Flattening the curve doesn't accomplish that much if you lower the line

In a lot of ways, social distancing is a delaying action, an attempt to buy time (more or less literally) so that we improve our treatments and ramp up our capacity. Instead we're gutting our health care system.


Sue Dremann writing for Palo Alto Weekly:

Employees of Stanford Health Care, including doctors, nurses and technicians who are caring for COVID-19 patients, will have their pay reduced by up to 20% starting Monday, April 27, for 10 weeks, according to a tip sheet the organization sent to workers on April 21.

The medical center briefly stated it was making the cuts due to the economic impacts of COVID-19 on the organization instead of laying off employees. The "temporary workforce adjustment" program was created as part of the hospital's "cost-saving measure and initiatives," hospital administrators stated. The pay reductions will apply to all employees at Stanford Hospital, Lucile Packard Children's Hospital Stanford and, in the East Bay, Stanford-ValleyCare. Asked if the cuts included to doctors' salaries, hospital spokeswoman Lisa Kim reiterated the cuts are "across the board." 

Paul O'Donnell and Kevin Krause writing for the Dallas News:

Dallas-based Tenet Healthcare is furloughing about 3,400 of its hospital workers nationally, citing lost revenue from elective surgeries being halted by the COVID-19 pandemic.

Tenet, one of the nation’s largest investor-owned hospital operators, announced the actions in a letter to employees Wednesday. CEO Ronald Rittenmeyer described the furloughs as temporary and resulting from the virus’s “acute” impact on the company’s business.

“These are difficult but necessary decisions in navigating near-term uncertainty that will eventually come to an end,” he wrote in the letter. “We remain ready to resume vital elective care in our communities once government restrictions are lifted.”

The 12-week furloughs affect 3% of Tenet’s 113,000 employees. It follows an earlier furlough of 500 corporate employees, as well as reductions in surgical center staffing at facilities closed or operating on a limited basis. The company said pandemic-related staffing cutbacks now affect about 10% of its workforce.

Dylan Scott writing for Vox

• The Cookeville Regional Medical Center in Tennessee will be furloughing 400 of its 2,400-person staff, and a few hundred others will see a cut in their hours, Fox 17 Nashville reports.
• Boston Medical Center is furloughing 10 percent of its staff, about 700 people, according to the Boston Globe.
• Trinity Health Mid-Atlantic, which runs five hospitals in the Philadelphia area and employs 125,000 people there, will furlough an unspecific percentage of its staff, per the Philadelphia Inquirer.
• Mercy Health, the largest health system in Ohio, is temporarily laying off 700 workers.
• Two hospital systems in West Virginia are furloughing upward of 1,000 employees combined, Metro News reports.
• The largest hospital system in eastern Kentucky is laying off 500 workers, according to the Lexington Herald-Leader.

Media and editorial judgement

This is Joseph

The New York Times has been accused lately of too much false equivalence. This deleted tweet is probably a high water mark:

The phrase "in the view of some experts" refers to injecting bleach into one's lungs as being actually dangerous. Yes, injecting bleach into lungs really was mused about. Yes, there is video. Who are these experts and can they go first?

The most amazing part was this:

“I was asking a question sarcastically to reporters like you just to see what would happen,” Trump said in the Oval Office, according to a pool report.

Neither explanation is good. On one hand, the president pondered the idea of people injecting lethal poison into their lungs. On the other hand, the president is so cynical about false equivalence that he set a trap to humiliate the media about their inability to apply editorial judgement. I don't think either explanation looks good.

Now, to be fair, the New York Times did eventually hear Donald Trump's explanation and update the story:

But surely better judgment can be used here? This isn't like hydroxychloroquine where there was actually some debate inside the biomedical community and an actual researcher, Didier Raoult, providing (weak) evidence. There was still some real risks with community use of hydroxychloroquine, but I can at least understand a political news correspondent not wanting to wade into a difficult debate.

