Friday, April 17, 2020

What I did last weekend

You know you're an Angeleno when you hear about a pandemic and your first thought is "with this traffic I can make Mount Baldy in 45 minutes."


Never even had to leave the county.

And a birthday shoutout








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Thursday, April 16, 2020

How they put the hype in hyperloop

Given the events of the moment, this topic seems almost quaint, but one of these days we'll be returning to our old threads, and when we do, I'll want to make a note of these examples of how this particular bullshit cycle made the piles ever deeper.

The following title popped up yesterday on a Google recommendation list:

Elon Musk's Hyperloop Idea To Become Reality In North Holland Thanks To Hardt



If you are at all familiar with the this genre of puff pieces, you know that the expectations will be down downgraded quickly, but even by those standards, the jump from the title to the first paragraph was remarkably abrupt.

"Elon Musk’s hyperloop idea might have a chance of becoming a reality in North Holland."

We can only hope an actual hyperloops braking system would work that well.



The author also apparently didn't get the memo that Musk's proposal for a high speed air-bearing system was quietly dropped years ago (Elon's only original contribution to all of the current plans was the name).

The post links to a Guardian article that also does itself proud in the hype department. Keep in mind that the insanely optimistic capacity numbers of the various proposals assume you are squeezing people in a pod and running full loads 24/7.

Now look at this artist's rendering.


They aren't even trying to be credible or consistent. Just cool pictures for gullible journalists.
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Another old post we're standing by


Thursday, March 2, 2017

There will be safe seats. There are no safe seats.

In 2017, we have a perfect example of when not to use static thinking and naïve extrapolation.

Not only are things changing rapidly, but, more importantly, there are a large number of entirely plausible scenarios that would radically reshape the political landscape and would undoubtedly interact in unpredictable ways. This is not "what if the ax falls?" speculation; if anything, have gotten to the point where the probability of at least one of these cataclysmic shifts happening is greater than the probability of none. And while we can't productively speculate on exactly how things will play out, we can say that the risks fall disproportionately on the Republicans.

Somewhat paradoxically, chaos and uncertainty can make certain strategic decisions easier. Under more normal (i.e. stable) circumstances it makes sense to expend little or no resources on unwinnable fights (or, conversely,  to spend considerable time and effort deciding what's winnable). The very concept of "unwinnable," however, is based on a whole string of assumptions, many of which we cannot make under the present conditions.

The optimal strategy under the circumstances for the Democrats is to field viable candidates for, if possible, every major 2018 race. This is based on the assumption not that every seat is winnable, but that no one can, at this point, say with a high level of confidence what the winnable seats are.
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Wednesday, April 15, 2020

The strange bedfellows of hydroxychloroquine

Picking up on this previous thread.

I know we've been through all of this stuff about Leo Strauss and the conservative movement before so I'm not going to drag this out into great detail except to reiterate that if you want to have a functional  institution that makes extensive use of internal misinformation, you have to make sure things move in the right direction.

With misinformation systems as with plumbing, when the flow starts going the wrong way, the results are seldom pretty. This has been a problem for the GOP for at least a few years now. A number of people in positions of authority, (particularly in the tea party wing) have bought into notions that were probably intended simply to keep the cannon-fodder happy. This may also partly explain the internal polling fiasco at the Romney campaign.

We don't know if hydroxychloroquine will turn out to have a useful role in the treatment of Covid 19, but we can say with almost absolute certainty that it's not a magic bullet. Controlled studies are incredibly helpful for answering a lot of questions, but even with observational data it's easy to spot large, simple, immediate effects. Thousands of patients have been treated with hydroxychloroquine (right now doctors are trying lots of things) and if there has been a benefit, it has been subtle.

Nonetheless, belief in the miraculous powers of the drug is widespread. Some of this comes from the people you'd expect: flakes; conspiracy theorists; and those who prey upon them.
















































Then there's the group we've talked about before, Republican politicians drinking from the wrong pipe, seeming to actually believe the lies meant for the base. One example of many (emphasis added):

And besides, the first-term Republican told reporters at a briefing this month, “South Dakota is not New York City.”

