This thread was created on 3/8/2020, or approximately one million years ago in virus time. It’s getting pretty bloated now, and a lot of things that were high value at the time have been eclipsed by events, making karma not a very useful sorting tool. So I’m declaring this thread finished, and asking everyone to move over to the April Coronavirus Open Thread.

Interested in what happened in this thread? Here’s the timeless or not-yet-eclipsed highlights:

  • Scott Alexander comes up with Hammer and Dance 6 days before Tomas Pueyo
  • Spiracular on why SARS-Cov-2 is unlikely to be lab-created.
  • Two documents collating estimates of basic epidemiological parameters, in response to this thread
  • Discussion on whether the tuberculosis vaccine provides protection against COVID-19.
  • Suggestive evidence that COVID-19 removes sense of taste and smell.
  • Could copper tape be net harmful?
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China is following a strategy of shutting down everything and getting R0 as low as possible. This works well in the short term, but they either have to keep everything shut down forever, or risk the whole thing starting over again.

UK is following a strategy of shutting down only the highest-risk people, and letting the infection burn itself out. It's a permanent solution, but it's going to be really awful for a while as the hospitals overload and many people die from lack of hospital care.

What about a strategy in between these two? Shut everything down, then gradually unshut down a little bit at a time. Your goal is to "surf" the border of the number of cases your medical system can handle at any given time (maybe this would mean an R0 of 1?) Any more cases, and you tighten quarantine; any fewer cases, and you relax it. If you're really organized, you can say things like "This is the month for people with last names A - F to go out and get the coronavirus". That way you never get extra mortality from the medical system being overloaded, but you do eventually get herd immunity and the ability to return to normalcy.

This would be sacrificing a certai... (read more)

If you first do lockdowns to get new cases to ~0 and then relax, optimistically you will get localized epidemics that you can contain with widespread testing, contact tracing, and distancing if needed. Cost of testing & tracing and having to do occasional local/regional lockdowns could end up being manageable until treatment/vaccine arrives.

My main reason for optimism is Korea's and China's success containing a large outbreak. We will be expecting the secondary epidemics and reacting quickly, so they will be small when detected, so should be much easier to contain than the first surprise outbreak.

We'll get data on this in the coming months as China loosens restrictions. There is option value in containing asap and first trying things other than deliberate infections.

1Jackson L
Linking the The Imperial College paper here (which a lot of people have referenced lately) that addresses these two approaches: (a) mitigation, which focuses on slowing but not necessarily stopping epidemic spread –reducing peak healthcare demand while protecting those most at risk of severe disease from infection, and (b) suppression, which aims to reverse epidemic growth, reducing case numbers to low levels and maintaining that situation indefinitely. ( The biggest issue with the suppression strategy is the time required for the lockdown - until R reaches low enough levels that eliminate human-to-human transmission, or until a vaccine is available. Estimated 12-18 months with a r0 of 2.4. In fact the more successful a strategy is at temporary suppression (China), the larger the later epidemic if the lockdown is lifted prematurely - due to lesser build-up of herd immunity (Figure 3, "post-September 2020"). Mitigation: "In the most effective mitigation strategy examined, which leads to a single, relatively short epidemic, the surge limits for both general ward and ICU beds would be exceeded by at least 8-fold under the more optimistic scenario for critical care requirements that we examined. In addition, even if all patients were able to be treated, we predict there would still be in the order of 250,000 deaths in GB, and 1.1-1.2 million in the US."
Their paper is not relevant as they do not analyze testing & contact tracing AT ALL, only mentioning it briefly in the Discussion section. I think everyone who thinks the strategy I describe might be feasible (which now seems to be most informed participants in the discussion on here & rationalist Twitter) more or less agrees with the Ferguson analysis if you assume you can't do testing & tracing & isolation or they won't work.
5Jackson L
Yes you are correct, succinctly addressed here " They ignore standard Contact Tracing [2] allowing isolation of infected prior to symptoms. They also ignore door-to-door monitoring to identify cases with symptoms [3]. Their conclusions that there will be resurgent outbreaks are wrong. After a few weeks of lockdown almost all infectious people are identified and their contacts are isolated prior to symptoms and cannot infect others [4]. "

I've spent some time thinking about endgames here. (Not that I feel like I've come to any conclusions. I wish I knew what e.g. the WHO thought the endgame was.) The biggest problem I see with this idea is the lag between input and output -- when you change your quarantine measures, you can't observe the result for at least the 5-7 days it takes the newly infected to get symptoms, and longer if you want to get a lot of confidence in your measurement, over the noise inherent in the system.

Control systems with high lag like this are incredibly difficult to work with. Especially in the presence of exponential growth like this system has -- if you accidentally let R get a bit too high, it will be a week or two before you notice, and in that time you will have seeded a ton of cases that you will have to track down and deal with.

I think the most hopeful endgame here, near-mid-term, is that we find a combination of antivirals with high effectiveness against COVID-19, which reduces the rate of severe pneumonia dramatically. At that point our hardest constraint, ventilators, will get relaxed. Beds are a lot easier to deal with a shortage of.

Mid-long-term, of course, we're all hoping for a va

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This is why you need to have borders on multiple scales and cancellation of large events. If one case slips through, in a week or two they will infect a handful of new people. If you have set up a system of regional and national borders, as well as cancelled large events, you will find out about this trace the contacts and temporarily increase the strength of the lockdown in only that region. This strategy nearly worked in South Korea, but then patient 31 was a superspreader:
7Alexander Gietelink Oldenziel
Just like to chime in to say that this (=' flattening the curve/ herd immunity') fundamentally doesn't work, and you don't need to have a PhD in epidemiology from Imperial College to understand this [but you might need a PhD in epidemiology to misunderstand it], just basic arithmetic and common sense. Suppose 50% of the UK (33 million people) get the virus of which 5% (~ 1.8 million people) will need serious hospitalization [conservative estimate]. The current capacity of ICU beds in the UK is something on the order of 2000 beds , depending on occupancy rates, ability to scale up et cetera. Let's be extremely optimistic and somehow the UK is able to quintuple this capacity [as far as I can tell this is unlikely]. When somebody is sick they might need care for 2 weeks. The annual hospital capacity is: 25 weeks * 10.000 beds= 250k. At the moment the capacity is nowhere that (perhaps 50-100k). You can see that 1.8 million is far larger than 100k or even 250 k. Even wildly optimistic estimates will not yield anything realistic. This assumes that the government is somehow able to control the infection spreading over a year; instead of two months. There is no reason to think they can do this without extreme (partial) lockdown measures. Controlling the R0 is extremely hard. All the mild measures seem to help only a tiny little bit. If the R0 is only a bit over 1, we still have exponential growth; and you have merely pushed timelines back a few months. Can we perhaps expose young people but lock up older people for one-two years [when the vaccin might arrive]? I find this is extremely unlikely; you need only a couple people to flout the rules to wipe out an entire nursing home. Is it worth it to (partially) lock down the entire country for a year to save maybe a hundred thousand old people? There are only two real possible approaches: 1. Let the Boomers die. If we're lucky the death rate is ~0.7 percent. When (not if) hospitals overflow this will easily triple. Wi
I agree with this analysis completely. There is a strategy bifurcation: Either you lock down hard and contain/eradicate, or you just accept the losses and tell people to go on as normal, with isolation of the vulnerable. The middle path is not favorable. You take both the human damage and the economic damage.
The South Korean approach seems to be roughly as effective as the Chinese approach but significantly less costly and disruptive. SK managed to halt exponential growth and currently cases are increasing linearly at a rate of 75 or so per day. This has been achieved without lockdowns or extensive border closings. Instead, the key ingredient appears to be rapid, extensive and largely free testing, and an educational campaign that stresses the importance of hand washing and staying at home.
I'm confused about why the second strategy works better than the first strategy at killing it permanently. If you shut down everything, shouldn't everything die out faster? (Unless you have open borders and let it in again, but wouldn't that also apply in the UK case?)

