This is an ugly and depressing story, but worth reading. It leaves me pretty cynical about who’s likely to get ahead in the current crisis.

Homewreckers, Aaron Glantz’s recent book about the investors who exploited the 2008 financial crisis, is essential reading as we plunge headlong into a new financial catastrophe. Glantz observes that there are two ways a government can respond to a crisis caused by reckless speculation: by stepping in or by stepping aside. During the Great Depression Roosevelt stepped in; Ronald Reagan, dealing with the savings-and-loan crisis, stepped aside. The George W. Bush and Barack Obama administrations, alas, hewed closer to Reagan’s example.

The Housing Vultures | by Francesca Mari

God knows I miss the days when New Orleans was cheap as hell and it was easy to live there and be an artist.

The song of American urbanization plays on an accordion. Americans compressed themselves into urban areas in the early 20th century. By mid-century, many white families were fanning out into the suburbs. Then, in the early 21st century, young people rushed back into downtown areas. But in the past few years, American cities have begun to exhale many residents, who have moved to smaller metros and southern suburbs. As with so many other trends, the pandemic will accelerate that exodus. Empty storefronts will beget empty apartments on the floors above them.

The American cities waiting on the other side of this crisis will not be the same. They will be “safer” in almost every respect—healthier, blander, and more boring, with fewer tourists, less exciting food, and a desiccated nightlife. The urban obsession with well-being will extend from cycling and salads to mask design and social distancing. Many thousands of young people who might have giddily flocked to the most expensive downtown areas may assess the collapse in living standards and amenities and decide it’s not worth it. Census figures will show that the urban exodus went into hyperdrive in the COVID years. There will be headlines exclaiming the decline of the American city or, more punchy, “Americans to New York: ‘Drop Dead.’”

Then something interesting will happen. The accordion will constrict again and American cities will have a renaissance of affordability.

“Right now, you see rich people literally fleeing New York for their upstate homes,” Jeremiah Moss, the author of the book Vanishing New York, told me. “What’s happening to New York is traumatic, and strange, and post-apocalyptic. But I reserve a dark optimism about all this, if cities become less expensive over the next few years.”

In the decade after the Great Recession, American cities became very popular—and very expensive. Neighborhoods that were once jewel boxes of eccentricity became yuppie depots. Wealth elbowed out weirdness, and rents soared to suffocating levels that pushed out many of the families and stores that made the cities unique.

“Cities have historically been places for outsiders, but they became ruinously expensive in the last decade when they became popular with mainstream people,” Moss said. “If cities become less expensive in the next few years, it might allow artists and weirdos and the counterculture to come back to New York and places like it. It could make cities interesting again.”

As Moss spoke, I thought of a forest fire that rages through the underbrush and leaves a legacy of ash. To look at the aftermath of the fire is to see little but death and ruin. But in time, the equilibrium of the environment is reset. Sunlight reaches the forest floor. New things grow that couldn’t have before the fire changed the landscape.

The COVID-19 pandemic will leave two legacies for the American streetscape. In the next few years, the virus will reduce to rubble many thousands of cherished local stores. Chains will surge, restaurants will feel desolate, and the density of humanity that is the life force of cities will be ruinously arrested by the disease.

But the near death of the American city will also be its rebirth. When rents fall, mom-and-pop stores will rise again—America will need them. Immigrants will return in full force when a sensible administration recognizes that America needs them, too. Cheaper empty spaces will be incubators for stores that serve up ancient pleasures, like coffee and books, and novel combinations of health tech, fitness, and apparel. Eccentric chefs will return, and Americans will remember, if they ever forgot, the sacred joys of a private plate in a place that buzzes with strangers. From the ashes, something new will grow, and something better, too, if we build it right.

The Pandemic Will Change American Retail Forever

A few updates:
1)
I imagine that y’all have all seen Trump’s plan to “let” states loosen restrictions. It’s actually a lot better than I expected from him, since it contains metrics that the states should base it on:

States that attempt to restart their economies will be responsible for setting up testing sites; tracing the contacts of individuals who test positive; and conducting “sentinel surveillance” aimed at identifying individuals infected with the coronavirus but not displaying symptoms, and then tracing their recent contacts, Birx said.

I forget where I saw them, but there are specific metrics for each of those conditions that Trump expects states to meet in order to loosen up.