But now South Dakota is home to one of the largest single coronavirus clusters anywhere in the United States, with more than 300 workers at a giant ­pork-processing plant falling ill. With the case numbers continuing to spike, the company was forced to announce the indefinite closure of the facility Sunday, threatening the U.S. food supply.

“A shelter-in-place order is needed now. It is needed today,” said Sioux Falls Mayor Paul TenHaken, whose city is at the center of South Dakota’s outbreak and who has had to improvise with voluntary recommendations in the absence of statewide action.

But the governor continued to resist. Instead, she used a media briefing Monday to announce trials of a drug that President Trump has repeatedly touted as a potential breakthrough in the fight against the coronavirus, despite a lack of scientific evidence.

 But there's one group that, for me, drives home just how out of control the bullshit problem is on the right, billionaires.





And no party would be complete without...



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Tuesday, April 14, 2020

More on Tyler Cowen and IHME

This is Joseph

EDIT: Andrew Gelman is also on the case with the IHME model. In case the stuff below isn't clear, critiquing this model is not only healthy but essential for good science. 

Tyler Cown writes:

And here is a further paper on the IMHE model, by statisticians from CTDS, Northwestern University and the University of Texas, excerpt from the opener:
In excess of 70% of US states had actual death rates falling outside the 95% prediction interval for that state, (see Figure 1)
The ability of the model to make accurate predictions decreases with increasing amount of data. (figure 2)
Again, I am very happy to present counter evidence to these arguments.  I readily admit this is outside my area of expertise, but I have read through the paper and it is not much more than a few pages of recording numbers and comparing them to the actual outcomes (you will note the model predicts New York fairly well, and thus the predictions are of a “train wreck” nature).
This is all fair and part of what the Epidemiology community has been discussing. But the follow-up is:
So now really is the time to be asking tough questions about epidemiology, and yes, epidemiologists.  I would very gladly publish and “signal boost” the best positive response possible. 
From "About IHME":
The Institute for Health Metrics and Evaluation (IHME) is an independent population health research center at UW Medicine, part of the University of Washington, that provides rigorous and comparable measurement of the world's most important health problems and evaluates the strategies used to address them. IHME makes this information freely available so that policymakers have the evidence they need to make informed decisions about how to allocate resources to best improve population health. 
Do you see the word Epidemiology anywhere?  I think that the reason I bristle is not that we shouldn't ask hard questions about models. It is the need to ask whether weak models in a different field should cast doubt on a field of study. I dunno -- do bad IHME models make me ask hard questions about physics too?

What about the director?
Christopher J.L. Murray, MD, DPhil, is the Chair and Professor of Health Metrics Sciences and Director of the Institute for Health Metrics and Evaluation (IHME) at the University of Washington. His career has focused on improving health for everyone worldwide by improving health evidence. A physician and health economist, his work has led to the development of a range of new methods and empirical studies to strengthen health measurement, analyze the performance of public health and medical care systems, and assess the cost-effectiveness of health technologies.
I see Health Economist but not Epidemiologist. There is a department of Epidemiology at the University of Washington and there are people in IHME affiliated with it, but it's hardly a large overlap. It's like blaming the Economics Department for economic forecasting models developed by the Business School. It's the right general disciplinary area and these people might talk, but they are not always going to agree with methodology. But there is definitely not a tight collaboration here and IHME has its own graduate programs in Health Metrics, which it is quite clear are distinct from Epidemiology. They even have their own PhD program in Health Metrics.

Now, I don't want this line of criticism to take away from the fact that the IHME model has some . . . limitations. Here is Ellie Murray (no relation, I think) quoting a statistics link on the IHME model because it was so different than what Epidemiology does. Here is Carl Bergstrom's critique of the model 9UW biology). Here are two bloggers showing discomfort with it a week ago, for many of the reasons that are coming out now.