The first strategy leaves you with a huge population of people with no immunity to the virus, which means you have to keep holding the lid on it indefinitely or you're back to square one.

In the second strategy, everyone ends up either immune or dead, which doesn't mean the virus is gone -- it will remain endemic -- but there will be no giant flood of new cases when people resume their lives.

(Obviously it's not quite as simple as that if the virus doesn't generate durable immunity. Then you end up with something like the flu, where partial immunity keeps it vaguely tamped down with occasional flares.)

Clarification: you don't need everyone to be immune or dead. Just enough people that the remaining population can't sustain a continuous epidemic.
Right, yes, agreed and good point -- my understanding is that a naive epidemiological model gives a fraction of 1 - (1/R_0) of the population needing to be infected, to drive the effective value of R (new transmissions per infected person) below 1, at which point the population can no longer sustain epidemic spread.
3Lukas Finnveden
Isn't this exactly what "flatten the curve" is about? Because a lot of people are talking about that as a solution, including some governments. The main problem is that the curve needs to get really flat for hospitals to have time with everyone. Depending on how overwhelmed you want your hospitals to be, you could be in lock-down for several years. Some calculations in this article.
Isn't "social distancing" the in-between strategy already? I was thinking of something similar today, when questioned whether to have a friend to my house. If I followed the strictest measures, I wouldn't. But then, if nobody did and we were essentially on self-quarantine mode, then the virus wouldn't spread at all or very, very, little and we would be hovering in small numbers for months, until next fall/winter, when it could get really risky again (presuming that weather has an influence, like with flu). So doesn't the social distancing strategy want some appreciable degree of transmission, high enough to get to herd immunity in a reasonable amount of time, but slow enough to avoid a hospital crisis? Are governments just relying on the idea that some people will ignore the suggestions, and we'll get a reasonable degree of transmission over time during social distancing?
1Liam Donovan
I'm pretty sure that's exactly what the UK is trying to do? I'm actually pretty confident that the UK government isn't planning to have " hospitals overload and many people die from lack of hospital care. ". Even if they were sure that was the best approach (and they just didn't think of your idea?) it would be completely unfeasible politically
But why can't we eradicate the virus? Let's say China shuts down international travel, keeps doing what they're doing, and then slowly eases back up in some area, letting the people in that city comingle and go back to work, but still restricting travel in and out. Let's say they get that city back running, with no coronavirus cases after a month. At the same time...Won't they also have basically eradicated other influenza there? Even if not entirely, there should be much less cold and flu, right? So as soon as coronavirus creeps back in, it should be much easier to contain. I guess my thinking here is, if coronavirus is much more virulent than the flu, and this type of containment works to almost eliminate the coronavirus, could China...actually eradicate the flu, at the same time? If not, why not? The problem comes in from other countries. If China goes to all this effort and the US, Europe, UK etc don't, do we would end up with this weird hazmat curtain? Asian countries would join China in eradicating the disease, and Australia and New Zealand would probably join them.
I've already heard that influenza cases are down in countries that enforced social distancing / lockdowns for coronavirus. However, it really only takes one country not doing this for influenza to return to typical incidence -- there's no real reason to believe it will be eradicated. (However, the same seems true for COVID-19, so I'm not sure what to expect there.)
I agree that actually eradicating influenza feels far-fetched. But on the other hand, it's quite a lot easier to work with than COVID-19. Influenza isn't nearly as infectious, most people have immunity, and it's barely transmissible at all when the carrier is asymptomatic. Imagine you actually did have the "hazmat curtain" situation. Everyone is asked to take their temperature on the way in, and significant fines (and potential visa cancellations) are imposed if you lie. At first nearly everyone is checked to verify, but this is relaxed to spot-checks as people get used to never breaking the rule. Few enough people are getting sick that when people do report influenza symptoms, they can be tested, and contact tracing can be employed to halt the outbreak and trace it back to how it was introduced. If there are no animal reservoirs for the disease, I think that could be viable? It's expensive, but influenza is a big cost in itself, in lost productivity and other problems. The big problem I see for eradicating coronavirus will be in poorer countries --- Africa, the middle east, etc. The outbreaks there are still pretty small, but there's no real resources to address them, so the problem could grow there until it's really hard to fix.

Update: the positions are now filled. See here for the official announcement.

Help wanted: project lead

The high interest and proliferation of questions on the novel coronavirus calls for dedicated attention, which led to the formation of Managing it, though, is straining Metaculus's very limited staff and community moderator team. Contingent on acquisition of funding (which Metaculus is working to secure), Metaculus is looking to bring onboard someone to help manage this project. Components would include:

  • Managing the pandemic site and question series as a sort of "editor in chief" working with the community moderators (as Tamay does now for Metaculus in general.)
  • Helping build data products and analyses out of the questions and results.

The above indicates a range of skills including pretty strong understanding of Metaculus, and data analysis capability. Science background would be great, and huge bonus for actual medical knowledge. This is probably a part-time role but full-ish time is also imaginable depending upon the person, the duration, and funding.

If you're interested, please send a note and CV to

If this news article is accurate, masks will not be scarce for much longer. That article claims that China is now producing masks at 116M/day, a 12x increase compared to the start of February (5 weeks ago), and that they will export them. This is in addition to mask production in other countries.

I  am not sure whether, when combined with production in other countries, this satisfies the entire world demand. But masks aren't complicated objects and aren't made of scarce materials, and this is pretty strong evidence that production can be scaled up even further, if necessary.

In a few weeks, a number of public figures may find themselves doing an awkward about-face from "masks don't work and no one should wear them" to "masks do work and they are mandatory".

(If you are able to buy masks for less than $1/each through ordinary channels, it means the shortage has abated, and you can buy them without worrying about depriving health care workers of those supplies, but you shouldn't stock up on more than you need in the short term until the price has been low for at least a few weeks.)

In a few weeks, a number of public figures may find themselves doing an awkward about-face from "masks don't work and no one should wear them" to "masks do work and they are mandatory".

I want to record and reward how this prediction seems to be correct:

I wonder if China will direct the masks to politically friendly countries, or let the free marker decide.
They'd likely ship them out to everyone as fast as they can, this is their chance to regain political points after this disaster. They already helped out Italy by donating medical supplies and enough people on the social medias are starting to regard them with a better opinion than other European countries, so as a political move is hugely effective.
I would think that would be the smart thing and the right thing. I suspect it also the thing they will do. That said, they have also already publicly stated (reported a few days back) they will offer that type of support "for those participating in their belt and road" initiative and I didn't notice (but did not read closely) if they mentioned nonparticipating countries and where they would stand. Might be more about prioritization in the line.

I heard a rumor of someone in the Bay area claiming to work in the intelligence community, to be terminally ill, and to have received an experimental COVID-19 vaccine. I think this rumor is false with respect to the specific person, but do note that "military officers with preexisting terminal illnesses who volunteer" is a group that may actually exist, and that at least one drug company claims to have shipped vaccines for a phase 1 trial on Feb 24.

This raises the question: if you're well resourced, desperate, competent, and in possession of expendable military volunteers, how long does development for a vaccine actually take?

Given a candidate vaccine, you need to do three things: find out if confers immunity (and how much immunity), find out if it causes side effects severe enough to not be worth it, and scale up production.

