Catastrophes, and the Trouble With Inside Information

The document from which I excerpted the above will one day be a historic one, and I vividly remember reading it late last year. But let me backtrack a little first.

Why, in late 2019, was I reading, on an infectious disease mailing list, about undiagnosed pneumonia in China? After all, I’m not an infectious disease specialist, nor an investor in related companies. I’m no more a hypochondriac than the average person who has used Dr. Google now and then, nor am I immunocompromised and worried about the next viral infection. 

It all started in early 2003. A then-colleague sent me a link to strange happenings on a mailing list I had never heard of, the previously mentioned ProMed. 

It was, of course, the first report on what would eventually become known as SARS, severe acute respiratory syndrome. Like the current outbreak, it was a coronavirus that had spilled over from an animal reservoir to humans, with tragic implications—and like the current outbreak, reports showed up very early on ProMed, if you were looking.

To return to where I started, here is more of that December 30th, 2019, ProMed mention of what has since become known as SARS-CoV-2. It is a machine-translated version of a news story:

And there is this attached comment from a ProMed contributor:

It makes for remarkable reading. All the pieces are there, but you can see the resistance to believing it is happening again. Within days, however, reports on ProMed made it obvious that it was happening again, and that, protestations to the contrary, it was spreading human-to-human, away from so-called wet markets, and, most troublingly, there was asymptomatic transmission. Unlike the coronavirus that caused SARS, which hit people hard and only then became infectious, this was spreading much earlier and more insidiously. 

What, you might ask, did I do with this? As the reports grew into the first week in January, I shared them with investor and doctor acquaintances, most of whom were dismissive (with the exception of my good friend Dr. Howard Luks, who, like me, saw the gravity of a less-lethal SARS-like virus with asymptomatic spread and high infectiousness). 

Trying to figure out what to do with all of this, I entered a put position on the S&P 500 in mid-January, thinking that markets, as they chugged to all-time highs, were badly over-discounting what was happening. Casting around, I contemplated a position at prediction market Predictit, wagering that there would be a recession in 2020. Mindbogglingly, at least to me, you could have that contract for less than $0.20 as recently as late February.

How did all that work out? I’m unhappy you asked: I closed my S&P put position too soon, making only modest profits, and never entered that Predictit recession position, which would have been a clean four-bagger. 

There are some lovely studies of this topic, showing how even early access to newswires is harder to profit from than you might think. You need the right idea, at the right time, and at the right size. And even then the market can move against you far enough and long enough that you give up on a good idea. Case in point: The S&P 500 was still hitting all-time highs in late February, a month after I had convinced myself a wave was growing offshore and getting ready to break—and only days before it finally cratered as we tumbled into our current malaise.

Perhaps appropriately, it is difficult to make money from misfortune, even when you are confident misfortune is coming. That, if nothing else, is a ray of sunshine in this unhappy episode.


Homeostasis, flat seas, and diseases of modernity

Much of modern life is a bet on calm seas and homeostasis. Just because you weren’t previously aware you were making that bet, doesn’t mean you haven’t been making that bet your whole life, picking up pennies in front of infrequent, often invisible, but very, very large bulldozers, relying on some force pushing things back to normal afterward, even if the worst happens,

In biology. this tendency for systems to return to normal is generally called homeostasis. When human bodies—complex systems—are pushed away for where they prefer to operate, the body has a strong, innate tendency to return to where it was before, a condition that we generally call normal, whether it’s body temperature, weight, biomarkers, or anything else.

We have similar homeostasis systems in society. Things, when pushed suddenly away from where they were before, tend to return to the prior position. Whether or not we recognize it explicitly, it gives us implicit comfort to know that there is a normal, and that things tend to return there over time (which is, of course, one of the reasons things return to normal: our collective desire to make that happen, makes it happen).

You can see how deeply our homeostasis worldview is embedded by scanning a site like IsItNormal, where people ask whether something is normal and others jump in with answers and data. Reduced to atomic levels of normality questions—is it normal that my cat licks my toes? is it normal to love something that makes you sad?—you can see how our worldview gets built, one comforting piece of normality at a time. 

