See image here for a best-estimate of the course of infection. (Matches a number of other analyses, unfortunately doesn’t have good representation of uncertainty.)
They kept them there for long enough that this seems unlikely.
Interesting—I’d ask Robin Hanson if that fits with his variolation suggestion.
That’s not quite right. I can’t get to that book right now, but measles and mumps for MMR are also done in Chicken eggs, IIRC, as are Herpes and Poxviruses, while cell lines and other media can be used to grow other viruses—but the remainder of the facilities are still similar, and can be repurposed.
But I agree that we do need new platform technologies.
This seems related to my speculations about multi-agent alignment. In short, for embedded agents, having a tractable complexity of building models of other decision processes either requires a reflexively consistent view of their reactions to modeling my reactions to their reactions, etc. - or it requires simplification that clearly precludes ideal Bayesian agents. I made the argument much less formally, and haven’t followed the math in the post above (I hope to have time to go through more slowly at some point.)
To lay it out here, the basic argument in the paper is that even assuming complete algorithmic transparency, in any reasonably rich action space, even games as simple as poker become completely intractable to solve. Each agent needs to simulate a huge space of possibilities for the decision of all other agents in order to make a decision about what the probability is that the agent is in each potential position. For instance, what is the probability that they are holding a hand much better than mine and betting this way, versus that they are bluffing, versus that they have a roughly comparable strength hand and are attempting to find my reaction, etc. But evaluating this requires evaluating the probability that they assign to me reacting in a given way in each condition, etc. The regress may not be infinite, because the space of states is finite, as is the computation time, but even in such a simple world it grows too quickly to allow fully Bayesian agents within the computational capacity of, say, the physical universe.
(This is still showing as a comment, not an answer.)
I don’t think the question can be answered as posed, because it is underspecified. In the comparative, realist case, however, I think it is overwhelmingly obvious that the impacts are positive—i.e. far less negative than not imposing them.
First, the question of economic effects is a comparative one, i.e. what will be the economic effects compared to not having quarantine. That means we’re asking about how much quarantine changes the economy compared to some other policy—and which one matters greatly. If the alternative is required masks in public, maximum gathering sizes of 5 people in a room, and physical distancing enforced by large fines, the difference is far smaller than if the alternative is a request to return to status quo ante.
Second, the question is also potentially either a counterfactual one, or a realist one. That is, either we are asking what the counterfactual economic effects are if we could control reaction completely, and not implement a quarantine, or we are asking what the world realistically looks like in a world where we do not implement a quarantine now. The second case is one where two weeks from today, as the death toll in the US and elsewhere mounts to currently unimaginable to the public levels, people would be demanding that politicians reverse course—and you would have even more strict quarantine, for longer, that is less effective due to the delay. If politicians were able to withstand this pressure, this might not be relevant, but it should be clear that in the US and most other places, they simply will not—when death tolls are in the 10s of thousands, and increasing rapidly, instead of holding course, they would reimpose the quarantine, if not overreact in the other direction. That would mean ordering months of full quarantine instead of weeks and slowly relaxing them when prudent, and instead going further than public health officials recommend, creating potentially even more severe economic impact.
I have updated strongly towards agreeing with you given research in the past 2 weeks, but transmissions are clearly happening both ways—it’s not hypothetical.
This was lots of fun!
The population of Italy is several times higher, and the death rate per case is still significantly lower.
Yes, I’ve noted elsewhere that treatment options might make increased spread more likely, - and it’s unclear that this will be net positive in fact, because as you say, decision-makers will muddle through, and use the existence of treatment as an excuse not to limit spread enough, potentially increasing total deaths despite partially effective treatment.
But your claim that we want to ” just allow the virus to go through the population as quickly as possible ” seems wrong. Imagine (very generously,) that the available treatments reduce the percentage of critical cases by 80%. That means that health care systems can stay under capacity with a flatten strategy, but not with your suggested strategy. For “as quickly as possible” to make sense, we’d need a 95% effective treatment—which is implausible to the point of impossibility with the types of drugs currently being considered.
At scale? Not easily—eggs are cheaper, more effective, and easier to deal with.
In that report, 13.8% had at least one of those symptoms—that doesn’t imply than many or most would require ICU support to survive.
And event if we assume they would all die, which is wrong, Wuhan was an unlikeley-to-be-repeated worst case scenario—not just because of the medical overload with no warning, or the significant under-diagnosis of lightly symptomatic younger patients inflating the severe case percentage, but because they didn’t realize this was a severe disease for the elderly until at least weeks into the spread. Elderly people globally are now being kept largely isolated, and will be treated aggressively when they get sick initially, instead of treating it like influenza until they are nearly dead.
