Following Sean here I’ll also describe my motivation for taking the bet.
After Sean suggested the bet, I felt as if I had to take him up on it for group epistemic benefit; my hand was forced. Firstly, I wanted to get people to take the nCOV seriously and to think thoroughly about it (for the present case and for modelling possible future pandemics) - from an inside view model perspective the numbers I was getting are quite worrisome. I felt that if I didn’t take him up on the bet people wouldn’t take the issue as seriously, nor take explicitly modeling things themselves as seriously either. I was trying to socially counter what sometimes feels like a learned helplessness people have with respect to analyzing things or solving problems. Also, the EA community is especially clear thinking and I think a place like the EA forum is a good medium for problem solving around things like nCOV.
Secondly, I generally think that holding people in some sense accountable for their belief statements is a good thing (up to some caveats); it improves the collective epistemic process. In general I prefer exchanging detailed models in discussion rather than vague intuitions mediated by a bet but exchanging intuitions is useful. I also generally would rather make bets about things that are less grim and wouldn’t have suggested this bet myself, but I do think that it is important that we do make predictions about things that matter and some of those things are rather grim. In grim bets though we should definitely pay attention to how something might appear to parts of the community and make more clear what the intent and motivation behind the bet is.
Third, I wished to bring more attention and support to the issue in the hope that it causes people to take sensible personal precautions and that perhaps some of them can influence how things progress. I do not entirely know who reads this and some of them may have influence, expertise, or cleverness they can contribute.
Nice find! Hopefully it updates soon as we learn more. What is your interpretation of it in terms of mortality rate in each age bracket?
Sure, I’ll take the modification to option (i). Thanks Sean.
The bet is on.
Hmm… I will take you up on a bet at those odds and with those resolution criteria. Let’s make it 50 GBP of mine vs 250 GBP of yours. Agreed?
I hope you win the bet!
(note: I generally think it is good for the group epistemic process for people to take bets on their beliefs but am not entirely certain about that.)
Good points! I agree but I’m not sure how significant those effects will be though… Have an idea of how we’d in a principled precise way update based on those effects?
Updating the Fermi calculation somewhat:
P(it goes world scale pandemic) = 1⁄3, no updates (the metaculus estimate reference in another comment counteracted my better first principles estimation)
P(a particular person gets it | it goes world scale pandemic) = 1⁄2, updating based on the reproduction number of the virus
P(a particular person dies from it | a particular person gets it) = 0.09, updating based on a guess of 1⁄2 probability rare equipment is needed and a random guess of 1⁄2 probability fatality without it. 1/2*1/30 + 1/2*((Probability of pneumonia: (1/3+1/4 )*1/2)*(Probability of fatality given pnemonia and rare equipment is needed: 1⁄2)
=> P(death of a randomly selected person from it) = ~1/67
I’m not entirely sure what to think of the numbers; I cannot deny the logic but it’s pretty grim and I hope I’m missing some critical details, my intuitions are wrong, or unknown unknowns make things more favorable.
Hopefully future updates and information resolves some of the uncertainties here and makes the numbers less grim. One large uncertainty is how the virus will evolve in time.
Adding to it a little:
Avoid being sick with two things at once or being sick with something else immediately before.
When it comes to supplements the evidence and effect sizes are not that strong. Referencing examine.com and what I generally remember, I roughly think that the best immune system strengthening supplements would be zinc and echinacea with maybe mild effects from other things like vitamin C, vitamin D, and whey protein. There may be a couple additional herbs that could do something but it’s unclear they are safe to take for a long duration. What you’d aim for is decreasing the severity of viral pnemonia induced by something like influenza.
It’s possible that some existing antivirals will be helpful but currently this is unknown.
The exponential growth curve and incubation period also have implications about “bugging out” strategies where you get food and water, isolate, and wait for it to be over. Let’s estimate again:
Assuming as in the above comment we are 1⁄3 of the exponential climb (in reported numbers) towards the total world population and it took a month, in two more months (the end of March) we would expect it to reach saturation. If the infectious incubation period is 2 weeks (and people are essentially uniformly infectious during that time) then you’d move the two month date forward by two weeks (the middle of March). Assuming you don’t want to take many risks here you might have a week buffer in front (the end of the first week of March). Finally, after symptoms arise people may be infectious for a couple weeks (I believe this is correct, anyone have better data?). So the sum total amount of time for the isolation strategy is about 5 weeks (and may start as early as the end of the first week of March or earlier depending on transportation and supply disruptions).