We want to believe the abnormal is normal. Sure, most mortality is caused by only a few rare events, but, hey, that’s normal. It comforts us to discover that seemingly freakish infrequent events happen frequently enough that we can take comfort in their infrequent frequency. It’s normal.

This is, I think, one of the reasons for the medicalization of everything. By medicalizing things—treating human conditions and problems as medical conditions, and thus prime for medical study, diagnosis, prevention, or treatment—we get to declare it normal. Further, the medicalization of the human condition offers the hope that “it” can be fixed, whatever “it” is that we’ve turned from something inherent in being human today to being something with diagnostics and treatments and specialists with billing codes.

We sometimes call a subset of these things that we’ve medicalized and declared normal “diseases of modernity”. One example is depression, which was only declared a diagnosable and treatable disease in the last hundred years. But there are other examples, where something about modernity makes people sick, and rather than treating the cause, we treat the symptoms.  Obesity, diabetes, lung disease, and heart disease are all disorders caused in large part by modernity, by polluted, obesogenic, car-bound environments. 

In that spirit, you can argue that the current Covid-19 outbreak is a new disease of modernity, one created by the conditions of modern life: Its crossover was caused by density, its spread by tight linkages and interconnections, its mortality goosed by aging societies, obesity, diabetes, heart disease, and air quality. While most of the coverage is of the innumerate, ambulance-chasing sort, you can also detect an undercurrent of nervous and desperate people questing to be reassured that this too is … normal. 

Biology & Medicine

Science & Technology

Finance, Economics, & Sociology

Improbable Things, A Big World and the Birthday Problem

It’s a big planet and so a lot of weird things that shouldn’t happen, happen all the time. As I like to remind people, on a planet with 7.5 billion people, a billion-to-one longshot potentially happens seven-ish times a day. That can take a lot of the fun out of calling things “billion-to-one longshots”, admittedly, but that’s the way it goes on a big planet.

But this insight gets ignored all the time. To put it somewhat technically, if an event has a non-zero probability of happening, and you give it enough opportunities to happen, it will, as “enough” →  ∞,  happen. The second point is crucial, of course. You have to give the non-zero probability event enough opportunities to happen for it to happen. It isn’t enough to say, “Yo, there are seven-point-five billion of you people out there—mad stuff: happen”. The probability has to be non-zero, and the opportunities legion. 

Let’s make this concrete. Say there is a billion-to-one chance that any given human breath contains a spangly, small unicorn that can recite the complete works of Jorge Luis Borges in the original Spanish.  Given that the average person breathes around 20,000 times a day, and there are 7.5-billion people on earth, our criteria are met: we have a non-zero probability event, and  150 trillion chances a day for Borges-reciting-spangly-small-unicorns to issue forth, almost certainly surprisingly, from someone. Doing the math, we might reasonably expect 150,000 Borgesicorns a day to appear on earth. That we do not suggests we may have the probabilities wrong, but that is a separate issue. 

Sometimes we get the probabilities wrong, like with the breath-born Borgesicorns. Sometimes, however, we get the opportunities for improbable events to happen wrong. Usually, narcissists that we are, we err on the side of not realizing how many chances there are every day for nutty things to happen, what with other humans being myriad & real, and not just flitting into and out of existence when we notice them. 

The birthday problem is a good example of how humans mess this up. It is usually posed this way: How many people do you need in a room before there is a 50% chance that two of them share the same birthday? Most people screw this up by, at least implicitly, only considering their own birthday, and thinking you’d need a decent number of people to have a  50% chance of matching that single birthday. 

But that’s not what’s happening here. It isn’t how many people it takes to match a single birthday; it’s how many people it takes to match any birthday.  I’ll leave the math as an exercise, and it’s not hard, but say there are 23 people in a room, then there are 253 possible pairwise birthday comparisons. Having one of those match is unlikely— 1 in 364—but having no matches out of 253 comparisons is much less likely, slightly less than 50%. Turning that around, there is a slightly better than 50% chance in a group of 23 people that two will share the same birthday.