But washing one's lungs with bleach? Here even the reporters covering it were asking a science advisor if it was really serious advice or not. This seems like a nitpick but surely this was one case where the NYT could have avoided this trap?

Think of this as your weekend starter

I read quite a bit of mockery of Stephen Moore's Rosa Parks comment, but they left out the funniest part, where he delivered the comments from. (for more on Moore, click here)





Also impressed by the impressive work still being done by John Oliver.




Chipman has also been pumping out tons of thoughtful, literate video essays.




And a nice bit of accompaniment to your weekend by Thomas Newman.

At least, it's under $21 billion

 Another news story about our favorite real life Tony Stark.

2) "The company formally notified the FCC earlier this month [May 2018] that it still won’t be seeking Connect America funding for Starlink."

Continue below to get a load of SpaceX VP's arrogance back in 2018...

— Scot, EV Customer Advocate (@ghost_scot) April 23, 2020

 

4) Two years later and SpaceX is now seeking 16 billion dollars in subsidies for this project.https://t.co/knUrmSDo8f

— Scot, EV Customer Advocate (@ghost_scot) April 23, 2020

Elon Musk has a real talent for selling himself as an exemplar of independence and champion of the public sector. Musk's promises of wondrous technology always come with amazingly low price tags. There's little if any reason to bother the taxpayer. All Elon asks is for the government to stay out of his way.

You may ask yourself why journalists would continue to fall for this. Perhaps it's because it appears to be a good career move.

Tuesday, May 31, 2016

At least it's under $5 billion...

As mentioned before, I'm working on a longer piece on the journalistic failure around the “proposal” for a supersonic passenger train called the Hyperloop (sorry about the scare quotes, but they really can't be avoided). It's a story of hype overwhelming the good work of some serious journalists.

The hype around the Hyperloop grows directly out of the carefully cultivated persona of Elon Musk. Here's a representative sample from the credulous Kevin Roose writing for New York Magazine:

For years, government has been a nuisance to Elon Musk. It's slowed him down. It's required him to spend his valuable time lobbying his Twitter followers for support in the New York legislature instead of building rockets. It's required him to explain his mind-bending technical innovations to grayhairs in Congress as if he were speaking to schoolchildren. Over and over, the public sector has convinced Musk that it is hopelessly lost when it comes to matters of innovation, and that anything truly revolutionary must spring from the ambitions of the private sector.

At the risk of a bit of Gawkeresque snark, Roose apparently has a rather unusually definition of “nuisance.”

Here is the far less credulous Jerry Hirsch writing for the Los Angeles Times:

Los Angeles entrepreneur Elon Musk has built a multibillion-dollar fortune running companies that make electric cars, sell solar panels and launch rockets into space.

And he's built those companies with the help of billions in government subsidies.

Tesla Motors Inc., SolarCity Corp. and Space Exploration Technologies Corp., known as SpaceX, together have benefited from an estimated $4.9 billion in government support, according to data compiled by The Times. The figure underscores a common theme running through his emerging empire: a public-private financing model underpinning long-shot start-ups.

"He definitely goes where there is government money," said Dan Dolev, an analyst at Jefferies Equity Research. "That's a great strategy, but the government will cut you off one day."

The figure compiled by The Times comprises a variety of government incentives, including grants, tax breaks, factory construction, discounted loans and environmental credits that Tesla can sell. It also includes tax credits and rebates to buyers of solar panels and electric cars. [It does not, however, include the more than $5 billion in government contracts that keep SpaceX in business -- MP]

A looming question is whether the companies are moving toward self-sufficiency — as Dolev believes — and whether they can slash development costs before the public largesse ends.

Tesla and SolarCity continue to report net losses after a decade in business, but the stocks of both companies have soared on their potential; Musk's stake in the firms alone is worth about $10 billion. (SpaceX, a private company, does not publicly report financial performance.)

Musk and his companies' investors enjoy most of the financial upside of the government support, while taxpayers shoulder the cost.