All three of these can be done in parallel. If you have expendable volunteers, you don't need to start with an animal model; you can just give them the vaccine, and see whether they suffer side effects. Testing efficacy can be done in parallel, with the same volunteers, and takes about three weeks--you give the vaccine, wait a week, expose to virus, then wait i

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5Ŀady Jade Beacham
For me, that fits my model of what the US intelligence agencies used to do during the cold war times, and we have unclassified documents about proactive, unethical experimentation they did - like Operation Sea Spray and MK Ultra. I don't know if the 2020 US intelligence community is up to the same task. I get the impression that capability and competence have fallen there, although it's hard to know since so much is classified. But judging by the fact that we have had several elections disrupted by pretty predictable cyberattacks without visible countermeasures, my estimation of their competence has fallen. On the other hand, here's an article about a UK laboratory infecting people with a non-covid coronavirus to help with vaccine research.
2Adam Zerner
But the space of possible vaccines is very large, I assume. So even with a ton of human testing that only takes three weeks, maybe this still doesn't help much?
In principle, with enough resources, multiple vaccines could be tested this way in parallel. Not that there are that many vaccine candidates to try, as far as I know; but if there were some software that bulk-generated candidate molecules, it could be done, in principle. The limiting input is mobilized resources, not time.
We have the genome of the virus. All the surface proteins of the virus are candidate molecules.
2Adam Zerner
Yeah, if you could reduce the space of possible vaccines to a smaller set of plausible ones, that certainly makes sense. This makes me wonder, why not just let people volunteer to test risky treatments in general? Because there'd be bad actors who try weird shit willy nilly and misrepresent it to people as more plausible than it really is, such that the harm done to people outweighs the advancements in knowledge? But what if you remove the profit motive and only give this power to government researchers? Would they have too many career-y incentives to be too aggressive?
Human trials are much more expensive then trials in mice. If you can already rule out a drug by giving it to mice you save a lot of money that you don't have to invest into your trial with humans.
2Adam Zerner
True. The downside would be that animal testing is slower, which is I think why jimrandomh was proposing human testing.
Speed is not an important variable for government researchers outside of a situation like this where you need a fast response to a pandemic. Speed matters a bit more for big pharma where it matters if you have one additional year of patent protection for your drug if you develop a year faster but even there the cost tradeoffs are in favor of doing animal testing.
It seems to me much more likely that the Chinese are doing human trials that skip animal testing then that the US intelligence community does that. Terminally ill patients don't make good subjects for clinical trials. If you run such a project outside of the reach of the FDA, it seems like a slight against the FDA. It's not a step in which companies that produce vaccines and that want to have good relationships with the FDA want to make. On the other hand the Chinese government has plenty of people in their prisons that they consider expandable and willing to sacrifice for the greater good. They should also have less institutional resistance to it
The "terminally ill" bit was part of the (probably false) rumor that I heard. Preexisting illness definitely screws with the safety-testing aspect, but there are also illnesses don't interfere with the efficacy testing. I agree that a competent agency uses healthy people for this if they could. If experimenting on healthy people wasn't possible or worth it, one possibility would be to do an efficacy trial on unhealthy people and a safety study on animals in parallel.
I have the impression that you ignore the institutional issues that are at play. The intelligence community can't simply deploy a vaccine on their own. They need buy in from the FDA.

Legally speak, yes they would. Practically speaking, however, the FDA has no enforcement power over secret programs in the intelligence community.

I think a lot of people are seriously overestimating the FDA's actual power, and that's causing pretty severe problems. Consider for example this tweet (and a long series like it) by the mayor of NYC, begging the FDA for approvals. While there is no legal precedent to refer to, it's extremely implausible that the FDA could ever get or enforce a judgment of the city of New York for actions taken during a state of emergency, when the FDA itself caused that emergency with culpable negligence.

The FDA has no power to stop the intelligence community running tests on patients but they do have the power to declare the results of the tests as not being enough to prove the resulting vaccines safe. Do you really think that you have a better idea of the institutional power of the various players then the mayor of NYC? The FDA has a lot of relationships that allow it to exert power that are distinct from direct legal tools.
There are some articles today about people trying out a drug called remdesivir
In general vaccines are very easy to make. You grow the virus you want to vaccinate against, kill or weaken it, and inject it, often with an adjuvant. Viral illnesses that don't have vaccines today are the exception where it turns out that doesn't work and it's more challenging. These difficult ones are what all vaccine research today is focused on, so people think making vaccines is hard. It usually isn't. Small pox, measles, mumps, rubella, chicken pox, and polio are all gone. Flu is 4 new viruses we make brand new vaccines for every year.

Are the economic forecasts still too sunny?

(Warning: Long comment)

Two weeks ago Wei Dai released his financial statement on his bet that the coronavirus would negatively impact the stock market. Since then (at the time of writing) the S&P has dropped another 9%. This move has been considered by many to be definitive evidence against the efficient market hypothesis, given that the epistemic situation with respect to the coronavirus has apparently not changed much in weeks (at least to a first approximation).

One hypothesis for why the stock market reacted as it did seems to be that people are failing to take exponential growth of the virus into account, and thus make overly optimistic predictions. This parallels Ray Kurzweil's observations of how people view technological progress,

When people think of a future period, they intuitively assume that the current rate of progress will continue for future periods. However, careful consideration of the pace of technology shows that the rate of progress is not constant, but it is human nature to adapt to the changing pace, so the intuitive view is that the pace will continue at the current rate. [...] From the mathematician’s
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The idea that smart investors don't understand exponential curves is absurd on its face

I don't think this is necessarily absurd or false. Like, this is what Black Swan Farming was about.

I think people in finance are used to exponential curves with doubling times of 20 years, and this doesn't give them much of an edge when it comes to doubling times of 2 days. Like, even in semiconductor manufacturing, the progress of Moore's Law over someone's 40-year career corresponds to about a month of viral growth at that rate. 

Startup finance people do work with stuff at roughly the same scale, and correspondingly freaked out much more.

The sheer insanity of such a prediction should give you an idea of how uncertain this whole thing still is.

I don't think this is crazy, once you consider healthcare system failure. What does the world look like if no one receives medical care for any condition besides a COVID infection for the next three months?

I don't have a strong stance either way but I think there are some interesting points for the other side. Let's say this is on the order of a ww2 number of deaths. Look at the impact of ww2 on the economy. Except with the present situation there's no need to halt international trading, and none of the productive assets get bombed. This still leaves a lot of room on the side of it being worse than many of these sunny projections, but what I want to point at is that it is also really common to drastically underestimate how bad things can look locally and still have trends mostly do alright due to the enormous differences of scale between what it takes for things to look bad and what it takes for things to be bad everywhere.

This blog post argues that the now popular idea of "flattening the curve", in the sense that most people get exposed but slowly enough to not overwhelm the health care system, is not feasible. The result is that we'll either achieve containment or at least widespread regional health care system collapse (and maybe Wei Dai's global health care collapse outcome). I haven't spent much time modeling this yet, but tentatively it looks like flattening the curve requires very precise fine-tuning of R0 to stay on a path very close to 1 for at least several months, which seems impossible to pull off.

It feels to me now that flattening the curve is just a nice graphic without anyone checking the math, but I am confused that many informed-seeming experts are promoting the idea. Anything I'm missing?

ETA: I made an epidemic + hospitalization model (Google Sheets), it sure looks like the usual flatten-the-curve chart is a comforting fiction. Peak hospital bed demand in the uncontrolled epidemic scenario is usually drawn at 2-3x hospital capacity. I'm getting 25x and the chart looks a lot less reassuring. My shakiest assumptions are hospitalization / intensive ca... (read more)

Disclaimer: I don't know if this is right, I'm reasoning entirely from first principles.

If there is dispersion in R0, then there would likely be some places where the virus survives even if you take draconian measures. If you later relax those draconian measures, it will begin spreading in the larger population again at the same rate as before.

In particular, if the number of cases is currently decreasing overall most places, then soon most of the cases will be in regions or communities where containment was less successful and so the number of cases will stop decreasing.