This result usually surprises people, and that’s great. We all like to be surprised by counterintuitive mathy things, or at least I do. But the reason why I like the birthday problem is because it’s emblematic of how imagination fails us when we are forced to think about how many opportunities there are on a crowded, connected world for strange things to happen. The next time something strange happens, whether it’s interpersonal, physical, medical, or anything else, ask yourself: Is this really that unlikely, or is it just my inability to imagine, given a non-zero probability and  x →  ∞, how wildly probable improbable things are. 


Rewilding, the Long Way ‘Round

A high jeopardy of extinction comes with territory. Islands are where species go to die.
― David Quammen, The Song of the Dodo

Tell them, I know what they did, and I’m on my way. And if they ask you who I am, tell them I came the long way ’round.
— Dr. Who, Heaven Sent

Rewilding1Conservation aimed at restoring and protecting wilderness, providing connectivity between such areas, and protecting or reintroducing apex predators and keystone species. has a bad rap. It’s generally thought of as crankish and impractical—other than, perhaps, if you have, say, a failed nuclear reactor and the area has been taken over by nature

The idea of turning back the ecological clock has otherwise been difficult to pull off, which helps explain why the example most of you will know best is the same one2I have this general theory of anecdotes, which is that when everyone retails the same one to prove a rule, it’s generally because there is no general rule, just that appealing anecdote.: bringing wolves back to Yellowstone National Park in Wyoming. The trouble with this story, however, is that it isn’t the unalloyed success it’s been made out to be, despite the endless stories on the topic. Doing this sort of thing properly requires more than simply bringing back a single apex predator; it requires the disappearance of humans from wild ecologies. 

Because animal habitats are increasingly fragmented physically by humans, but also by sound. Many animals are acutely sensitive to humans, even if merely recreating, and it turns a troubling fraction of their habitats into islands. And after more than fifty years of studying island biogeography, we know without doubt that more islands, however created, means fewer viable species. 

That is why it is interesting when we see a natural experiment withdrawing humans from landscapes, especially if it doesn’t involve crashing a Soviet nuclear reactor. Current events are causing that sort of experiment right now, as roads become quieter, factories close, and people hunker down, all in the space of weeks. I saw a coyote confidently walking the street in front of our house mid-morning the other day,, and I’m hardly alone, as these tweets show. People are spotting mesopredators in places where they’ve never seen them before, and at times they’ve never seen them,

It’s too soon to say that rewilding is underway, and this is a roundabout way of getting there, but there has been a recent spike in people remarking on mesopredators in their neighborhoods. Depending on how long the current experiment in re-connecting ecological islands continues, the consequences will be worth watching.


Medicine & Health

Economics & Finance

Science & Technology

Every Generation Throws a Hero Up the Pop Charts

It’s every generation throws a hero up the pop charts
Medicine is magical and magical is art
– Paul Simon, The Boy in the Bubble (1986)

They were still so young they hadn’t learned to count the odds and to sense they might owe the universe a tragedy. 
― Norman Maclean, Young Men and Fire (1992)

If something cannot go on forever it will stop.
— Herb Stein (1986)

There is a theory that every major financial market crisis marks the end of one big thing, or the beginning of another big thing, or both, or neither. This theory, like most all-encompassing explanations of financial markets, owes much of its value to its carpet-bombing of the rhetorical landscape. 

To this way of looking at financial things, while financial market crises are awful, they at least have a handy explanation … maybe. The crash of 1907? The end of laissez-faire; the return of central banks!1Which arguably led to crashes in 2000 and 2008 The crash of ’29? The end of a decade of leveraged, consumer excess2Leverage that was all back, plus plus plus, by 2008.; the return of probity via the separation of banks and brokers!3Yeah, that separation? Gone now. The Black Monday crash? The end of attempts to insure against financial losses in automated markets; the introduction of circuit-breakers4Most of which are entirely irrelevant now, given that arbitrary withdrawal of liquidity by algos makes market movements more capricious than ever.