The payoff for the public would come in the form of major pollution reductions, but only if solar panels and electric cars break through as viable mass-market products. For now, both remain niche products for mostly well-heeled customers.
...
Subsidies are handed out in all kinds of industries, with U.S. corporations collecting tens of billions of dollars each year, according to Good Jobs First, a nonprofit that tracks government subsidies. And the incentives for solar panels and electric cars are available to all companies that sell them.

Musk and his investors have also put large sums of private capital into the companies.

But public subsidies for Musk's companies stand out both for the amount, relative to the size of the companies, and for their dependence on them.

...

California legislators recently passed a law, which has not yet taken effect, calling for income limits on electric car buyers seeking the state's $2,500 subsidy. Tesla owners have an average household income of about $320,000, according to Strategic Visions, an auto industry research firm.

Competition could also eat into Tesla's public support. If major automakers build more zero-emission cars, they won't have to buy as many government-awarded environmental credits from Tesla.

In the big picture, the government supports electric cars and solar panels in the hope of promoting widespread adoption and, ultimately, slashing carbon emissions. In the early days at Tesla — when the company first produced an expensive electric sports car, which it no longer sells — Musk promised more rapid development of electric cars for the masses.

In a 2008 blog post, Musk laid out a plan: After the sports car, Tesla would produce a sedan costing "half the $89k price point of the Tesla Roadster and the third model will be even more affordable."

In fact, the second model now typically sells for $100,000, and the much-delayed third model, the Model X sport utility, is expected to sell for a similar price. Timing on a less expensive model — maybe $35,000 or $40,000, after subsidies — remains uncertain.

The politics of covid-19 start to bite

This is Joseph

This viral facebook post is excellent:

It's about making sure people can't file unemployment. It isn't about saving lives, certainly. It's not about the peak of the curve. I think lots of people are going to ignore the governor and stay home regardless. This isn't a decision being driven by epidemiology. It's the rawest and most lethal of political decisions, and it will kill people.

Kemp is looking forward to the fiscal discussion in 2021 and 2022, when all of this really starts to hit. He got elected by out-yahooing the field. His base has been trained to view government spending as a crime, and he knows that he becomes politically vulnerable to an attack if he raises taxes. He is not capable of delivering a nuanced message around necessity, because his base doesn't know how to hear it.

and

Georgians did the Kansas thing a couple of years ago and instituted a hard constitutional limit on income taxes of 6 percent. It cannot go higher without amending the state constitution. What that means is that there's no easy mechanism for the state to accommodate an extraordinary expense, like this, without somehow telling Republican reactionaries that they must raise taxes. 

I really do look forward to the day that the right-wing has ideas other than "cut taxes" and "taxes bad". It is not that anybody likes taxes. I don't like many things that are necessary: queues, licenses, car service visits, etc . . . But there is a real lack of any idea of how to respond to an emergency; imagine a war today with the fear that raising taxes might be needed to win.

That said, it is a pity there isn't a union of states that could raise revenue, float debt, and step in to mitigate the financial crisis.

Why low estimates matter

This is Joseph

People wonder why I am so concerned about the preprints that are suggesting much higher levels of infection (and thus lower fatality rates) than expected. Consider this example:

and

The low estimate of 500 was used to justify a policy response to the covid-19 epidemic. The current number as of April 20th is 45,013 reported US deaths.

But we need to be careful about predictions that can change. This study suggests a lower infection fatality rate then previous studies show:

We can use our prevalence estimates to approximate the infection fatality rate from COVID-19 in Santa Clara County. As of April 10, 2020, 50 people have died of COVID-19 in the County, with an average increase of 6% daily in the number of deaths. If our estimates of 48,000-81,000 infections represent the cumulative total on April 1, and we project deaths to April 22 (a 3 week lag from time of infection to death), we estimate about 100 deaths in the county. A hundred deaths out of 48,000-81,000 infections corresponds to an infection fatality rate of 0.12-0.2%. If antibodies take longer than 3 days to appear, if the average duration from case identification to death is less than 3 weeks, or if the epidemic wave has peaked and growth in deaths is less than 6% daily, then the infection fatality rate would be lower. These straightforward estimations of infection fatality rate fail to account for age structure and changing treatment approaches to COVID-19. Nevertheless, our prevalence estimates can be used to update existing fatality rates given the large upwards revision of under-ascertainment.