2)
Important info: I’ve been mentioning caveats to the IHME (U Washington) model for a while, but it turns out it’s much worse than that; they’re not doing any epidemiological modeling at all, just superimposing the Wuhan curves onto US data. From StatNews (yesterday):

HME uses neither a SEIR nor an agent-based approach. It doesn’t even try to model the transmission of disease, or the incubation period, or other features of Covid-19, as SEIR and agent-based models at Imperial College London and others do. It doesn’t try to account for how many infected people interact with how many others, how many additional cases each earlier case causes, or other facts of disease transmission that have been the foundation of epidemiology models for decades.

Instead, IHME starts with data from cities where Covid-19 struck before it hit the U.S., first Wuhan and now 19 cities in Italy and Spain. It then produces a graph showing the number of deaths rising and falling as the epidemic exploded and then dissipated in those cities, resulting in a bell curve. Then (to oversimplify somewhat) it finds where U.S. data fits on that curve. The death curves in cities outside the U.S. are assumed to describe the U.S., too, with no attempt to judge whether countermeasures —lockdowns and other social-distancing strategies — in the U.S. are and will be as effective as elsewhere, especially Wuhan.

3)

So where can we find better models? There are a bunch out there, but I’m not sure which ones are considered the best. Does anyone else have a good sense of that? The StatNews points to a couple, calling out this machine-learning-based one as especially accurate so far, and also mentioning this one.

InsightMaker is an interesting site where you can look (in a somewhat intuitive/accessible flowchart-ish way) at models created by other people, and tweak them yourself, as deeply as you like (or even build your own from scratch). They probably won’t be as good as the most accurate ones out there, but they can be pretty damn good.

4)

At least for as long as we maintain the current level of social distancing it seems like we’re past the first-derivative peak nationally (ie the number of new cases per day is clearly going down), which is an enormous relief. I don’t necessarily think we’re at the peak of cases yet, although I think hopefully that’s coming soon as well, as the number of new daily cases descends toward zero. Does anyone disagree? I’m sure it’ll continue to get worse in some specific places, but it overall we’re headed in the right direction as far as I can tell (see for example the “new cases” and “daily growth rate” sections here).

Of course that may all change the minute we start relaxing our current social isolation, if we do that badly. But it’s very good to know that we’re able to clamp down enough to keep it under control.

This Vox article on testing is really good. The NYT has an update on testing today as well. And you can see state-by-state testing updates at covidtracking.com.

I wonder what is the percentage of testing is, that constitutes adequate surveillance?  anyone know?

I’ve seen numbers ranging from 150k/day to 22 million/day (in that Vox piece, from Paul Romer — by far the highest I’ve seen).My thought would be that it depends dramatically on the situation — if we’ve managed to get fully past this first outbreak and we’re just stamping out small local outbreaks with testing & tracing, the number could be pretty low. If it’s still everywhere and we’re trying to open things back up, we would need an enormous number.

Other stuff I’ve read in the past few days that may or may not be of interest (none of them are urgent):

• James Heathers describes why we can’t rush into treatments like hydroxychloroquine without thorough testing first, by looking at the history of bone marrow transplants as an example of how that can go badly wrong.
• UnHerd argues that things are actually going fairly well in Sweden (with much less lockdown).
• UnHerd tries to consider how long lockdown can last politically (somewhat UK-centric but applies well to the US too).
• Rolling Stone thinks that the main reason the current situation is so exhausting is that our day-to-day decisions carry way more moral weight than usual.
• SlateStarCodex investigates who did a good or bad job predicting this situation, and why.

Coronavirus patients in areas that had high levels of air pollution before the pandemic are far more likely to die from the infection than patients in cleaner parts of the country, according to a new nationwide study that offers the first clear link between long-term exposure to pollution and Covid-19 death rates.In an analysis of 3,080 counties in the United States, researchers at the Harvard University T.H. Chan School of Public Health found that higher levels of the tiny, dangerous particles in air kno

Source: New Research Links Air Pollution to Higher Coronavirus Death Rates – The New York Times

Study:

https://projects.iq.harvard.edu/covid-pm

(some of this is linked in the previous “summaries of research” post)

https://fivethirtyeight.com/features/why-its-so-freaking-hard-to-make-a-good-covid-19-model/
Testing tracking: https://covidtracking.com/data/
Economic tradeoffs: https://fivethirtyeight.com/features/what-should-the-government-spend-to-save-a-life/

https://www.nytimes.com/interactive/2020/03/26/us/coronavirus-testing-states.html

In the morning of 4/1:

– The FiveThirtyEight article Lib posted on why it’s so hard to model C-19 is really fantastic (although probably not of practical interest). They’ve been doing some good journalism in their science and health section, including weekly surveys of infectious disease experts to try to get a sense of the C-19 outlook.