The list goes on and on, right up to the present, when markets are crashing once again. What big thing is ending? It’s almost too easy to say, but it seems it’s the end of integration. Free trade triumphalism had begun to fall apart a few years ago, and that trend has only accelerated since, a trend that will further accelerate, however briefly, as global supply chains become less integrated in the face of re-discovered  risks. 

What big thing is coming? Regionalism and fear of the other, one would think. Regionalism in everything, from financial markets, to supply chains, to … well, regions. Ever-tighter economic and social integration has turned out to be not such a great idea given our inability to deal with its economic and health consequences.

And more fear of the other? Well, that seems a given. I remember after 9/11 looking up and seeing commercial jets for the first time and feeling, not pleasure at a return to normalcy, but unease and a kind of epistemic collapse about airlines. They no longer represented what I thought they did.

It doesn’t take much imagination to see that people increasingly feel the same way about one another—as bipedal bags of hidden health hazards, rather than that guy from down the hall who sometimes coughs into his hand. This, of course, would have come as no surprise to, say, wealthy Venetians reversing a recent trend toward wider trade and hiding in their homes for months during the plague waves of 1629-1631. 

The trouble with all these explanations, of course, is that everything in history, especially financial history, is overdetermined: there are many causes for every outcome, and we get far more causes than we do outcomes. Our main realization should be, and I’m merely echoing sociologist Charles Perrow here, is that financial markets crises are normal—in the sense that they happen all the time with the least provocation, not that they are in a way something we should feel good about, leave aside lessening the tragedy as each generation learns the same lesson. 

Here is Perrow: “If interactive complexity and tight coupling—system characteristics—inevitably will produce an accident, I believe we are justified in calling it a normal accident, or a system accident.” What financial markets are very good at is exposing systems prone to systems accidents, especially financial systems themselves.

Whether anyone will learn that lesson, whether we will introduce more slack, less complexity and less integration into our lives is an open question, however. It will eventually stop, however, because it can’t not stop, amirite?

Some readings:


Exogenous Events, Fires, and the Height of the Tide

California fires October 2003Back in 2003 during the inevitable post mortems after the massive Cedar Fire in southern California that burned hundreds of thousands of acres, destroyed two thousand homes, and killed more than a dozen people, there was one quote that always stuck with me. The then San Diego fire chief was asked about the most terrifying moment of forward progress for him, when he most doubted where they could make a stand and stop the fire. He said it came midday on October 26th.

Recall, the Cedar Fire had started late on October 25th, had burned all night pushed by hurricane force Santa Ana winds, racing across 40 miles of scrub and chaparral, and had now penetrated the city. People were in full panic, freeways were clogged, and no-one knew what was next. 

To give you a flavor, here are some snippets from the police and fire log around that time:

2020 02 28 13 42 40

The chief said that, for him, that moment came around noon on October 26th, when Santa Ana winds had pushed the fire along the 52 corridor as far as the intersection of the 805 and 52 freeways, to a point where it could progress all the way down Rose Canyon to Mount Soledad and into La Jolla. What would have stopped it at that point, asked the interviewer, if the winds hadn’t died down and stopped pushing the fire to the west? Only the “height of the tide”, the fire chief responded.

Only the height of the tide. That line has always stuck with me. Sometimes we are very small, and things are very big, and changes outside our control become the only things that matter. 

Kedrosky: Natural experiments, bomber raids, etc.

Natural Experiments, Bomber Raids, and Economics

The spring morning of May 11, 1944, dawned mostly clear over southern England. There were a few high clouds, but it was a bright and breezy day with a high of 20 C. A good day for an Allied bombing raid, albeit one that turned out to matter decades later. 

Shortly after 10 am, 364 B‐24s and 536 fighter aircraft of the Eighth Air Force, second and third Bomb Divisions, took off for Germany from their bases. And a second raid, involving 609 B‐17s and 471 fighter aircraft of the first and third Bomb Divisions, took off just before 3 pm. And, a 2011 paper argues, the two massive waves of bombers had an unexpected effect: they changed the weather. 