 Now, we all do "back of the envelope" calculations. This is me doing some. But we need to be careful. In a press release, the senior author pointed out that this calculation made the IFR of covid-19 about that of the flu. Like these are actual headlines. But this would be a massive issue, if true, as the decisions we are making depend on a higher IFR. But there are concerns with this research and there is a second study that appears to be only via press release.

Now, let me be clear, I would be deliriously happy if these studies were correct. I would feel much better about loosening the lock-down and "taking it on the chin", as Boris Johnson said. These super low rates of fatality would shift the conversation about the economy, as well as suggesting people will go back to movie theaters because we'll quickly all be immune.

But these numbers don't seem compatible with New York, Italy, Spain, or the careful studies in Iceland. Corrections to the Reason story note the NY problem. This doesn't mean we don't have a lot of asymptomatic infections, we do.

But it is important that we not base policy on numbers that can be rapidly revised and quite different when they are eventually put into the record. The reason I started with the article above is that it is easy to dismiss the epidemic. I would like there not to be one too! But if you are going to argue, either way, in an official capacity then there should be some serious accountability if the estimates are way off, in a way that a statistician helping might easily fix.

Tuesday Tweets -- Dr. Elon will see you now

I have to admit it took me a while to realize to what degree Elon Musk learned his lines phonetically. In my defense, it was more difficult t tell at first. Musk would say lots of smart, technically savvy things then throw in something stupid, but lots of intelligent people have sudden dips when they wander out of their areas of expertise. It wasn't until Musk started routinely started going off script that it became clear he had no real understanding of anything scientific or technical. The illusion of comprehension was only maintained while he was repeating what the genuinely sharp engineers at SpaceX and Tesla had told him to say.

When he has to rely on Google, it doesn't work quite as well.

The latest example started when Musk, under fire for keeping his Tesla plant open during the pandemic, insisted he could make all the ventilators our ICUs need. Normally these promises are quickly forgotten but people kept bringing this one up, particularly when...

The first ventilators that were produced by General Motors and Ventec Life Systems are being delivered to hospitals in the Chicago area, per General Motors. The hospitals were chosen by FEMA.

— Kaitlan Collins (@kaitlancollins) April 17, 2020

So the promise to build was quietly changed to a promise to provide.

We have extra FDA-approved ventilators. Will ship to hospitals worldwide within Tesla delivery regions. Device & shipping cost are free. Only requirement is that the vents are needed immediately for patients, not stored in a warehouse. Please me or @Tesla know.

— Elon Musk (@elonmusk) March 31, 2020

And then the definition of "ventilator" was broadened.

California hospitals say Elon Musk sent them biPAP, CPAP machines, not ventilators | TheHill https://t.co/8kBh7Z5XEj

— Russ Mitchell (@russ1mitchell) April 17, 2020




Hey, I just wanted to weigh in to say that CNN reporters (including me) have reached out to Tesla multiple times to ask about ventilators over the past several weeks, and we never got a response. This latest story reports what Gov. Newsom said.https://t.co/wsVkc3w0W4

— Jackie Wattles (@jackiewattles) April 16, 2020

Happy #ElonMuskDay everyone! To celebrate, I'm going to donate these ventilators to my local hospital pic.twitter.com/ZaVBPbbr2b

— Rebecca Watson (@rebeccawatson) April 20, 2020

  Musk responded with the full force of his expertise.

Tesla actually sent out ResMed, Philips & Medtronic units. Latter is fully intratracheal. My personal opinion is that some ICUs are jumping the gun on intubation & setting PEEP & O2 too high. High pressure, pure oxygen increases risk of lung damage. pic.twitter.com/2IUnS5DPOg

— Elon Musk (@elonmusk) April 16, 2020

Hi @elonmusk. Appreciate your interest!
What do you mean by "lung strength"? Diaphragm TF? Pocc? P0.1? Compliance?
What do you mean by "natural lung pressure"? PEEP? PEEPi? Pmus? Elastance? Chest wall or lung?
Not familiar with your terms.

