the time.
Has it ever bit me in the ass?
Not once. I talk my doctors out of stuff all the time.
Has it ever bit me in the ass?
Not once. Because I always get the lawyer or the doctor to agree before I do it.
You know, I always make sure that I've tested my argument.
I don't just go rogue and say, ah, screw you, I'll make my own decisions.
But yeah, you can talk your professionals into stuff if you have a good argument.
It's common. Very common.
Alright, that's all for now.
And I will talk to you tonight.
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