– NYT data journalism is continuing to kick ass, with a good piece from 3/26 on how each state is doing on per-capita testing (covidtracking is also trying to track tests per state), along with their various updating charts like their daily tracker of C-19 deaths per state and country. I wish they had a centralized table of contents of their C-19 datavis work.

– A few updates and better organization for my bookmarks, and I’m starting to stick stuff I read that I think is good on my blog; that’ll probably be a lot more stuff than my bookmarks.

In the afternoon:

– I’ve been trying to get some sense of what the tradeoff in human wellbeing is for different C-19 strategies. Here’s a starting place, at least: if we treat a human life as worth about 10 million dollars (which is the standard figure researchers arrive at in terms of eg what we’re willing to pay for a safer car, or the premium that dangerous jobs command) we in the US should be willing to spend about 20 trillion dollars on this (if that gets us from a bad outcome of 2 million US deaths to a “good” outcome of about 100k deaths). It’s not clear what the cost of our planned response is on top of the $2 trillion we’ve officially spent (you have to take into account the uncertain effects of economic slowdown, failed businesses, lost jobs etc), but at least one analysis (which I haven’t yet read) suggests that we still come out comfortably ahead using the strategy we’re using. Hoping to try to read that paper at some point, but fivethirtyeight does a good job taking at least a basic look at it. Obviously it’s uncomfortable to think about tradeoffs between human life and money, but in practice we’re all doing it all the time even if we don’t talk about it…

– I found a source for better info on how we’re doing on tests (StatNews). tl;dr: we’re theoretically now in a position to do 100k tests per day (we’ve only done a total of 160k to date, so I’m a bit skeptical that we’re at that capacity in practice). That may be enough? “A recent report from the American Enterprise Institute co-authored by former FDA Commissioner Scott Gottlieb puts the number of tests needed at 750,000 tests per week.” But there must be a ton of assumptions built into that number, and StatNews doesn’t seem to feel too clear on whether we’ll have enough. I’d still like to find comparable info for ventilators and masks/PPE.

https://www.sciencemag.org/news/2020/03/mathematics-life-and-death-how-disease-models-shape-national-shutdowns-and-other#

Over the past two decades, as conservatives and liberals have drifted ever farther from each other, an influential body of literature has attempted to psychologize the partisan divide — to identify conservative and liberal personality types, right-wing or left-wing minds or brains, and to vindicate the claim of the noted political scientists Gilbert and Sullivan, That every boy and every gal / That’s born into the world alive. / Is either a little Liberal / Or else a little Conservative.

In its crudest form this literature just amounts to liberal self-congratulation, with survey questions and regression analyses deployed to “prove” with “science” that liberals are broad-minded freethinkers and conservatives are cramped authoritarians. But there have been more sophisticated and sympathetic efforts, too, like the influential work of New York University’s Jonathan Haidt on the “moral foundations” of politics: Haidt argues that conservatives actually have more diverse moral intuitions than liberals, encompassing categories like purity and loyalty as well as care and fairness, and that the right-wing mind therefore sometimes understands the left-wing mind better than vice versa.

Both the crude and sophisticated efforts tended to agree, though, that the supposed conservative mind is more attuned to external threat and internal contamination, more inclined to support authority and hierarchy, and fear subversion and dissent. And so the political responses to the pandemic have put these psychological theories to a very interesting test.

Source: Opinion | The Coronavirus and the Conservative Mind – The New York Times

I’m planning to start using this as a repository of interesting stuff I read re: the COVID-19 crisis, basically just so I can keep track of it (I’ve also got some curated bookmarks, but that’s only really important stuff; this is more general. I may go back and delete it all once this is all over; we’ll see.