To understand why, it helps to keep a few things in mind.

There was no other air traffic at the time, mostly because of the war, but also because the commercial air travel industry was in its infancy. As a result, contrails—those dense and persistent condensation trails in the sky induced by hot jet exhaust meeting ice crystals —were non-existent. There is a large and growing literature about the effect of air travel on climate, and, more specifically, on the effect of contrails on the weather. The general view in the climate research community has been that contrails have an effect, but, until recently, it’s been hard to find sufficiently well-designed studies to make that definitive.

That 2011 study helped give an answer. It showed, via a kind of natural experiment, that waves of airplane-caused cloudiness (i.e., contrails) changed the weather. Specifically, one paper argues, the absence of contrails induced an almost 1° reduction in the daily high/low temperature range, caused, it seems clear, by those waves of bombers. 

Contrails nasa langley research center 1024x8091

We saw something similar after 9/11 in the United States. With more than 36,000 canceled flights, contrails disappeared from the sky, which was usually gridded with the things as this NASA satellite picture from 2004 shows. And just like in 1944, there was a change in the daily range of temperatures: During the three-day aircraft grounding, the average daily temperature range in the US increased by 1.1° C. 

We are in the middle of a similar experiment today as a result of the coronavirus outbreak. There have already been more (mostly trans-Pacific) flights canceled than during 9/11, and outbound China shipping (another source of cloud) has contracted more than 30%. The impacts will be manifold. For example, as happened after 9/11 and after the May 11, 1944 bomber raids, we will likely see reduced cloud cover, at least over the Pacific, which will mean greater temperature ranges and more unusual weather, albeit on the US west coast.

2020 02 21 08 25 20

We will also see a sharp reduction in CO2 emissions from China, as has already been noted by energy observers. Estimates vary, but the drop could be 25% or more. Daily coal consumption from six major Chinese power firms has gone down dramatically, with no sign of recovery. 

2020 02 21 08 28 48

There will be other effects too, most of which will be unanticipated. We are in the midst of a massive natural experiment in turning back time, an unprecedented one in terms of scale and scope, and it is impossible to know the outcomes and consequences. 

Unrelated readings

Music history, path dependency, and Dresden


So, let’s do this again. Here are three things to think about—or at least that I’ve been thinking about.

The History of Music Technology

I don’t really care that much about music, which is one reason it is all the more strange I keep thinking about music. Or at least about the evolution of music. Or the evolution of its technology grammar. I blame Pink Floyd drummer Nick Mason. 

I’ll explain. Almost a year ago the BBC did a wonderful documentary series on the history of music and technology, hosted by Pink Floyd’s Mason, which I heard at the time, but that promptly disappeared from the BBC website, other than a placeholder. I’m delighted to report that the series is now available again, and I’ve no idea for how long, on (grab it quickly). 

From the rise of multitrack, to the Hammond organ, to the electric guitar, to synthesizers and ORCH_2 hits, this series hot-swapped most of what I dimly knew about the building blocks of modern music, and replaced it with a new sonic grammar, one that was both coherent and evolutionary.

The upshot: I listen to music in an entirely different way. I don’t necessarily like it any more, but I now hear the evolving machine inside the noise. And it’s remarkable.

Path Dependency and Action Bias in Immunology

Humans like to feel like they’re doing something. They have, in behavioral jargon terms, an action bias—when faced with a problem they feel better if they do something than if they don’t, even if the thing they are doing doesn’t do much. Or is even counterproductive. 

My go-to example of this sort of thing comes from professional soccer goalkeepers. As a classic 2007 paper showed, they feel compelled to dive to one side or the other, despite having no idea (for the most part) what shooters are going to do. The action bias is so strong that they jump even when it’s fairly clear they would stop more shots if they simply stood still. They just want to be seen to be doing something. 

We see a similar action in bias in healthcare, where the over-prescribing of antibiotics can be seen the same way. According to a new study in this stream of work, around 10% of people like being prescribed antibiotics, even though they know they don’t do anything for their current malady. They just like feeling like they’re doing something. The effect is even more pronounced with younger patients, where a recent study presented evidence that more than one-in-four patients were being prescribed antibiotics unnecessarily. 