If it's infeasible to literally stamp it out everywhere (which I've heard), then you basically want to either delay long enough to have a vaccine or have people get sick at the largest rate that the health care system can handle.

5Sammy Martin
South Korea, Singapore, Italy The UK. We're running an interesting experiment to see which approach works. One potential benefit is that the world will be able to observe which of the two strategies is viable and switch between them, at least theoretically. Practically, switching from 'suppress/contain' to 'flatten curve' seems a lot more feasible than the alternative of trying to suppress after not taking tough measures, as the UK will have to do if its strategy means cases grow out of control. South Korea could still try to use curve-flattening as a backup plan. However, for the reason given in the blog post, suppression will be a viable backup even if switching from curve-flattening to suppression is intrinsically harder than the other way round.
Still seems to me like you should be able to isolate those problem areas from the rest of the country. Then even if you can't contain the epidemic inside, you spare most of the country (for the moment). But I think we mostly agree. A scenario that seems increasingly likely to me is that governments will intervene in increasingly strict ways until we get very close to true containment (before ~15% of the world is infected), and then will loosen movement restrictions in more-contained areas while playing whack-a-mole with a sequence of localized outbreaks for 1-2 years until a vaccine is ready.
Borders, travel restrictions, cancellation of large events, contact tracing and testing will solve this. Borders are necessary precisely because of this dispersion issue.

That's an interesting question that seems like it ought to be able to be checked numerically.

I made an attempt using this simulator of the fairly-naive "SIR" model of disease transmission:

Note that this simulator appears to be someone's class project. However, its behavior seems to track more or less with what I'd expect. But I'd love for someone with more experience to reproduce this relatively simple model and check it.

You can read about the model at .

I have limited confidence that I've understood it correctly, so take this for what it's worth. It looks to me the time step used in this simulator is one day. So the gamma parameter (rate of recovery per unit time) should be (Wikpedia says) 1/D where D is the duration of the disease. (For transmission modeling purposes, this should be the infectious duration, not the duration of symptoms.) I chose gamma=0.7, meaning D ~= 14 days, semi-arbitrarily, based on (

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Thanks for pointing me in this direction. I think the key worry highlighted in the post is that the health care system gets overwhelmed with even just a few percent of the population being infected. So even if we can bring peak infections down by a factor of 2-4 by slowing transmission, the health care system is still going to be creamed at the peak.

I've now built a discrete-time, Bay Area version of the SIR model (+ hospitalization) in this Google sheet. I assume 20% of infections need hospitalization, of which 20% need intensive care, and use raw bed-to-population ratios (non-COVID utilization vs stretching capacity should roughly cancel out). Hospital bed availability at peak infections is 4% (25x over capacity) in the uncontrolled beta=0.25 scenario and only improves to 10% (10x over capacity) in the "controlled" beta=0.14 scenario. Even if my hospitalization/ICU numbers are too high by a factor of 5 the "controlled" scenario still looks pretty terrible. Any feedback on the model assumptions would be super useful.

I haven't checked your models quantitatively, but qualitatively I absolutely believe you that the options here are "bad" and "really really bad", and that neither one of them gets us down to where we need to be. The difference between 4% and 10% could still save a lot of lives; at that level it may be close to 1:1 (every bed freed up is a life saved), since only the most critical cases will be getting beds at that point. But you're right that this is clearly not adequate, and the graphic showing the flatter curve as peaking under the capacity line is pretty misleading. (There are versions of the graphic which don't, but they appear to have been memetically outcompeted by those that do.) I think it's still true that "flattening the curve" will save lives, potentially a lot of lives, so even if the graphic might be a bit misleading as to the possibility of flattening it below the critical threshold, I think it's still a reasonable meme to promote. But really the ultimate goal has to be reducing R below 1, which will arguably flatten the curve, just not quite in the way the meme seems to be trying to get at. I don't want to steer too close to dark side epistemology here, but if the meme gets people to stay inside, cancel their parties, and wash their fucking hands... it's hard for me to be too against it, and I think it's probably true enough?
I don't know how other people react. I took the epidemic fairly seriously but my initial reaction to the meme was one of reassurance/complacency - OK so I can't avoid eventual exposure anymore, but at least things will proceed in a somewhat orderly fashion if we cancel big events, wash hands, stop touching our face, etc. I feel like this is the sort of attitude that contributes to, and allows the public to accept, decisions like the capitulation in Sacramento. The mental image of mitigation is "basically trying to mitigate the risk to those who are most at risk: the elderly and those with chronic underlying conditions". The reality is that we'll be forced to let all the old and sick die in hospital parking lots. It seems to me fairly likely that the public will ultimately accept the Hubei-style lockdowns that will result in containment, but this meme probably is responsible for delaying that moment by at least a few days :(

I saw the meme as mostly targeting people who were currently even more complacent "eh, there's nothing we can do, so fuck it", and getting them to instead go "okay, there's stuff that's actually worth doing."

You're probably right.
Alex, I'm looking at your spreadsheet and I don't understand where you got these bold numbers from. It looks like you tweaked your sheet a bit since writing this comment, but still I can't figure out what you are looking at when you say 25x and 10x over capacity. Could you explain?
Yeah I got better hospitalization/ICU rates from Bucky and upped beta to 0.3 in uncontrolled scenario to make a point on Twitter. Hospital/ICU bed availability % is graphed in each scenario tab, by overcapacity I mean the inverse of availability. Alternatively take ratio of peak to line in the Charts tab. Looks like ~15x and 5x now for hospital beds.

That's a really interesting blog post, and it made me update (towards the idea that containment efforts in most countries will keep ramping up until containment actually succeeds). How did you come across it? I've been following Twitter, a couple of FB groups, and Reddit, and it didn't get linked by any of the posts I saw.

It feels to me now that flattening the curve is just a nice graphic without anyone checking the math, but I am confused that many informed-seeming experts are promoting the idea. Anything I’m missing?

I'm wondering this too.

