Mortality rate estimation, at this stage, is very hard. The relevant problems:

• Severe cases are more likely to be detected than minor cases (but we don't know how much more likely)
• Nearly all of the quantitative data comes from China, which is underreporting both cases and deaths in an unknown ratio
• Cases which end in death resolve faster than cases which end in recovery

On top of which:

• No one knows the morbidity rate at all
• There are unconfirmed rumors that recovery may not confer lasting immunity (this is a priori unlikely but would make the situation much worse)
• The prior is a sample from a distribution which contained SARS, MERS, and an large but unknown number of variations of common cold
• The timeline for a cure could be anywhere from a month (chloroquine or remdesivir works) to never

The practical upshot of all of which is, the confidence intervals are all wide enough to drive a truck through.

Disruption of learning mechanisms by excessive variety and separation between nutrients and flavor. Endocrine disruption from adulterants and contaminants (a class including but not limited to BPA and PFOA).

I suspect that, thirty years from now with the benefit of hindsight, we will look at air travel the way we now look at tetraethyl lead. Not just because of nCoV, but also because of disease burdens we've failed to attribute to infections, in much the same way we failed to attribute crime to lead.

Over the past century, there have been two big changes in infectious disease. The first is that we've wiped out or drastically reduced most of the diseases that cause severe, attributable death and disability. The second is that we've connected the world with high-speed transport links, so that the subtle, minor diseases can spread further.

I strongly suspect that a significant portion of unattributed and subclinical illnesses are caused by infections that counterfactually would not have happened if air travel were rare or nonexistent. I think this is very likely for autoimmune conditions, which are mostly unattributed, are known to sometimes be caused by infections, and have risen greatly over time. I think this is somewhat likely for chronic fatigue and depression, including subclinical varieties that are extremely widespread. I think this is plausible for obesity, where it is approximately #3 of my hypotheses.

Or, put another way: the "hygiene hypothesis" is the opposite of true.

Comments from Facebook crossposts of this question:

Ryan C: The likeliest kind of disability would be pulmonary fibrosis or some other chronic lung condition from the trauma there.

William E: I don’t have any answers for you, but I’ve had the exact same thought myself. 😞 We will learn more in the coming months from the very first cases in Wuhan, as they recover full or partial function. I’m *personally* most worried about long term lung damage in people in our age cohort, as deaths have been so heavily concentrated in the elderly.

While this seems accurate in these cases, I'm not sure how far this model generalizes. In domains where teaching mostly means debugging, having encountered and overcome a sufficiently a wide variety of problems may be important. But there are also domains where people start out blank, rather than starting out with a broken version of the skill; in those cases, it may be that only the most skilled people know what the skill even looks like. I expect programming, for example, to fall in this category.

User acquisition costs are another frame for approximately the same heuristic. If software has ads in an expected place, and is selling data you expect them to sell, then you can model that as part of the cost. If, after accounting for all the costs, it looks like the software's creator is spending more on user acquisition than they should be getting back, it implies that there's another revenue stream you aren't seeing, and the fact that it's hidden from you implies that you probably wouldn't approve of it.

Since you're basically risking the loss of money you could have in a hypothetical future you wouldn't want to live in anyway, and you are betting said money to maximize your utility in the future you want to live in.

Actually, this is backwards; by investing in companies that are worth more in worlds you like and worth less in worlds you don't, you're increasing variance, but variance is bad (when investing at scale, you generally pay money to reduce variance and are paid money to accept variance).

Some software costs money. Some software is free. Some software is free, with an upsell that you might or might not pay for. And some software has a negative price: not only do you not pay for it, but someone third party is paid to try to get you to install it, often on a per-install basis. Common examples include:

• Unrelated software that comes bundled with software you're installing, which you have to notice and opt out of
• Software advertised in banner ads and search engine result pages
• CDs added to the packages of non-software products

This category of software is frequently harmful, but I've never seen the it called out by the economic definition. For laypeople, about 30% of computer security is recognizing the telltale signs of this category of software, and refusing to install it.

Both. Uncontroversially, I think, though there is some room to quibble about the exact ratio of causality direction.

In the case of insulin, dosage is too complicated and illegible for insurance to restrict people to the amount they're using without significant slack. This is good, because running out of insulin is much deadlier much faster than any other commonly-used medication.