The IHME model was a very good way of articulating exponential growth. I think Kevin Drum is doing something almost as sophisticated and his closeness to the data has him asking some good questions.  Recent papers have me asking some of the same questions and, coupled with the Iceland data (nicely noted by Korolev), is forcing this (non-epidemic modeling epidemiologist) to ask some hard questions.

That said, the first part of the post was really nice as Ivan Korolev is doing some smart discussion of SEIRD models and is the sort of contribution that matters, as the models that he is critiquing at least come from the field itself and the Iceland data set is very useful adjunct information. Maybe I need to go back and spend some time on that.

Anyway, the health field is complicated and there are a lot of overlapping issues here. I do think it is of great service to be asking hard questions about the models that guide policy. If people want some bad Epidemiology models, I am pleased to provide some examples. But in general some more precision about the field questions would be useful here.


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Tuesday Tweets (now actually on Tuesday)



From Vox:

Dr. Deborah Birx, a respected physician and experienced diplomat who seemingly serves as a voice of reason in her role as coordinator of the White House’s coronavirus task force, raised a lot of eyebrows on Thursday with her effusive praise of President Donald Trump as “attentive to the scientific literature and the details” during an interview with the Christian Broadcasting Network.

“He’s been so attentive to the scientific literature and the details and the data,” Birx said. “I think his ability to analyze and integrate data that comes out of his long history in business has really been a real benefit during these discussions about medical issues.”


Neither Rain nor sleet nor snow...

This is the essential thread.







Tyler explains everything
And the punchline...

  

You should keep an eye on OAN
More pandemic news


Essential IHME thread



 
From another of those subsidized conservative "think tanks" (and yes, this does require scare quotes).

 

Meanwhile






And in closing
 
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Monday, April 13, 2020

A reply to Tyler Cown's questions on Epidemiology

This is Joseph.

Tyler Cowen had a critique of epidemiological disease models. Based on the list of issues, I think he is critiquing the IHME model, which is a medicine unit led by a trained DPhil Economist (Chris Murray) and which is more of a Health Economics unit than an epidemiology one (happy to correct if Tyler wants to link to some Epidemiology models). But the big Epidemiology models are the ones from Imperial College and the critiques seem misplaced for those models. But this is, of course, a guess.

But he asked some questions and so here are some answers

a. As a class of scientists, how much are epidemiologists paid?  Is good or bad news better for their salaries?

Epidemiologists are typically paid above average for academics, because of their links to medical schools. Those in departments of public health are shamefully underpaid. Since people want good news from them, there is some pressure to produce good news and most of our scandals come from over-optimistic forecasts.

b. How smart are they?  What are their average GRE scores?

Very hard to answer as there is no undergraduate preparation. So the field contains a lot of MDs (no GRE scores) and people from a diverse set of backgrounds. I would say that the variance is high, more than anything else.

c. Are they hired into thick, liquid academic and institutional markets?  And how meritocratic are those markets?

They are often hired into soft money positions that are contingent on grant funding. I was in one such for about a decade. This is a selection process that breeds productivity, although a lot of it is in the area of grant writing.

d. What is their overall track record on predictions, whether before or during this crisis?

Very little of Epidemiology in in forecasting. I am an infectious disease epidemiologist and generally do not do epidemic forecast models. I look at treatment effectiveness.

e. On average, what is the political orientation of epidemiologists?  And compared to other academics?  Which social welfare function do they use when they make non-trivial recommendations?

Public health, as a field, tends to rely on efficient government. It is no more odd to see epidemiologists as left leaning then it would be to see a small business trade association president as right leaning. I think it was Megan McArdle who pointed out that the best model of government being effective is public health (vaccinations, public sanitation, etc . . .)

f. We know, from economics, that if you are a French economist, being a Frenchman predicts your political views better than does being an economist (there is an old MR post on this somewhere).  Is there a comparable phenomenon in epidemiology?

There are huge wars in Epidemiology but they are not driven by country so far as I can tell. It's more by epidemiological sub-field. Observational versus experimental. Causal inference versus traditional epidemiology. That sort of thing.

g. How well do they understand how to model uncertainty of forecasts, relative to say what a top econometrician would know?