Don't recall how I ended up seeing it, but it was through this tweet by the author: (ETA: Razib Khan RT'd him)
2Sammy Martin
Perhaps the numbers work out better when you include cocooning of populations that disproportionately make use of hospital resources
I think each little bit of curve flattening makes things a little less bad (since a smaller number of cases are beyond capacity, and a little more time is created to prepare), but the graphs tend to draw the "capacity" line unrealistically high. This graph is more realistic than many since the flattened curve still peaks above the capacity line, but it still paints too rosy a picture.
Nice model. For hospitalisation / intensive care, the original data from China had 14% "severe" and 5%"critical" cases. These are percentages of diagnosed cases so you would need to modify these with the diagnosis rate. For the Diamond Princess about 50% of cases were asymptomatic so that is likely an upper limit on diagnosis rate. Ascertainment rates from these papers are highly variable so an actual number here is hard to estimate. That suggests hospitalisation is probably no more than 10% and intensive care no more than 2.5%. These numbers are a bit lower than your model but not enough to get us out of the woods.
4Sammy Martin
From the blog post: I have heard '5-15%' and '20%' and '12%' for hospitalization/'no-treatment fatality' rates, with a trend that the newer estimates tend to be lower. The initial figure from China was a blood-curdling 20%, as you said, while a current projection based on evidence from real overwhelmed healthcare systems is a merely very bad 3-5%. This is lower by a larger factor than most of the reductions to the CFR that account for undocumented cases - perhaps indicating there are more undocumented cases than those corrections imply? Also, of relevance to the UK's strategy (cocooning older people from infection), how does this breakdown by age? This poster has estimated that young, male, no pre-existing condition have 1/4th the risk of hospitalization (assuming a 50/50 chance that the intersection of age-30/no-pre-existing condition has a much lower risk than either alone) - which means if older and vulnerable people can be 'cocooned', the actual rate of hospitalization can be slashed again by a factor of 4 to something bearable, around 1%, if you take 4% as the baseline. (note that the corrections in this paper for delay to death and underreporting skew the death rates even more strongly towards older patients, with the fatality rate among 20-29 barely changing after adjustment but the fatality rates among 60+ doubling). That means you could surf a wave of a few hundred thousand people having the virus at a time and still provide adequate ICU space. With some expansion in capacity, that could be even higher.
Thanks for digging these up! I updated the model. Still terrible.
I'm wondering why you are also coming up with a LOT more hospitalization than even cases reported in China. In early April, if I'm readying this right, you are expecting the Bay area to need over 80,000 hospital beds for COVID-19 for the uncontrolled case (I assume that is merely a comparison scenario) and then after 3 months, say starting July, in the controlled scenario about 81,000 hospital beds will be needed. Then things keep going up. That seems like something is missing there. Why would the Bay area really expect to see such drastically higher impact than China as a whole? Using your 20%, 20% assumption and saying China is at 85,000 now, the total demand for hospital beds would have been 20,400 over the entire December - March time period.
China locked down Wuhan at ~500 confirmed cases and many other Hubei cities the next day, which immediately lowered transmission (see Chart 7 here) to R0 below 1. This is very far from the uncontrolled scenario and still overloaded the health care system. This is much of the point of the post I linked -- the degree of hospital overload in an uncontrolled scenario is so high that even huge reductions in transmission don't realistically avoid overload if R0 stays above 1.
I do get that point, and do think it is one that is well made. At the same time, I find the numbers produced a bit on the high side. Clearly the 20,400 number being within existing capacity for the Bay area completely ignores current patients unrelated to COVID-19. But perhaps under a regime of social distancing, containment and isolation of both known cases and by the more concerned both the speed of growth and the total number your model is producing would be much closer to manageable.
I think it might also be worth considering hospital beds -- to some extent -- is not a fixed quantity to can expand as demand increases. Consider using hotels or other (these days rather vacant) building/structures. That's basically what China has done here (and in other cases with their "legos" 10 day to build hospitals -- rejected the concept of what a hospital is and how fixed the supply is. Just as an assumption check, was your hospital bed/ICU bed value an average for, say the USA, or some other country level metric or an average of the local hospital to service area metric?
I used overall US numbers. I didn't consider capacity expansion but also didn't take out already-occupied beds, as I think both are roughly on the order of 2-5x in opposite directions. The only Bay Area-specific numbers are population and day 0 infected (I assumed ~10x confirmed cases).
It worked in 1918:
I should have made it clearer I don't deny we can literally flatten the curve, but rather the idea that Unclear to me how well St Louis did on the health care system front. Also, the pairing of Philadelphia and St Louis is a bit convenient if you consider the raw scatterplot (panel C bottom left - ETA Philadelphia is the dot closest to Pittsburgh per this table).

I think it would be valuable to compile a list of estimates of basic epidemiological parameters of the coronavirus, such as incubation rate, doubling times, probability of symptomatic infections, delay from disease onset to death, probability of death among symptomatics, and so on. I find that my inability to model various scenarios accurately is often due to uncertainty about one or more of these parameters (uncertainty relative to what I suspect current expert knowledge to be, which is of course also uncertain to a considerable degree).

For current expert knowledge, this list of values from lots of different papers might be helpful.

Wonderful, thank you so much.

Did you end up finding one besides the MIDAS network, or develop your own? I'm assembling a parameter doc for inputs to a rough model that accounts for ventilator & hospital bed capacity, since it seems like we're lacking that.

  • I encourage folks to add parameters w/ citations to the doc, I'll be active on it for the next few days.
  • If anyone knows of models that incorporate actual healthcare capacity, please share!
Thanks for putting this list together. I stopped looking after Bucky supplied the link to the MIDAS network list, since it seemed so comprehensive. For models that incorporate actual healthcare capacity, see this thread. One limitation of the models I've seen is that they fail to account for growth in such capacity. China responded to the realization that they didn't have enough hospitals by quickly building more hospitals. Maybe Western countries are less competent than China and it will take them longer to build the needed capacity. But it seems implausible that they will be so incompetent that capacity-building efforts will not make a significant difference.
5Eli Tyre
Having a list of of values of interest, with estimates and citations for each, would be great. But in addition, I gotta say, this seems like just about a perfect use-case for prediction markets: we have a bunch of individual, well operationalized scalars, for which accurate estimates that incorporate all of the existing information are of high value. Is anyone in a position to set up, or to subsidize, a market on these values?
I second this.
And to start compiling a list of common problems with the parameter estimates being used. Eg I am seeing some models extrapolate naively from the fact that most cases are coming from the least controlled places with the widest uncertainty bars.
I'm also very interested in this. Here are some numbers I've been using: * Ratio of confirmed to unconfirmed cases (USA): 34 (50%), or 5 (5%) to 94 (95%) This is based on , which estimated the true number of coronavirus cases in Seattle (as of 2020-03-01). I divided that by the number of confirmed cases in Seattle at that time. * Doubling time (USA): 4 ish (which I'm treating as 2 (5%) to 7 (95%).–20_coronavirus_outbreak_data/WHO_situation_reports is how I'm getting 4ish. There are papers that estimate higher: gives 7, for example, but that appears to be in Wuhan post-containment.
South China Morning Post had a story line a day or so back where Chinese experts were suggesting a 10 fold increase every 19 days. Interestingly the rate seems to be about double that if you look at the last 19 days. I did not look past the totals but suspect that is highly dominated by South Korea (seems to be slowing), Italy and Iran (these two do not seem to be slowing). Might also be interesting to put a latitude metric in as well -- while I have a "sense" that more equatorial areas have a lower incident (and may be spread rate) I've not seen that data plotted anywhere.

Paper on some of nCOV's mutations

Incidentally, also strong evidence against it being a lab-strain. It's a wild strain.

Closest related viruses: bats and Malayan pangolins

Mutation Descriptions

Polybasic Cleavage Sites (PCS): They seem to have something to do with increased rates of cell-cell fusion (increased rate of virus-induced XL multi-nucleated cells). Mutations generating PCS have been seen in Influenza strains to increase their pathogenicity, and they had similar effects in a few other viruses. So it's not exactly increasing virus-cell fusion, it's actually... increasing the rate at which infected cells glom into nearby cells. Fused cells are called syncytia.

O-linked glycans : Are theorized (with uncertainty) to help the virions masquerade as mucin, so hiding from the immune system. (Mutation unlikely to evolve in a lab on a petri dish)

Arguments strongly in favor of it being a wild strain

  • It's not that similar to one of the known lab-strains, so it probably was wild
  • The "polybasic cleavage site" and "O-linked glycans" mutations would have required a very human-like ACE-protein binding site, so basically only human or ferret cells
  • O-linked glycans are usually evolved as an immune defense, which isn't something cell cultures do.

(Just following the recommendation to move this out of shortform so it can be tagged later.)

Chinese virology researcher released something claiming it SARS-2 might even be genetically-manipulated after all? ZC45 and/or ZXC21 backbone. Claims that the RaTG13 genome was a concocted cover-up. After assessing, I'm not really convinced of the GMO claims, but the RaTG13 story seems to have something weird going on. See here for my further thoughts on this. EDIT: After assessing, I'm not finding the GMO claims convincing. The RaTG13 story does seem to have something weird going on, and there's several people and papers that note weird inconsistencies (See the further thoughts, I don't have a simple explanation.).
Additional little bit that reminded me of that cell-cell fusion trait... another paper described the SARS-CoV-2 autopsy results, and included this: Translation: The paper-thin, high-surface-area (for gas exchange) cells wrapping your lung balloons (the pneumocytes in your alveoli) fuse together with each other into an ineffectual, clumpy mess with a way lower surface-area-to-volume ratio. These are fragile cells to begin with; they don't even replicate themselves (other cells have to replace them when they break). They don't seem to be producing virus themselves, but they do seem to be getting badly screwed up by things the virus is doing.
What exactly does "lab-strain" mean here? Does it means a strain with a already published sequence?