This matter, of course, mostly because it reduces the effectiveness of antibiotics through selection pressures on bacteria. But it has other effects too, as an increasing number of studies show, like potentially permanently altering the human gut microbiome, often in ways that have a long-term effect on future health. 

The human adaptive immune response is evolutionary, it responds to things, in part, based on what it’s previously seen, so our current resistance to viruses and bacteria is path-dependent. For example, a recent study showed how imprinted by their birth year with influenza A exposure have different responses to future flu outbreaks than those who do not. We are, in short, what’s made us ill.

The Firebombing of Dresden

This past Thursday was the 75th anniversary of the firebombing of Dresden. The anniversary of the horrors of Dresden was re-examined this week in an excellent BBC Start the Week episode, one that, among other things, called attention the almost immediate revulsion to the episode in newspaper headlines.

Even Churchill had a change of heart about its merits, writing a secret memo about the bombing, as well as asking privately “Are we beasts?”.

Unrelated reading
Video of the Week

The UTMB ultramarathon at night.

Readings: Wildfires, Loot Boxes, Fruit flies, Lego, etc.

I got out of the car and stamped on the cigarette. “You don’t do that in the California hills,” I told her. “Not even out of season.”
—Philip Marlowe, in Raymond Chandler, “Playback” (1958)

Sometime over the next day or so more people in California are likely to have their electricity turned off than lost power during any US hurricane in 2019. Around 2m people — 800,000 customers — will lose power as utilities try to prevent their lines from sparking wildfires in the current Santa Ana event. 

And everyone knows who to blame—Pacific Gas & Electric! Climate change! Hedge funds!—and they’re mostly wrong.

First, however, some history. Wildfires in California predate human inhabitation. There is charcoal evidence in river beds of massive fires long before humans—aboriginal or otherwise—settled in the state. The state has what ecologists call a fire-adapted ecology, one that is not only prone to regular, massive fires, but even has many species of plants adapted for that event.

The typical timing of these fires is high winds and low humidity during what are called Santa Ana events1Many literary types know about the relationship between California fires and Santa Anas because of writer Joan Didion, whose essay mentioning them is an annual citation ritual. On point of un-clichéd pride, I will not mention Joan Didion again., usually in the fall, and the historical trigger was lightning. Millions of acres burned decadally that way in what eventually became California, mostly during Santa Anas. 

That, of course, changed once humans came to the state. While Santa Anas continued, fires no longer needed solely lightning triggers. The first native populations were active fire-setters, burning tens of thousands of acres every year to ready them for planting, transforming the California landscape through the power of fire. The earliest Spanish explorers noticed this, with some reporting as they sailed up the coast how this was the land of smoke, with a pall often covering the land. 

But newer triggers yet arrived when the state became settled by non-natives. Humans are profligate sources of ignition, from campfires, to gas-powered equipment, to pyromania, to, yes, power lines falling into dry landscapes. We have taken a state prone to massive fires and brought it what it didn’t need: Many news ways to be set on fire. At the same time, we have spread our ignition sources throughout the state. Where lightning was once limited to the mountains, and natives (largely) to the state’s coastal plains, humans are now everywhere in California, so wildfires can now start everywhere. 

You can see this pattern in the following figure, where California fire frequency soared with the state’s population. Note that this slowed in recent decades as settlement slowed, replaced by fewer, larger fires.

But let’s get back to causes. To give you some more historical context, here is a table of the largest California wildfires over the last hundred years—and their causes.

To summarize the causes:

    • Humans (accidentally or on purpose): 9
    • Lightning: 7
    • Powerlines:4

The takeaways are two-fold. First, most California fires aren’t caused by powerlines. Second, most fires are caused by humans—5 or 6 of the ten largest, depending on how you want to allocate things. Take away humans and you take away most of the ignition sources. You also take away most of the consequences too, as the following figure shows, where the number of California properties exposed to wildfire risk is larger than the rest of the country combined.