In my experience, very. Look at the range of forecasts in the Imperial College models which are far greater then the IHME model. They do better than 10-fold differences in forecasts based on the response functions of the government and populace.

h. Are there “zombie epidemiologists” in the manner that Paul Krugman charges there are “zombie economists”?  If so, what do you have to do to earn that designation?  And are the zombies sometimes right, or right on some issues?  How meta-rational are those who allege zombie-ism?

Some fields of epidemiology have simply no high quality data (see nutritional epidemiology); fields with access to robust experiments tend to purge these ideas. Again, part of the problem is the variance in both people and subjects in "epidemiology" is huge, as are the tools available. Fields with experiments definitely kill off Zombie ideas, less so when it is all observational.

i. How many of them have studied Philip Tetlock’s work on forecasting?

I know of it, and tend to think that it is less applicable for disease models which tend to be more mechanistic. But epidemic curves are not my sub-field. That said we have had some incredible blunders in epidemiology (Farr's Law) when we get too mechanistic.
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Yes, Covid-19 will finally bring knowledge work practices into the Twenty-first Century -- a rerepost

I realize I've been dipping into the archives a bit too often as of late (the rerepost is definitely a sign things have gotten out of hand), but this is an important development that will almost certainly not get the attention it merits.


One of the most passionately advocated solutions to two of our most pressing problems (global warming and the housing shortage) has been ever increasing urban density unleashed by market forces. It is one of those positions that cuts across ideological lines and is so ensconced in the conventional wisdom that  even an unsubstantiated (and, as it turns out, false) rumor of opposition is enough to have one labeled a traitor to the environment.

But what if the central assumption -- that people need to physically travel to their place of work on a daily basis -- is wrong? What if more and more jobs can be done from anywhere? What if Arthur C. Clarke was right? (Just off by a couple of decades.)

Wednesday, March 18, 2020

Will Covid-19 finally bring knowledge work practices into the Twenty-first Century?


I don't have numbers but I'm reasonably certain this is the largest number of Americans working from home since the advent of the internet and the smart phone.

There's no good technological reason why most knowledge workers need to live within a hundred or even a thousand miles of where they work. The obstacles are cultural but they are still formidable. Despite a tight job market and a growing housing crisis centered around a handful of overcrowded and overpriced cities, employers have been slow to consider alternative models.

Now new models are being forced upon everybody. New things will be tried. Adaptations will be made. Bugs will be worked out. Attitudes will shift.

Fifty years from now, this might be what Covid-19 is remembered for.

Friday, November 10, 2017

Why do we still have cities?


Following up on "remembering the future."

Smart people, like statisticians' models, are often most interesting when they are wrong. There is no better example of this than Arthur C Clarke's 1964 predictions about the demise of the urban age, where he suggested that what we would now call telecommuting would end the need for people to congregate around centers of employment and would therefore mean the end of cities.







What about the city of the day after tomorrow? Say, the year 2000. I think it will be completely different. In fact, it may not even exist at all. Oh, I'm not thinking about the atom bomb and the next Stone Age; I'm thinking about the incredible breakthrough which has been made possible by developments in communications, particularly the transistor and above all the communications satellite. These things will make possible a world where we can be in instant contact with each other wherever we may be, where we can contact our friends anywhere on earth even if we don't know their actual physical location. It will be possible in that age, perhaps only 50 years from now, for a man to conduct his business from Tahiti or Bali just as well as he could from London. In fact, if it proved worthwhile, almost any executive skill, any administrative skill, even any physical skill could be made independent of distance. I am perfectly serious when I suggest that someday we may have rain surgeons in Edinburgh operating on patients in New Zealand. When that time comes, the whole world will have shrunk to a point and the traditional role of a city as the meeting place for man will have ceased to make any sense. In fact, men will no longer commute; they will communicate. They won't have to travel for business anymore; they'll only travel for pleasure. I only hope that, when that day comes and the city is abolished, the whole world isn't turned into one giant suburb.