COI: Anesthesiologist and Intensivist

— Vatsal Trivedi (@VatsalTrivediMD) April 17, 2020

At which point, Elon Musk abruptly left the conversation.

He deleted but I got the receipt lol pic.twitter.com/C4HzmPOSd4

— Castles 666 (@McNukes) April 18, 2020

But the conversation did not leave him.

Here's a hint for @elonmusk. If you don't want to go "much above their natural lung pressure," this is your only option. By definition, positive pressure ventilation is well above "natural lung pressure.”🤦🏻‍♂️ https://t.co/5sDMqhavkX https://t.co/UWegvnhCst

— David Gorski, MD, PhD (@gorskon) April 18, 2020

Surprising how social distancing makes for strange bedfellows. In 2020, Bill Kristol is voting Democratic and I'm retweeting a New York Post columnist. https://t.co/BYLj8rWDon

— Mark Palko (@MarkPalko1) April 18, 2020




More on CA infection rates

This is Joseph

A new study is out which also suggests that the infection rate is higher than expected:

Based on results of the first round of testing, the research team estimates that approximately 4.1% of the county's adult population has antibody to the virus. Adjusting this estimate for statistical margin of error implies about 2.8% to 5.6% of the county's adult population has antibody to the virus- which translates to approximately 221,000 to 442,000 adults in the county who have had the infection. That estimate is 28 to 55 times higher than the 7,994 confirmed cases of COVID-19 reported to the county by the time of the study in early April. The number of COVID-related deaths in the county has now surpassed 600.

Methods are not yet out, but there are several points of concern. One, such small percentages are vulnerable to a lot of errors in specificity (see Andrew Gelman and Thomas Lumley).  They don't say in the press release (I cannot even find the study yet) but another press release says:

In L.A. County, researchers on April 10-14 sampled the blood of a random population of 863 area residents at six testing sites.

So we are talking maybe 30 or positives.

Two, the New York numbers make no sense if these estimates are correct, unless the disease is either wildly misclassified (in NY or LA there must be important mis-attribution of case of death) or the infection rates in NY must be enormous. Here is Megan McArdle discussing it. 

The obvious way to solve this is to do a 1000 person sample in NYC. If it is even close to the huge infection rates needed for these numbers then it should be quickly obvious in any study of seroprevalence.

The final point, is if the IFR is massively higher in NYC that, alone, is worth studying. They have 9,101 confirmed deaths and 4,582 probable deaths as of April 20th. There are 8.3 million people in NYC. That suggests an IFR of 0.16% assuming a 100% infection rate. The Stanford study suggested an IFR of 0.12% to 0.2% based on their models.

Figuring this out is important and not helped by being led by press releases before full scientific evaluation.

It’s not about the economy versus public health – – more on the framing of the COVID-19 debate

Lots of things are over before they start. John Houston argued that once you had the script and the cast, the movie was mostly finished before filming even began. Something similar happens with journalism. Once the decision has been made what to cover and how to frame it, you have largely decided the outcome of the debate.

The conservative movement was especially good at playing this part of the game. Think back at all of the discussions about the social safety net that were set up in terms of compassion versus fiscal responsibility. The approach was a profoundly dishonest but remarkably effective. For years, it allowed Randians like Paul Ryan to rebrand themselves as the reluctant grownups in the room.

We are seeing something similar but much more dangerous with the debate over the economic cost of social distancing. Establishment conservatives (those who acknowledge that the pandemic is real) are pushing hard to frame this as a choice between the toll the disease will take if allowed to go unchecked and the suffering that would company an economic collapse. It’s worth noting that this is not the way that most economists are likely to approach this question. There appears to be a consensus in both camps that the economic cost of inaction would probably be greater than that of reasonable containment steps. Furthermore, it's not clear how much power governments have to end social distancing.