But California is inhabited, and that has consequences, like properties and powerlines. So, we need to answer a few questions here about why powerlines cause fires, whether that’s increasing, whether it’s negligence, and whether there is anything that can be done about it. 

Powerlines cause fires when they fall into dry landscapes, spark, and cause stuff to start burning. It’s that simple. Of course, they don’t fall into landscapes and start fires every day. It requires a bunch of pre-conditions, like low humidity, dry fuels, and (usually) winds. Without these elements, California fires either don’t start or stay small. 

Can this powerline-falls-into-dry-stuff problem be prevented? Is it somehow negligence? There isn’t anything that can be done about dry fuels, low humidity, or winds, so the question becomes, Can utilities prevent power lines from falling into landscapes during wind events?

Sure, bury them. Buried powerlines can’t fall into dry stuff and cause it to catch fire. But that is not a realistic solution. Pacific Gas & Electric alone has 134,000 miles of overhead power lines in the state, and burying them would cost something like $100-billion, according to one estimate. Burying even a fraction of the lines would still cost billions, leaving aside the environmental damage, or the unintended consequences of having power crews working in fire-prone landscapes to bury the lines, thus almost certainly starting fires in the pursuit of preventing fires.2Some have argued that paying homeowners to trim back brush would be a cheaper and better solution. While maintaining a “safe space” around homes in California is a good idea, and this could save some homes, it does not address the underlying trigger issue of what causes wildfires in the first place. Further, it ignores the “loot box” problem that I refer to and expand on below. 

Of course, that won’t stop many from making the “negligence” argument. Having made out nicely by turning PG&E into the bad guy for recent fires in the state—with their lines having causes fires and billions in property losses—some hedge funds have turned PG&E into a gaming-style loot box, something that with a modest investment of legal fees they can freely pillage for its cash contents. To, in effect, close the loot box, PG&E has now been forced to turn off a huge slice of California’s power when stronger Santa Anas blow. 3There is another solution, of course, but I’ve been reluctant to mention it. The California state legislature could inoculate utilities against negligence lawsuits brought by property owners if a fire starts after power is left on during a wildfire. I have issues with this solution, not least the unanticipated consequences of further privileging a regulated industry, but it would begin to address the loot box problem if the state simply said that utilities cannot be sued for leaving the power on during wildfire conditions. Residents cannot have this both ways.

So, are we simply screwed? The state is going to have fires, and this may be getting worse as a result of climate change, and utilities are going to cause some of these fires, and people always want someone else to blame. This isn’t a great combination.

We may not be screwed, but, as should now be obvious, blaming utilities is pointless. No-one wants to ask the right questions, like, why, in a tightly-coupled system,  wildfire-prone landscapes are inhabited, and why those properties don’t see insurance prices reflecting the real systemic risks created by their existence.

Houses in the California wildland-urban interface can be thought of as barbecue starters in a butane landscape—cheap sources of ignition with systemic consequences for the rest of the state as fires started there blow west during Santa Anas into more heavily populated areas.  Risk simply isn’t priced properly in California. Population growth in previously rural counties comes with consequences for the rest of the state, as historical data shows, and this ignition growth re-accelerated during the go-go, we”ll-fund-homes-built-anywhere years before the financial crisis. Entire landscapes were transformed by tract homes, most directly in the path of previous wildfires. All these thousands of homes, new and old, have powerlines, people, and lawn trimming appliances—ignition sources—virtually none of which are paying insurances prices commensurate with either their own risk, or with the systemic risk they create for others in the state. 

But meanwhile, rather than talking about the real issue, let’s go right on blaming utilities, or blaming climate change, or blaming anything but a grounded sense of what it means to live in a fire-prone landscape. That’s much more fun than talking about how mispriced risk, the housing bubble, and loot boxes embedded in a tightly-coupled system of urbanism and wildfires is a really, really bad idea, one that will only get more costly over time. 


Finally, here are some articles and papers worth reading:

Science & Technology

Life Sciences

Finance & Economics

Readings: Red Meat Therapy, Brexit, Parking, etc.