Clarke was working with a 20 to 50 year timeframe, so it's fair to say that he got this one wrong. The question is why. Both as a fiction writer and a serious futurist, the man was remarkably and famously prescient about telecommunications and its impact on society. Even here, he got many of the details right while still being dead wrong on the conclusion.

What went wrong? Part of this unquestionably has to do with the nature of modern work. Clarke probably envisioned a more automated workplace in the 21st century, one where stocking shelves and cleaning floors and, yes, driving vehicles would be done entirely by machines. He likely also underestimated the intrinsic appeal of cities.

But I think a third factor may well have been bigger than either of those two. The early 60s was an anxious but optimistic time. The sense was that if we didn't destroy ourselves, we were on the verge of great things. The 60s was also the last time that there was anything approaching a balance of power between workers and employers.

This was particularly true with mental work. At least in part because of the space race, companies like Texas Instruments were eager to find smart capable people. As a result, employers were extremely flexible about qualifications (a humanities PhD could actually get you a job) and they were willing to make concessions to attract and keep talented workers.

Telecommuting (as compared to off shoring, a distinction will need to get into in a later post) offers almost all of its advantages to the worker. The only benefit to the employer is the ability to land an otherwise unavailable prospect. From the perspective of 1964, that would have seemed like a good trade, but those days are long past.

For the past 40 or so years, employers have worked under (and now completely internalized) the assumption that they could pick and choose. When most companies post jobs, they are looking for someone who either has the exact academic background required, or preferably, someone who is currently doing almost the same job for a completely satisfied employer and yet is willing to leave for roughly the same pay.

When you hear complaints about "not being able to find qualified workers," it is essential to keep in mind this modern standard for "qualified." 50 or 60 years ago it meant someone who was capable of doing the work with a bit of training. Now it means someone who can walk in the door, sit down at the desk, and immediately start working. (Not to say that new employees will actually be doing productive work from day one. They'll be sitting in their cubicles trying to look busy for the first two or three weeks while IT and HR get things set up, but that's another story.)

Arthur C Clarke was writing in an optimistic age where workers were on an almost equal footing with management. If the year 2000 had looked like the year 1964, he just might have gotten this one right.
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Friday, April 10, 2020

The challenges of bicycling commuting

This is Joseph.

I was struck by how cluttered the bike lanes are in this video of discussing business practices during bicycle commuting:


Just the first five minutes reveal a startling amount of clutter on the bike lanes, with cares parked and people randomly walking into them. I think this is Williamsburg in Brooklyn, based on the soundtrack. Now, I have recently been a bit sore at bike riders as they don't seem to have any conception of social distance.

But this is also a sign that it's hard to make protected bicycle lanes work effectively in a large city with a lot of cars. And that is unfortunate as making dense cities work for alternate transportation is a huge step in the goal of reducing climate change.

We need to do better. 
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Quarantine Viewing part whatever week this is

Continuing to fill in gaps in my musical education.









We lost the great character actor Allen Garfield this week. Lots of great movies in his filmography, but I've always had a soft spot for "The Stunt Man." An off beat little gem that, as Peter O'Toole put it, "film wasn't released. It escaped."




Garfield was also memorable in one of the most powerful films of the 70s.



Both available on Kanopy (support your local library).
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Thursday, April 9, 2020

Of course, the economist can never view the world through the innocent eyes of the epidemiologist either...

This piece by Noah Feldman really challenged a lot of my preconceptions.
The upshot of these different worldviews is that, on the whole, epidemiologists are insisting that we must take all necessary steps to control the spread of Covid-19. Meanwhile, many economists are saying that we must find a way to reopen the economy and that we must explicitly weigh the trade-off between virus-related health and broader human well-being that is in part a product of a functioning economy. (Of course, not all epidemiologists and economists fit neatly into these two boxes; I am offering a heuristic device to make sense of different approaches, not a sociological study.)

The gulf between the worldviews is big — and it’s growing.