I’d put money on healthcare capacity being at an increased level throughout the pandemic, if you can figure out how to implement this as a concrete prediction. Perhaps total ICU-equivalent beds available?
That might be the main point of disagreement—I’m much more interested in effective altruism in pandemic preparedness than it making true claims that are irrelevant to decision-making.
Yes, the diagram is based on waiting another full month—April 20 - before starting any interventions to reduce this, and assuming an Rp of 2.2 or 2.4 until then. That’s not happening, because they’ve already started much of the proposed interventions, and given that, the curve will already be far lower.
And “flatten the curve” can and will be used as an interim strategy if it is ineffective—this paper assumes that they would have 6,000 people in ICUs before anyone starts asking whether they should start more.
Note that EA global is this weekend, and I think there’s a big EA facebook meetup next weekend, but more socializing is good. We want to increase physical distancing, but reduce social isolation. More meetups are better—especially if we can get more international socializing.
From what I understand, we use eggs to incubate and clean-rooms to produce the final product for all of them, and I understood that vaccine producers can switch between which ones they make, with a couple month delay for incubation and switching over.
In general, I think calling for interventions that would work but aren’t politically feasible is low value, and mostly about signalling. This is made worse by the fact that the current projection aren’t catastrophic, just very bad—but even in the worst case, it’s a waste of time.
For example, as you suggested, we could have called for groundings on February 1, and if super-strict, it could have been mostly successful—but wouldn’t have been enough. If we had banned all air travel on Feb 1, we’d still have had community transmission that had started earlier than that.
But let’s say we did it. Everyone involved would be looking for a new job by February 3rd, and the decision would have been reversed—and the people knew it. Perhaps we’d now be more upset about the reversal, but that wouldn’t have made it work, and you would of course have many people blaming the initial overreaction for why the containment failed. So I think Vox called this exactly right—you can’t implement these measures early enough, even if in the counterfactual world where people did try, and even if in that counterfactual world it would work. And as I said at the time, I didn’t think it was going to work in practice.
BUT I think that calling for eradication in the US now. We should have gone for suppression earlier, and let the CDC tell seniors not to fly, etc. But it’s unclear we could manage eradication at this point, with the spread where it is—and calling for it is a waste of our time. But don’t worry, they’ll call for more drastic measures in another 2 weeks anyways, even though it’s already too late. And then you can say you told them so. At this point, arresting everyone who has an event with more than 10 people is arrested and everyone there is fined heavily, which I think is the right strategy everywhere that can manage it—isn’t feasible in a country like the US or UK. This is for the same reason I thought banning flights on Feb 1 would be a bad idea. I don’t think the population will listen, COVID is widespread already, and authorities aren’t willing to do something so unpopular.
NOTE: I’ll likely be writing a post-mortem of my reactions and thoughts in a couple months. I was wrong to think the government was starting to handle it decently, or that they would get their act together quickly enough—I wasn’t pessimistic enough about how badly the current US administration screwed things up, or how long it would take them to let public health people actually take over managing the response—I’ve stopped hoping they will start doing that at all, despite the fact that it’s insane they haven’t.
To start, the severity estimates that Joshua assumed were worst case and are implausible. The very alarmist Fergeson et al paper has much lower numbers than Joshua’s claim that “20% will develop a severe case and need medical support to survive.”
I also think you’re wrong about the likely course of the disease, for a couple reasons.
First, as the overload gets worse, therapeutic drugs will become more widely used. I expect that at least a few of the candidates will be at least moderately effective in treating cases, and even though we’ll run out of Remdesivir quickly, production will be ramping up. Chloroquine will be made available widely as well.
Second, R_0 will drop significantly with the community distancing / flattening the curve measures. The line in your diagram is typical capacity—but if the spread is slowed enough to bring extra ventilators and emergency response capacity online, the situation is much less disasterous. Yes, it will be bad, but the worse it is, and the more news coverage there is, the more distancing will happen on its own.
Third, the seasonal component is very uncertain, but is almost certainly non-zero. If spread is slowed due to distancing, R_0 could certainly drop below one by the time the health system is getting overloaded.
For all of those reasons, I think your prescription is alarmist. Good Judgement’s Dashboard has less than a 20% chance of over 350k deaths—that’s a 0.1% population fataility rate. (Full disclosure: I’m forecasting for it, but am currently less pessimistic than the average.)
I’ll address my claims about why not to call for bans or eradication yet in another comment.