More specifically:

  • It was not genetically modified for use as a bioweapon
    • The mutations don't resemble other well-known and well-characterized pathogenicity mutations too closely, in sequence or location
  • It probably wasn't cultured as cell-culture in a lab-setting for an extended period
  • The virus was not notable to science prior to this event

Or in other words, it doesn't look planned. Its most recent mutations look much more like a "natural variation let it jump species" sort of situation.

This doesn't address situations like, for example, "dead bats with a wild-type virus being left near a bunch of ferrets or pangolins," or something to that effect.

(ETA: Or... accidental release like this is still possible.)

Despite the virus being characterized in pangolins, after looking into this, I now think it is basically incorrect to think of this as primarily a "pangolin virus." The pangolins were a dying canary in a coal mine, and probably caught it from something else that serves as the real reservoir species for this nCOV precursor*. See: further explanation here

Two facts:

  1. HCoV-OC43 (one of human coronaviruses causing common cold) can generate cross-reactive antibodies against SARS.
  2. Immunity to HCoV-OC43 appears to wane appreciably within one year.

Here's the paper which mentions both of these facts. (The actual paper is not important, I expect these facts to be well-known to coronavirus researchers, if the paper itself is not terribly mistaken and if I haven't misread anything.)

Even if cross-immunity is mild, won't it make sense to intentionally infect people with HCoV-OC43? Downside seems quite small compared to the number of deaths, and intuitively it seems that "mild cross-immunity" = "less severe SARS-CoV-2 cases", which is extremely valuable.

I notice I'm confused, since these facts should be well-known to pretty much everyone who's working on the vaccine. What's the explanation for why it's not a good idea?

Possible explanations, but I'm probably missing something:

  1. Vaccines which cause the actual illness are considered unethical. (Probably not? I don't expect humanity to be that stupid.)
  2. Mass-producing HCoV-OC43 virus is too hard for some reason. (Possible? I don't know much about vaccine production, and I'm clueless about whether
... (read more)
There's speculation that having acquired immunity to similar viruses leads to worse outcomes with COVID-19, and that's why children don't have many symptoms. This is still highly speculative, I won't be surprised if it turns out to be something totally different, but it would make me nervous about this plan.
Okay, SARS-CoV-2 is pretty different from SARS-2003 ("~76% amino acid identity in the spike protein"), this might be the reason it won't work. OTOH, I don't know how different HCoV-OC43 is from both SARS strains.
Similar to the thing Elizabeth mentioned, I'm concerned about the possibility of antibody-dependent enhancement wherein an imperfect antibody match actually worsens the course of the infection. I've tried to look into this. My results weren't conclusive, but I think it's a very real possibility for this virus, and fairly likely to slow vaccine development due to the added testing it neccessitates. I opened a question on it here.
I would also like to know the answer to this. One thing I'm not sure about: how hard is it to get your hands on HCoV-OC43? With high confidence and in quantities suitable for pretty much guaranteeing to give someone a cold / some immunity? (Do excessive quantities lead to a more severe cold?) This does really seem like something someone should be working on. Probably someone is, somewhere... EDIT: Here is one paper on the consequences of HCoV-OC43 infection: Among other things: "Recent studies have suggested [that human coronaviruses] can cause severe lower respiratory tract illnesses in children." and "In our population, HCoV-OC43 infections generally caused upper respiratory tract infection, but can be associated with lower respiratory tract infection especially in those coinfected with other respiratory viruses." So safety might be in question. EDIT 2: Scihub link: EDIT 3: I would really love for someone who knows things to take a look at this paper actually, and help interpret it. It is only studying children, and notes that "HCoV-OC43 infections tend to occur before 2 years of age" (does that mean adults can't get it? or they aren't exposed to it much? Does exposing them to it generate a useful immune response?), and also that, among the children selected for the study, children with HCoV-OC43 had better outcomes than controls (but I have no idea how to normalize this for statistical issues; the subjects were children who tested positive for HCoV-OC43, whereas the controls were children who were tested for respiratory viruses but were negative for HCoV-OC43.)

This paper is well worth a read, according to me. Given that we have all kinds of problems doing testing for COVID-19 in the US, the authors do an analysis of the ratio of people seeking medical help for flu-like symptoms, but testing negative for the flu, to people testing positive (compared to previous flu seasons). The idea being that if COVID-19 is spreading, we should be seeing increases in flu symptoms relative to flu diagnoses.

However, I'm confused about Arizona. (See figure 4 in the paper). It looks like its score on this axis has been 2 to 3 standard deviations from the mean for the decade since November.

What's going on?


  • The Flu season in Arizona was so bad this year that the number of people who came in with flu symptoms skyrocketed, relative to other kinds of ailments, and even though most of those people did test positive for the flu, the wILI term swamped the (1 − proportion of tests positive for influenza), for an overall much higher than usual ILI-.
    • Is that mathematically plausible?
  • There was some other flu-like non-flu that was spreading in Arizona since November.
  • The flu diagnosis process spontaneously failed this season, producing orders
... (read more)
Based on figure 4, this would predict that the midwest would have a worse epidemic than the pacific NW right now, and twitter reports from hospitals don't seem to bear that out.

Why are we prioritizing testing the sickest people? AFAIK diagnosis doesn't change what care is given, so it's irrelevant to them. Testing people who might be sick and take high impact action based on the results (e.g. medic deciding whether to go to work) seems higher impact.

Possible explanations: sickest people get the most positives and that's important for contact tracing, I am wrong about how it affects care (in particular it might affect if you get an isolation room or no)

My assumption has been that the primary purpose of testing is for contact tracing. I would suspect that probably don't have enough tests at this point to usefully test everybody who is ill and yet still planning to go to work, even just people with healthcare jobs -- I'm assuming that someone who is ill, but still thinking about going to work at their healthcare job, is probably not very sick, in which case most of those tests would end up negatives, on people who just have colds/flu.
Most tests you carry out on anyone else will be negative, so even if you think there's an 80-90% chance the patient is COVID-19 positive, you still get more information from running those tests than the lower symptomatic people. Also, it does change all sorts of decisions. It probably changes what precautions the healthcare workers need to take, and it lets you tell the person's family to self-isolate. Otherwise the husband is in critical condition, and the wife might be a week behind, so she's in the waiting room making everyone sick.
Hm, can you say more about information? I believe you should get the most direct information (in the information-theoretic sense) out of running tests where the outcome is most in doubt (i.e. where your prior is approximately 50%, although I think this might budge a bit depending on the FP/FN rates of the test if they are different.) You also get information about their contacts -- if their contacts have a lower-than-50% base rate of exposure, then it seems like you get more of that "secondary information" from a positive than from a negative. (I'm not too confident about that, but certainly at worst it's equal, right?)
An accurate count of how many people are infected may be a highest priority. Since the virus has exponential growth, the difference between a known count of 10 infected vs 100 infected is massive in terms of policy decisions. Undercounting is extremely dangerous to the entire population. This could change once the number of infected patients gets very high, but we may not have seen numbers high enough to justify that anywhere outside of China yet.

Several counties in California are now advising people not to bother self-quarantining at home after COVID-19 exposure unless they get symptoms. This seems wildly irresponsible to me. I understand not wanting to use valuable health system resources on people who are unlikely to have the virus, but home self-quarantine does not cost the health system anything now, and it is likely to save the health system a lot of cases later. Right?

This seems in particular very much at odds with Italy's striking decision to lock down the entire country, including whole regions with no known exposures.

Any thoughts?