When epidemiologists say that there is no trade-off to be had between health and the economy, because if people keep getting sick and dying it will leave the economy worse off, lots of economists just shake their heads. “There is always a trade-off,” you can hear them thinking. The consequences are measurable. People dying is unfortunate, but it’s still a cost that can be compared to the costs of shutdown.

Meanwhile, when the economists talk the trade-off talk, lots of epidemiologists (and others) find it morally reprehensible when people are dying.


This guy is a Harvard law professor, not some clueless ass setting up straw men. Obviously, I need to reconsider my assumptions. I thought epidemiologists were actually making calculations (often with the help of economists who specialize in health care) and concluding that even extreme containment measures would more than pay for themselves when compared to the consequences (economic and otherwise) of a full collapse of the health system. I had assumed that any reasonable cost/benefit analysis would favor the outcome of South Korea over Italy.

Of course, I was also under the impression that the vast majority of economists agreed with the epidemiologists on this,  with only a few Fox News shills pushing the "don't let the cure be worse than the disease" line. Apparently, I'm going to have to re-examine lots of my preconceptions.

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Wednesday, April 8, 2020

Tuesday Tweets -- One for Gelman, a hydroxychloroquine collection, and a covid miscellanea


______________________________
  








_______________________

An important thread from Carl T. Bergstrom.







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Tuesday, April 7, 2020

Chait on Trump and Lysenkoism

I've been thinking about doing a post on Lysenkoism, but Jonathan Chait beat me to it and in more detail. TThere are, however, a few points that deserve added emphasis.

None of this would be possible without the decades long effort of the conservative movement to defund and undermine trusted sources of objective information. (See this weekend's posts for details.)

The composition of hydroxychloroquine boosters (billionaires/Silicon Valley tech bros/biohackers/Fox News/the White House) will make for interesting study one of these days.

Big effects are easy to spot. Hydroxychloroquine may have a future in the treatment of covid 19, but it is highly that it will be the game changer that Trump and Fox have promised.

Chait's own New York Magazine itself has a long history of flirting with Goop and anti-vaxxers. All good clean fun till thousands start dropping dead in a pandemic.

Trofim Lysenko was a Soviet biologist who gained the favor of Joseph Stalin by promoting pseudoscientific theories that purported to apply Marxist-Leninist theory to biology. Lysenko’s insight was to dismiss the burgeoning field of genetics as a capitalist lie, and to posit a socialist alternative theory of biology that refused to accept that plants were bound by any such thing as “genes.” Orange trees would flourish in Siberia, he promised Stalin. Catering both to the regime’s state ideology and its yearning for prosperity — he promised his methods would yield orange trees in Siberia — Lysenko established his crackpot theories as official Soviet science, and purged scientists who refused to endorse them. Stalin directed Soviet farmers to follow Lysenko’s bizarre theories, contributing to mass starvation.

There are eerie echoes of Lysenkoism in President Trump’s obsession with promoting hydroxychloroquine, a medication used to treat malaria, as a cure for the coronavirus. The parallel is not exact: Hydroxychloroquine has shown some anecdotal promise as a coronavirus therapy. It might emerge as a treatment, and conceivably even the major treatment, for the coronavirus. What gives Trump’s hydroxychloroquine obsessions its creepy Lysenkoist tinge is that the fervor is altogether disconnected from science.

Trump has repeatedly touted the medication, at times with a fervency that makes him sound like a marketer hired to promote the drug. “Hydroxychloroquine. Try it. If you like,” he suggested from the podium Saturday. In perhaps the most surreal moment of his pitch, he announced that he might personally try the medication, even though he does not have the coronavirus: “I think people should — if it were me — in fact, I might do it anyway. I may take it. Okay? I may take it. And I’ll have to ask my doctors about that, but I may take it.”

Public-health officials are far more skeptical. Evidence to date can be summarized as “limited and inconclusive.” Trump’s former FDA commissioner Scott Gottlieb wrote a Wall Street Journal column urging the rapid development of coronavirus treatments, citing several promising examples, but conspicuously omitting the president’s favorite example. On Twitter, Gottlieb cautioned that hydroxychloroquine is not the wonder treatment Trump believes it to be: “If the [hydroxychloroquine] drug combo is working its effect is probably subtle enough that only rigorous and large scale trials will tease it out.” Dr. Anthony Fauci, the White House’s top scientist, has sounded cautionary notes. “The data are really just at best suggestive,” he says. “There have been cases that show there may be an effect and there are others to show there’s no effect.”