James Pethokoukis writing for the National Interest.

The economic impact of the Swedish strategy is also unclear. The government certainly thinks it’s going to be pretty bad. According to the National Institute of Economic Research, an agency that reports to the Finance Ministry, its baseline scenario has Swedish real GDP growth declining by 3.4 percent this year, worse than its 2.9 percent forecast for the United States. It also sees a 6 percent contraction in the second quarter, comparable to the annualized US forecasts by Wall Street of a 25 percent to 30 percent contraction here from April through June. From the NIER: “Concern about infection and official advice on limiting social contact are putting a major damper on household demand, and delivery problems are disrupting production in parts of the business sector. … However, there is extreme uncertainty about future developments.” It doesn’t seem the light-touch approach provides immunity from severe economic hardship.

So where does the lives versus jobs framing come from? For a bit of political context, both Trump and the Republicans desperately need Q3 of this year to be as non-terrible as possible. 
Even a dead cat bounce, if the timing were lucky, could considerably improve the prospects of the GOP.

Some covid-19 study thoughts

This is Joseph

This study needs context:

A seroprevalence study led by Stanford researchers estimates that the number of COVID-19 cases in Santa Clara County was 50 to 85 times higher than the number of confirmed cases by early April — meaning that the true case numbers could range from 48,000 to 81,000 people infected. The county has reported 1,870 confirmed cases as of Friday. 

Medicine professor and study co-lead Jay Bhattacharya said in a Friday press conference that the study results put coronavirus’ fatality rate “about on par with the flu,” but he warned that the lack of a vaccine means the two situations aren’t equivalent. 

And

Out of the 3,330 samples analyzed, 50 came back positive, indicating a crude prevalence rate of 1.5%. The researchers adjusted the initial results both by demographics — to account for the zip code, sex and race of study participants — and by test accuracy. The antibody test misses between 10 and 30% of those who have COVID-19 antibodies, according to Bendavid.  

The problem of course is what is the specificity of the test. The authors estimate it:

A combination of both data sources provides us with a combined sensitivity of 80.3% (95 CI 72.1-87.0%) and a specificity of 99.5% (95 CI 98.3-99.9%)

But 3330 samples would have 17 false positives at the center of the point estimate and 56 at the bottom of the interval (e.g. the entire sample size could be false positives based on this data making the true prevalence ZERO) (and 3 at the top of the interval). This sort of low prevalence population is dangerous for making conclusions.

It also makes no sense. Look at New York as of Sunday:

There are 12.6 cases per thousand and 0.93 deaths per thousand. That is already at a flu level of mortality (suggesting nearly 100% of New Yorkers are in infected, across the entire state). But that is required for this statement:

A hundred deaths out of 48,000-81,000 infections corresponds to an infection fatality rate of 0.12-0.2%.  

A 50 to 85 times under-count would mean 63% to 107% of New Yorker residents are infected. That is for the entire state, not just NYC. If Stanford researchers think this level of under-count is plausible then it should be immediately apparent with a quick NY based study.

So these rare infections require an extremely accurate specificity or else you get huge confidence intervals that make the rest of it difficult to interpret, as the scenarios in the paper don't seem to incorporate the uncertainty in the test specificity. If they do, I am surprised that they end up with confidence intervals so narrow. What we really learn is that the rate is small, and could support a lot of possible infection fatality rates. I don't know that the media quotes above are supported by the analysis in the paper, once variance is considered carefully.

Postscript: After writing this, I realized that I am late to the party, via statchat. The linked articles discuss specificity in a lot more detail, although neither use the number right of the paper.

Postscript 2: Never schedule a post for Monday. Andrew Gelman is awesome here. Go read that instead.