Governments by detecting cases early or restricting travel, and citizens by isolating and using better hygiene, could change these numbers and dates.
(note: for future biorisks that may be more severe this reasoning is also useful)
I base it on what Greg mentions in his reply about the swine flu and also the reasoning that the reproduction number has to go below 1 for it to stop spreading. If its normal reproduction number before people have become immune (after being sick) is X (like 2 say), then to get the reproduction number below 1, (susceptible population proportion) * (normal reproduction number) < 1. So with a reproduction number of 2 the proportion who get infected will be 1⁄2.
This assumes that people have time to become immune so for a fast spreading virus more than that proportion would fall ill (note thought that pointing in the opposite direction is the effect that not everyone is uniformly likely to get ill though because some people are in relative isolation or have very good hygiene).
It’s based on a few facts and swirling them around in my intuition to choose a single simple number.
Long invisible contagious incubation period (seems somewhat indicated but maybe is wrong) and high degree of contagiousness (the Ro factor) implies it is hard to contain and should spread in the network (and look something like probability spreading in a Markov chain with transition probabilities roughly following transportation probabilities).
The exponential growth implies that we are only a few doublings away from world scale pandemic (also note we’re probably better at stopping things when their at small scale). In the exponential sense, 4,000 is half way between 1 and 8 million and about a third of the way to world population.
I wonder what sort of Fermi calculation we should apply to this? My quick (quite possibly wrong) numbers are:
P(it goes world scale pandemic) = 1⁄3, if I believe the exponential spreading math (hard to get my human intuition behind) and the long, symptom less, contagious incubation period
P(a particular person gets it | it goes world scale pandemic) = 1⁄3, estimating from similar events
P(a particular person dies from it | a particular person gets it) = 1⁄30, and this may be age or preexisting condition agnostic and could, speculatively, increase if vital equipment is too scarce (see other comment)
=> P(death of a randomly selected person from it) = ~1/300
What are your thoughts?
How confident are you that it affects mainly older people or those with preexisting health conditions? Are the stats solid now? I vaguely recall that SARS and MERS (possibly the relevant reference class), were age agnostic.
By total mortality rate do you mean total number of people eventually or do you mean percentage?
If the former I agree.
If you mean the later… I see it as a toss up between the selection effect of the more severely affected being the ones we know have it (and so decreasing the true mortality rate relative to the published numbers) and time for the disease to fully progress (and so increasing the true mortality rate relative to the published numbers).
Thanks for the article. One thing I’m wondering about that has implications for the large scale pandemic case is how much equipment for “mechanical ventilation and sometimes ECMO (pumping blood through an artificial lung for oxygenation)” does society have and what are the consequences of not having access to such equipment? Would such people die? In that case the fatality rate would grow massively to something like 25 to 32%.
Whether there is enough equipment would depend upon how many get sick at once, can more than one person use the same equipment in an interleaved fashion, how long each sick person needs the equipment, are their good alternatives to the equipment, and how quickly additional equipment could be built or improvised.
So the case I’d be worried about here would be a very quick spread where you need rare expensive equipment to keep the fatality rate down where it is currently.
It’s true that this is pretty abstract (as abstract as fundamental epistemology posts), but because of that I’d expect it to be a relevant perspective for most strategies one might build, whether for AI safety, global governance, poverty reduction, or climate change. It’s lacking the examples and explicit connections though that make this salient. In a future post that I’ve got queued on AI safety strategy I already have a link to this one, and in general abstract articles like this provide a nice base to build from toward specifics. I’ll definitely think about, and possibly experiment with, putting the more abstract and conceptual posts on LessWrong.
Yes, the model in itself doesn’t say that we’ll tend towards competitiveness. That comes from the definition of competitiveness I’m using here and is similar to Robin Hanson’s suggestion. “Competitiveness” as used here just refers to the statistical tendency of systems to evolve in certain ways—it’s similar to the statement that entropy tends to increase. Some of those ways are aligned with our values and others are not. In making the axes orthogonal I was using the, probably true, assumption that most ways of system evolution are not in alignment with our values.
(With the reply I was trying to point in the direction of this increasing entropy like definition.)