...

Trump’s lawyer, Rudy Giuliani, has repeatedly lobbied Trump to adopt hydroxychloroquine, which he has falsely described as “100 percent effective.” Giuliani told the Washington Post that he hasn’t discussed his views with Fauci, “I’m sure he thinks I am an ignoramus,” he concedes. Upon realizing that one of the country’s most prestigious scientists considers them an ignoramus, most laypeople would begin to question their own views, but Giuliani operates at a level of self-confidence that few people can fathom. Trump’s trade adviser, Peter Navarro, has enlisted in the cause. In a bizarre episode, he confronted Fauci at a Saturday White House meeting, denouncing his caution.

Whether Giuliani and Navarro are even qualified to advise the president in their stated areas of expertise — law and economics, respectively — is a matter of serious dispute. For both to emerge as self-styled medical authorities during a pandemic is beyond unnerving.
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Monday, April 6, 2020

Hospital beds

This is Joseph

This is a blog post from 2014 (so it was written long before the current era of covid-19). Note the shrinkage in hospital beds:
In 1990, according to OECD data, the OECD countries had on average 10% more beds per capita than Canada. By 2000, that had increased to 47% more beds.  By 2005, 71% more.  And by 2012, the OECD countries had 78% more hospital beds per capita than Canada.
The same thing is happening in the United States:
The fact is that between 1980 and today, 400,000 hospital beds have vanished from our system while Wall Street financed a bonanza of hospital mergers and acquisitions. Given population growth of 100 million over this period, this means that the number of hospital beds per 100,000 people in the US has fallen by more than half. In 1980 there was 595 hospital bed for every 100,000 people. Today there’s only 281 per 100,000.  
One of the tricky problems with covid-19 is the high level of hospitalization associated with it. The reduction in beds may well look like a short sighted way to decrease costs and increase profits in the scenario where there was any sort of infectious disease. In both Canada and the United States this episode should be a wake up call to do proper capacity planning for medical services.
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Saturday, April 4, 2020

How we got here repost

Thursday, May 30, 2013

The (ongoing) War on Data

I know we've been through this before, but from the New York Times (via ataxingmatter):
One bill, introduced in the House by Jeff Duncan of South Carolina, would effectively end all surveys by the bureau, except for the decennial census, and even that would be limited to counting noses — a silly interpretation of the census’s mandate. Banning the surveys would make it impossible to compile reliable data on employment, productivity, health, housing, poverty, crime and the environment, to name a few of the affected fields.

This bill would be too wacky to worry about, but its lunacy makes the other know-nothing bill look moderate. That bill, introduced in the House by Ted Poe of Texas and in the Senate by Rand Paul of Kentucky, targets the American Community Survey. Started in 2005 to replace the long-form census, the survey is the indispensable source of information on factors that define American life, including family configurations, education levels, work and living arrangements, income and insurance coverage. Credible information is the basis for a responsive government, an efficient economy and, by extension, a functional society. It also gives American policy makers and businesses a competitive edge, because it encourages decisions based on hard data as opposed to guesses or other faulty rationales that dominate in the absence of credible data.

About three million people receive the survey every year, and, as with the census, answering it is required by law. Mr. Poe and Mr. Rand want to make it voluntary, which would make the results less reliable, and potentially worthless, because fewer people would answer and those who did would not be a representative sample.

Canada recently replaced its mandatory long-form census with a voluntary survey — and now lives with the sorry results. To try to get an adequate level of response, the voluntary survey was sent to one in three Canadians instead of one in five, which increased costs. The response rate plunged anyway, from 94 percent to 68 percent. In a staggering one-fourth of Canadian communities, not enough people responded to make the data usable.
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