Triage in Utah

As you know, I've been covering the worsening outbreak in Utah here on this blog since September 18th. 

If you did not see the news reported Sunday, late last week the Utah Hospital Association went to Governor Herbert and asked for approval of a triage policy.

If you still think COVID-19 is "just the flu", triage is unprecedented at Utah hospitals.

For those of you who do not know what triage is, it means that medical staff divide patients into 3 groups: those who can be helped, those who can be delayed, and (roughly for emphasis) those who should be cut loose so the first two groups can be served.

As a medical technique, triage is most closely associated with battlefield casualties on the Western Front in World War I.

However, while information is not public, it appears that it was practiced in many European hospitals last spring.

What the UHA asked the Governor for was an approved shift in policy from no triage ever, to triage if needed. Without that approval medical professionals could be criminally charged if they failed to provide adequate care to those in the third group.

I haven’t said, ‘It’s gonna happen’ — until [Thursday] night,” Bell said. “I told the governor, ‘It’s gonna happen." [Bell is the head of the UHA]

If you're curious, the ICU in Cedar City is handling only non-COVID-19 cases for the region. Anyone with COVID-19 in the region who needs ICU care is taken to DRMC in St. George. That's the hospital that had to convert a regular wing to an ICU wing last week because they were already full. 

And, yeah, if you're banking on the idea that it doesn't hit the young very hard (and who could blame you), a male between 15 and 24 in Utah died of COVID over the weekend.

BTW: The article also makes clear that the problem at this point really isn't beds or facilities, it's healthcare professionals to staff them: too many of them are out sick too. And, in case you hadn't noticed, that doesn't happen with other infectious diseases because they're either controlled with public health measures, or those professionals have some immunity from earlier exposures.

Saturday's COVID-19 Numbers

This sums it up:

Saturday is supposed to be a much lighter day, not a somewhat lighter day.

Recall that the projections I made just yesterday were based on incorporating the recent worsening of the pandemic in Utah. I forecast 1,118 new cases, and we got 1,608. 

So I was low by almost 30%. Worried.

BTW Utah

Record breaking day today for new cases in Utah (at 1,960)

Of course, Thursday was a record breaking day too (at 1,543).

As was Wednesday (at 1,498).

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But, it's the end of the week, and records on those days can be sort of normal as labs catch up on backlogs before the weekend.

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So it's probably much better to look at the number of new cases over the last 7 days (to mitigate the effects of day of the week patterns). Like so:

• Today was a record breaking day for cases over the last week (at 9,525).
• Of course,  Thursday was a record breaking day too (at 9,055).
• As was Wednesday (at 9,001).
• And Tuesday (at 8,773).
• And Monday (at 8,641).
• So gosh it's a good thing last Sunday and Saturday did not set 7 day records! But last Friday did (at 8,594).
• And the Wednesday before that.

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Now, I will be the first to tell you not to pay much attention to record numbers in trending time series. Records are part of what you should expect to see. 

But you shouldn't see a lot of them. And clustering of them is highly unusual. Further ... they should get rarer with the passage of time (just like, say, breaking home run records in baseball).

So let's set out a really simple forecast of what we should expect to see over the next week. Our 7 day growth rate has been a little on the high side of 10%, so I assumed 10% to be conservative. And I get:

• Saturday: total cases at 102,627; new cases at 1,118
• Sunday: total cases at 103,833; new cases at 1,207
• Monday: total cases at 105,118; new cases at 1,285
• Tuesday: total cases at 106,307; new cases at 1,189
• Wednesday: total cases at 107,807; new cases at 1,499
• Thursday: total cases at 109,504; new cases at 1,697
• Friday: total cases at 111,660; new cases at 2,156

Due note that I'm not doing anything sophisticated here. Anyone with a spreadsheet and minimal knowledge could do this. 

What's unusual would be acting surprised at the numbers, as Governor Herbert seemed on Friday. There's a word for that: blinkered. And I kinda' like Gary Herbert, and have been very pleasantly surprised by his whole term in office.

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In local news ... Wednesday was the first time I've seen a line at our testing center by the soon to be abandoned "old movie theater". 

OK, yeah, I couldn't resist that little bit of snark.

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Back to the data: most people are also not aware that Utah updates it's updates, but quietly. They have a lovely dashboard, which only shows the new numbers on a daily basis. But in the background, they update the old numbers as lost, forgotten, misplaced, and whatever results come in. 

And they don't show you that very readily.

But Wikipedia does. Funny thing those updates there: they always shows that Utah Dashboard has underreported its numbers. In statistics, making errors that are usually in one direction is called bias. It's a bad thing. 

So yeah, the Utah Dashboard is biased towards underreporting the severity of the numbers. 

Having said that ... not by much ... don't panic. It's just that people who really care about getting the data right make a point of getting rid of bias. I'll be waiting.