Postscript 3: I think here is where Bayesian perspectives are super helpful. For the NY death numbers to be even close, more than half of the city must have been infected. The Diamond Princess only had 17% infected. They also had an IFR of 0.5% (95% CI: 0.2-1.2%). Applied to NYC (about 9000 deaths), that suggests 1.8 million infections (which is about 20%) with a range of 750,000 (less than 10%) to 4.2 million (50%). NYC demographics are not the same as Santa Clara, but  the median age in NYC is 36.9 years and the median age in Santa Clara is 37.2; these are not wildly different numbers that would make NYC uniquely vulnerable.

Rhetorical Orthogonality

Repost

 I'm about to do one of those things that annoys the hell out of me when other people do it, namely taking a well-defined technical concept and trying to generalize it in order to make some big sweeping statements. So I start with apologies, but I think this goes to the heart of many of the problems we've been seeing with journalism and the public discourse (and also explains much of the difficulty that a lot of us run into when we tried to address those problems).

If we think of orthogonal data in the broad sense as something that brings in new information, it gives us a useful way of thinking about the discussion process. I'm thinking in a practical, not a theoretical sense here. Obviously a mathematical theorem does not technically bring any new information into a system, but in practical terms, it can certainly increase our knowledge. By the same token, a new argument may simply present generally known facts in a new light, but it can still increase our understanding. (You might argue at this point that I'm conflating knowledge and understanding. You'd probably be right, but, in this context, I think it's a distinction without a difference.)

My hypothesis here is that (putting aside literary considerations for the moment), good journalism should be judged mainly on the criteria of accuracy and orthogonality, with the second being, if anything, more important than the first. Instead, we often see indifference to accuracy and barely concealed hostility toward orthogonality. We do see a great deal of lip service toward diversity of opinion, but the majority of that "diversity" is distinctly non-orthogonal, falling on the same axes of the previous arguments, just going the opposite direction.

For example, imagine a disgruntled employee locked in an office with a gun. "He's willing to shoot."/"He's not willing to shoot" are nonorthogonal statements even though they contradict each other. By comparison, "he doesn't have any bullets" would be orthogonal. I'd put most of the discussion about liberal bias in the mainstream media squarely in the nonorthogonal category, along with every single column written by Bret Stephens for the New York Times.

Nonorthogonal debate has become the default mode for most journalists. What's more, they actually feel good about themselves for doing it. Whenever you have an expert say "is," you are absolutely required to find another who will say "is not." This practice has deservedly been mocked in cases where one of the arguments is far more convincing than the other (as with global warming), but even when there's some kind of rough symmetry between the positions, it is still a dangerously constrained and unproductive way of discussing a question.

Ahem

This is Joseph.

It is Tyler Cowen week on the blog.

But I ask you, where are the numerous cases of leading epidemiologists screaming bloody murder to the press, or on their blogs, or in any other manner, that the most commonly used model for this all-important policy analysis is deeply wrong and in some regards close to a fraud? 

So we did have blog material on this, here, here, and here.  But it is a fair critique that we should have been more aggressive in blogging about this issue. Andrew Gelman was ahead of the curve here, way back on March 29th:

I have a few thoughts on this model. First, yeah, it’s curve-fitting, no more and no less. Second, if they’re gonna fit a model like this, I’d recommend they just fit it in Stan: the methodological appendix has all sorts of fragile nonlinear-least-squares stuff that we don’t really need any more. Third, I guess there’s nothing wrong with doing this sort of analysis, as long as it’s clear what the assumptions are. What the method is really doing is using the second derivative of the time trend on the log scale to estimate where we are on the curve. Once that second derivative goes negative, so the exponential growth is slowing, the model takes this as evidence that the rate of growth on the log scale will rapidly continue to go toward zero and then go negative. Fourth, yeah, what Dorman says: you can’t take the model for the asymptotic limit seriously. For example, in that methodological appendix, they say that they use the probit (“ERF”) rather than the logit curve because the probit fits the data better. That’s fine, but there’s no reason to think that the functional form at the beginning of the spread of a disease will match the functional form (or, for that matter, the parameters of the curve) at later stages. It really is the tail wagging the dog.

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

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.

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.