Reading between the lines, it sounds like they're no longer contact tracing. I would interpret this to mean they're not tracking down people to recommend that they, specifically, self-isolate, but it's not a blanket recommendation not to self-isolate. They also don't seem to recommending that, but it's not clear they ever did.
I think that would have been a very reasonable thing, but no, it is a blanket recommendation that self-quarantine for known exposure is not required (at least for Sacramento County): "With the shift from containment to mitigation, it is no longer necessary for someone who has been in contact with someone with COVID-19 to quarantine for 14 days. This applies to the general public, as well as health care workers and first responders. However, if they develop respiratory symptoms, they should stay home in order to protect those who are well. "

What are the issues involved in receiving delivery food during this pandemic?

Can one safely receive and eat delivery food as follows: Avoid contact with the deliveryperson (have them leave it outside), carefully dispose of the packaging in the same way you would for a package delivery, then take the delivered food and reheat it in the oven for a time/cooking temp that will kill the virus?

The respiratory viruses as a family do not appear very resistant to heat (as compared to e.g. some of the foodborne illnesses.) From (I didn't check the citations yet), it seems like 70C for 25 minutes will kill most respiratory viruses thoroughly. This is such a low temperature that I wonder if hot food is inherently inhospitable to them even without the reheating step. My oven dial doesn't even go that low. (Getting the center of the food to this temperature could be challenging without using a higher oven temperature, but you really only need to do the surface; the center has already been cooked, and any relevant contamination will be on the surface from post-cooking handling.)

(There is also a mention of

... (read more)

I like the discussion in Food Safety and Coronavirus: A Comprehensive Guide. Note that the author has a conflict of interest, but I don't think he let it affect the article.

Thanks, I believe that article is great advice and I fully endorse it -- I saw it a few days ago but never came back here and updated my comment.
FWIW I think this'd make a good top-level question post.
Thanks, will maybe do that today, it's on the queue.
My preliminary look gave me a similar "huh, is cooked food just totally fine?" reaction, but I don't trust myself to have enough context to know the answer.

An review of Ferguson et al's paper by Nassim Taleb has come out:

I think this document contains the essential strategy for quickly bringing covid-19 under control. I'll call it "Containment and Eradication":

1. Close national borders

2. Reduce R0 below 1 using a thorough lock-down, social distancing, testing, contact tracing and hygiene

3. Once the outbreak is quite small and testing capacity is decent, aim to drive the number of infected individuals as close to 0 as possible

4. Test aggressively and wait a couple of weeks

5. Gradually return people to mostly-normal life, but with large gatherings cancelled for the foreseeable future due to the possibility of super-spreader events, and international travel mostly cancelled.

6. Keep borders fully closed to until we have a vaccine, or at least impose long quarantine periods on travelers.

Approaches to covid-19 that involve getting a large number of people infected to build herd immunity and minimize the damage along the way are far inferior to this. The Ferguson et al analysis showed us just how messy that would get, but I think it wa... (read more)

As part of the LessWrong Coronavirus Link Database, I am publishing a daily update post with all the new links we are adding each day that we ranked a 3 or above in our importance rankings. Here are all the links we added over the weekend.


Coronavirus: Why you must act now (medium post)

Summary and call to action, one of the best summaries I've found, focuses more on policy-interventions than on individual actions, but is still good at giving you an overview

UpToDate: Coronavirus Overview

UpToDate very frequently has the best overviews over many crucial medical topics. Geared towards a more professional medical audience. 

Letter to loved ones asking to take CV seriously

Well written, compassionate explanation of why this is worse than what we've seen before and need to take this seriously. A few pointers on where to get started

Early February 80,000 hours episode on Coronavirus (1h 18min)

Long episode on coronavirus. Includes all the basic information, and discussion of big-picture implications

Spread & Prevention

Masks help prevent infection in schoolchildren

In a group of 10,524 Japanese schoolchildren, masks and vaccination decreased the chance of catching

... (read more)

How useful is it to heat your house to 75F+? To heavily humidify your house?

Why not ask this as a question post?
3Ŀady Jade Beacham
Do you expect transmission to occur within your house? From a guest? Or at a grocery store or outside contact? Seems like it would only help in the in-house case. I expect this to be pretty far down the list of useful interventions
If you get delivery, or shop at a grocery store but avoid coming near the people there, a significant part of your risk may be from contamination of objects you bring home. In that case this question seems important.

I’ve been keeping notes on corona virus risk reduction tactics and turned some of them into a webpage to share with my family and friends. The idea to to make them as quickly actionable/understandable as possible. This is the pretty version, but you can contribute here.

I'm very interested in critical feedback, including if any of these tactics are likely to be harmful/ineffective or if I'm missing anything high-value/low-cost.

I consider my copper wrapped stick to be a high-value/low-cost option. It allows me to open door handles/light switches without having to touch them with my hands.

A new paper: Correlation between universal BCG vaccination policy and reduced morbidity and mortality for COVID-19: an epidemiological study says that vaccination for tuberculosis has a potentially large effect on COVID-19 problems. This explains some of the strange differences between countries. That's bad news for the U.S. (which hasn't required the vaccine), good news for some countries.

That's extremely interesting. I would love to see someone in our community who I trust to be good at statistics redo the analysis, since all the data is public. Apparently there are already multiple trials underway, though: . The Science article came out before the paper, so I wonder where the idea struck first. Apparently the broader pro-immune effects of the BCG vaccine for tuberculosis have been known or suspected for a long time; see e.g "Non-specific effects of BCG vaccine on viral infections",, which is a fucking wild read and I highly recommend reading the whole paper.
It is also a hope in type 1 diabetes: - this is really unexpected stuff.

I'm still trying to understand how COVID-19 actually spreads. (Related to my recent question on touching-vs-breathing.) Based largely on this article, my current very-low-confidence belief (in decreasing order of importance):

Again, very low confidence in all this. Thoughts?

We are looking for forecasters/"estimators" to help with estimating various COVID-19 parameters, such as number of infected cases, which will go into epidemic modelling, augmenting unreliable reported data. Ideally the end product should be the results of the modelling presented in a good web UI. If you would be interested in helping, reply privately.

Q&A: How does it compare to Metaculus? In a few important ways.

1. the estimates are not the end product, but an input to epidemic modelling software

2. in our UX, we want to clearly communicate the results of the epidemic are not pre-determined, but depend on actions humanity will take

3. we want to expose more of the uncertainties and underlying dynamic, as opposed to static forecasts

Have you thought about cooperating with Metaculus?

Read the Imperial College COVID-19 Response Team report tonight.

The numbers are quite starkly grim, based on an epidemiological simulation model. They conclude that mitigation strategies (only isolating symptomatic people, social distancing only at-risk people) will at best reduce the load on the healthcare system to "only" 8x current surge capacity in UK/US, leading to estimated 1.1M deaths from COVID-19 alone (i.e., not considering possible deaths from other causes due to an overloaded healthcare system). Instead, suppression strategies (everyone socially isolating) need to be followed for 12-18 months to ensure that the load from COVID-19 stays within surge capacity, minimizing total deaths to the low hundreds of thousands, and buying time for a vaccine / treatment to help beat back a second epidemic after relaxing suppression measures.

I am curious about a few assumptions in their model (wish it was open-sourced!), and how this might change the estimate.