One way to think about the recent meta-analysis paper on the health consequences of eating red meat is to think of red meat as a medicine. Let’s call it Red Meat Therapy, RMT for short, and we can imagine administering RMT to patients.

This will seem weird. First, red meat isn’t usually thought of as a medicine, any more than, say, panang curry is thought of as a medicine, but let’s put that aside for a moment. Second, and in case you didn’t read the paper, it showed (based on meta-analysis of a host of other papers) that eating red meat is likely bad for you. We don’t usually administer non-medicines that are likely bad for you to people and call them medicines, or least we don’t usually do that and not call it quackery. 

But bear with me. Because the paper argued that we have such weak evidence against eating red meat is that it’s hard to make a strong recommendation against eating red meat. That’s not the same thing as saying red meat is not not bad for you, let alone that red meat is good for you. We just aren’t sure how bad it is, but it seems at least a little bad. Admittedly, it’s not clear what to do with that information. Lots of things are a little bad — sometimes it seems like most things in life1Like life itself, really. are at least a little bad. 

What are we to do with things are a little bad? One thing we can do is ignore it. We do that a lot. We can also put it in practical and quantitative terms, which seems like a non-awful idea.

We have ways of doing that kind of calculation. One way is to use a measure called “number needed to treat” (NNT). It tells you how many patients need to be treated with a particular medication before we expect to see an effect, like, say, a saved life.2It’s a fun calculation. NNH is the inverse of the absolute risk reduction (ARR), which is, in turn, the difference between the rate of an experimental treatment (EER) and that of a control treatment (CER), or ARR = CER – EER. To be specific, if a drug reduces the risk of a bad thing happening from 50% to 40%, the ARR is calculated as 0.5 – 0.4 = 0.1, which gives us an NNT of 1/ARR = 10. You would, in other words, need to treat ten people to expect one to benefit. In the best case the NNT is 1, where everyone who is treated benefits. That mostly doesn’t happen, other than in fake medicines for, like, hair loss.

But you can turn NNT around and calculate the number needed to harm (NNH). That, as the name suggests, is how many people need to have a particular treatment before it’s likely we hurt someone. Granted, that isn’t the way we usually think about therapies, for obvious reasons, but it can cover some interventions. 

You can apply that method to our RMT. Pretending red meat is medicine, and taking the base incidence3Around 4.6% of one of the main projected bad consequences of red meat’s excessive consumption (colorectal cancer), and then comparing that to the study-based projected increase in colorectal cancer4This is obviously controversial — hence the meta-analysis we are writing about here — but a mid-point is a roughly 20% increase, putting the incidence at 5.4% or so., we can say, at least approximately, how many people would have to take Red Meat Therapy before we expected an additional case of colorectal cancer. 

So, how effective is RMT? Not so good, at least under these assumptions. If we were trying to give one more person colorectal cancer by stuffing them regularly with red meat, we would need to treat around 100 people with RMT. If this were a drug, we would likely call it a failure — it doesn’t do much for most of the people who take it. 

To return to the original study, this does help us think more coherently about the paper. It isn’t that red meat isn’t bad for you, as some of the resulting media articles implied5Red meat is back on the menu!. It’s just that the effect size is so small, and the confounds so large, that we can’t say much about red meat’s actual effect on most people, most of the time, in most real-world situations, especially given all the stuff we do to ourselves that aren’t good for us.6There is a separate issue here, which is how seriously to take meta-analysis papers of other papers that themslves have weak conclusions based on their data. I sometimes argue that such meta-analysis papers are the research equivalent of collateralized debt obligations (CDOs): bundles of individually squirrelly things that magically become credible when wrapped together in a neat quantitative package. This, of course, should feel unsettling, and no more defensible in meta-analysis papers than in mortgage securities, but that’s a topic for another day. Humans are complex, mischievous systems, and we shouldn’t be surprised when our bodies conspire to make even the best intentioned nutrition researchers look silly.


Here are some papers worth reading:

Life Sciences

Science & Technology

Economics & Finance