Utahns On the Wrong End

I think Utahns are so used to being on the good end of any graph of state by state behavior that they don't look too carefully anymore. We should:

In my house, 1 out of 3 of us knows someone with symptoms right now, so Utah's position above seems spot on.

But here we run into another problem with Utahns: not paying too much attention to people in the rest of the country.

So, here's the thing. If a third of the people in your circle know someone currently exhibiting symptoms, this is not normal or typical for the rest of the country. This is a sign that we are on the bad end.

The Bump Up In Utah

Most of you are aware that COVID-19 cases increased greatly in Utah after the universities started up again.

Here's what they're not telling you (because it's complex) but which a macro student ought to be able to digest. 

Prior to September 10th, the daily measure of case growth over the previous week had hung around 5% for about a month. What's happened since then is not a level shift, but rather a growth shift.†

We are now over 30 days into a sustained shift of that daily measure of week-over-week growth to 10%. 

What does that mean? From March through August, what we saw was a slowly declining growth rate. Even in July, when there were a lot of cases statewide, the growth rate was high but still dropping. It seemed like it had been hit by a transitory shock.

No more.

What we have now is a full-fledged second wave.

Except ... shut up if you ever feel the need to say that out loud. Viruses don't have second waves. People do.

And Utah's second wave is not like its first.

The first wave was characterized by the portion of the population where the infection was thriving figuring out that it didn't like the way things look and slowly learning to avoid infection. 

It's still early, but it appears that our current second wave is in a portion of the population that isn't learning those things at all. Growth rates aren't getting worse. But they don't have to. At this rate we're doubling cases every 10 weeks, and by this time next year everyone in the state will have had it. 

Time to review the lily pad analogy.

† A sustained growth rate shift is exactly what we do not see in real GDP. There, shocks to growth rates are transitory, and fade out after a few quarters. Most of what we observe in real GDP is permanent level shifts caused by those transitory growth shocks. What we're seeing with COVID-19 in Utah is an increase in slope of the level.

Local News In Case You Missed It

Dixie Regional Medical Center exceeded their ICU capacity this past weekend. So, they put into action a plan to convert a wing of the hospital into a new ICU facility.

Uh Oh

FYI: I am like the most pro-vaccine person out there.

But, I also noted in COVID-19 coverage in class, and in the departmental seminar — both last February — that they've been working on a vaccine for the original SARS since 2003 and have not been successful. This is mostly due to side effects.

Which brings us to the third stage trial of the AstraZeneca vaccine against COVID-19 ... one of the best bets out there. It's trial was stopped about a month ago.

Why is that so?

Because in an 18,000 person trial there were two cases of transverse myelitis. Not to horrible a condition, but definitely worse than the typical side effects of "dry eyes, moist eyes, trouble sleeping, trouble staying awake, even numbers of arms, and so on." The thing is the incidence of that disease is 4 per million. †

This is a good example for students of how to get at probabilities of a certain sort. 

So, if 4 people out of a million get the disease, the probability of you not getting it is 0.999996. But what if you are just one of 18,000 people in a test? To get that, you'd need to raise that number to the 18,000th power. Good luck.

But there's an easier way. Take the figure 0.999996 and square it. That's the probability of having 2 people not get the disease. Square that to get the probability of 4 people not getting the disease, and so on. If you iterate that 14 times, you'll find that the odds of transverse myelitis not showing up in 16,384 (approximating 18K) people is 93.7%.

However, that doesn't get us the chance of getting two cases. Here's another trick: we can figure out the probability of getting exactly 1 case, and subtract both results from 1 to get the probability of getting two or more (figuring anything more than 2 probably has a probability really near zero). That's pretty easy to figure out. First, divide the 93.7% by the 0.999996 to get the probability of 16,383 people not getting it, multiply that by the (1-.999996) chance of getting it, and then by the 16,384 possible people you'd need to check, and you get 6.1%.

That leaves the probability of getting 2 or more in an 18K sample at roughly 0.2%. When I did that calculation and got that result, my first thought was: they're never going to re-open this trial. That doesn't mean there aren't other vaccine candidates out there, but it is the first sign that we're not going to get a vaccine on the optimistic timetables.

Why figure that out in a macro class? Because that's also the way that you figure out the bad effects of data mining when you subject your data to multiple tests. 

BTW: You could also approximate this with a Poisson distribution by estimating lambda as the expected number of cases, 4, times the sample as a fraction of a million (.018). Doing this gets you 0.24%.

† Of course, going on the basis of Wikipedia, perhaps the problem is that an effect of the side effect is "dysfunctional ... anal sphincter activities", and if they had to list that in a commercial's disclaimer I think they'd get some people's attention very quickly.

Visualizing World GDP

 From HowMuch:

Do note that this appears to use nominal GDP (weighted by exchange rates). It will look somewhat different if PPP data is used.

Progress On Other Diseases

 Economic growth is about this:

Note that exactly none of these were taken care of before three centuries of economic growth, or by countries with governments known for either central planning or socialism.