1) They assume a fixed ICU capacity (where I think the main limit is ventilato... (read more)

My understanding is that the treatment requires significant monitoring and skill; the ventilation is often invasive (they have to get the tube into your lung, rather than just into your mouth). But for a while people have been suggesting compartmentalizing the medical system further. If you just want someone to be a 'ventilator nurse', able to intubate a patient and then manage a ventilator for that patient, could you do that with a 30-day training program? Seems likely and worthwhile, but will require some sort of emergency legislation to authorize in most places, and some rapid development of curricula and testing. Similarly, expanding production runs into legal issues. You may have heard about the volunteers who 3D printed ICU valves; they asked the company for blueprints, and the company threatened to sue for the IP violation. You might also have heard about the patent troll who sued the makers of a COVID19 test for infringement; they dropped the case once it was public that the use was a COVID19 test. It seems like a potentially sensible government action here is to nationalize (or otherwise force licensing) of technology that's useful in a disaster, with the government paying for the IP after-the-fact based on actual usage out of the overall disaster response fund. But in general, our 'peacetime' standards for medical devices are very high. If you want to take your toaster factory (or w/e) and start spitting out ventilators instead, there's a lengthy approval process because this is complicated stuff with many ways things can go wrong. When the alternative is nothing, it's probably good to have rush jobs available, but there's nothing in place (that I'm aware of) to allow this sort of rapid ramping.
For intubation: * The patient is usually sedated/unconscious. (drugs need to be administered) * correct insertion of endotracheal tube ( endo ~ inside trachea = windpipe) The first hard part is getting the tube past the vocal cords in the larynx. This requires the correct positioning of the patient to be able to see the vocal cords. (fibreoptic scope sometimes necessary) and to align structures for easier insertion. Laryngospasm where the vocal cords come together to block the airway is a major concern. (the vocal cords coming together is a normal part of swallowing to prevent things going into the airways and contacting the cords will induce a spasm.) This can be reduced by using a local anaesthetic spray on the cords - essential if the patient is conscious (a rare situation). Correct placement of the endotracheal tube is critical. It must be within the trachea, above the carina (where the trachea splits into the main bronchi and definitely not into a lung). If the tube goes into a bronchus it means one lung gets air, the other doesn't. A bad intubation is worse than no intubation. For ventilation: * Fancy equipment or * Someone squeezing a ventilation bag. (+ oxygen supplementation) But ultimately, nurses/EMTs/medical students can be trained to do all this in a few days. If someone's competent and confident and has adequate back-up in-case of issues.
I think we might want to be in the world where we train a substantial fraction of the recently unemployed, or the National Guard, or whoever to do this, which requires starting from a lower point than nurses/EMTs/medical students.
There's a big difference between the process of intubation and maintaining a patient once intubated. Someone with no prior knowledge of anatomy and physiology intubating patients (even after intense training) would increase the risks to patients. A mistake could be fatal. Time is a crucial factor - less than 4 minutes to correct an issue (brain needing oxygen). Sedation/paralytic drugs need to be given. Dangerous in themselves. (an old saying re intravenous anaesthetics - dead easy, easily dead) Adequate supervision/ back-up would be essential. Aptitude of the trainee would also be very important. No room for getting stressed. 1st rule emergency medicine - breathe. Better for the more experienced to intubate and then training people on ventilator management / how to squeeze a bag at the right pressure and timing (when ventilators aren't available).
Tracheal intubation in the ICU: Life saving or life threatening?

I'm a nurse in an at risk area. Should I shave my long hair like the Chinese nurses were doing?

I know that a roommate of a friend if coughing regularly according to my friend. I'm living in Berlin. How likely is it that the roommate is having COVID-19 based on the available information? How careful should I be interacting with that friend?

Epidemiologist Behind Highly-Cited Coronavirus Model Admits He Was Wrong, Drastically Revises Model (archive)

Epidemiologist Neil Ferguson, who created the highly-cited Imperial College London coronavirus model, which has been cited by organizations like The New York Times and has been instrumental in governmental policy decision-making, offered a massive revision to his model on Wednesday.

Ferguson’s model projected 2.2 million dead people in the United States and 500,000 in the U.K. from COVID-19 if no action were taken to slow the virus and blunt its curve.
However, after just one day of ordered lockdowns in the U.K., Ferguson has changed his tune, revealing that far more people likely have the virus than his team figured. Now, the epidemiologist predicts, hospitals will be just fine taking on COVID-19 patients and estimates 20,000 or far fewer people will die from the virus itself or from its agitation of other ailments.

Ferguson thus dropped his prediction from 500,000 dead to 20,000.

Author and former New York Times reporter Alex Berenson broke down the bombshell report via Twitter on Thursday morning (view Twitter thread below).

“This is a remarkable turn from Neil
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7Wei Dai
1Lukas Finnveden
That article is based on a twitter thread that is based on this article that is based on the parliamentary hearing that Wei Dai linked. The twitter thread distorted the article a lot, and seems to be mostly speculation.

I have a lot of hand sanitizer I bought for a dance weekend that is now cancelled. What should I do with it?

EDIT: I gave some to an immunocompromised friend, some to friends who have critical jobs, and the rest to a food pantry

Keep them until you more clearly see what the best possible or most urgent immediate use turns out to be.
How about donating them to nearby retirement home?
Too bad ebay is no longer an option.
Facebook marketplace?
Put them on a table at work or school with a sign saying "fee - take one".
I mean, I can definitely distribute them randomly. I'm trying to figure out if there's something better to do with them. (They're also gallons, so a bit tricky to distribute)
2Ŀady Jade Beacham
If you are going to donate them I would suggest local hospitals or urgent cares might put them to best use. I wish we had managed to get some hand sanitizer, we only managed to find travel sized ones before shtf.

Health care settings are likely to already be well supplied, and to be picky about which kind of hand sanitizer they use (even if it's just about getting an internal approval).

I was feeling rudderless trying to do actionable CV research without a grounding in its basic science, so I took a step back to build a foundation. These are the top sources that were useful to me:

These have also been added to the links DB


What's the best way to convince skeptics of the severity of COVID? I keep seeing people saying it's just a slightly worse flu, or that car accidents kill a lot more people, and so on. I want some short text or image that illustrates just how serious this is.

I found this heartbreaking testimony from an Italian ICU doctor:

But I guess skeptics will want a more authoritative source.

8Steven Byrnes
A nice figure is that 1 person infected with COVID-19 requires (I think) 100x the hospital capacity of 1 person infected with the flu - 30x likelier to need hospitalization, and they stay there 3x longer if they do (you'll have to check these figures, but it's something like that I think...). Then that connects to the nightmarish Italian hospital situation you mention, and the fact that the death rate is dramatically higher without available hospital beds, including for young healthy people.
5Lukas Finnveden
Angela Merkel says that 60-70% of Germany is likely to be infected. That's useful if people believe that it won't infect that many. Example source, though you can google for others. If they're willing to believe a redditor's summary, this one says that WHO says that 20% of infected people needed hospital treatment for weeks. (If they want primary sources, maybe you could find those claims in the links / somewhere else.) Putting together 1 and 2 (and generalising from Germany to whatever country they're in), they ought to be convinced that it's pretty severe.
It is now literally not true that car accidents kill more people, in either the UK or Italy, and won't be true in the US in about a week. I've found the time-delayed log graphs like this one pretty convincing:
For today, I have been directing people to this chart of Italian intensive care hospitalizations and deaths, 2020 COVID-19 vs 2018-2019 flu season: (Source: As well as this news story about Italy banning all public gatherings across the whole country: Plus the fact the the stock market is down >10% over the last week...
Maybe citing the CDC:

Should poly people consider stopping intimate contact (hugs+) at some point? The network structure of polyamorous relationships might make people particularly vulnerable.

Having all partners isolate together is maybe another option for small polecules who all get along well.
3Ŀady Jade Beacham
From the WHO report on China, most infection clusters they found were family clusters. This may be applicable to your thinking on this.
Something is weird about that 3-10% secondary attack rate number. The study isn't published yet, so I don't know what exactly they're measuring, but I'm pretty confident that people who share a household and hug each other will transmit at much greater than 10% probability.
This is a fairly late update, but closing the loop on this: I believe the 3-10% number ended up being the secondary attack rate among households where the infected person was isolated after diagnosis. So that's an estimate of the rate of transmission during extended close contact before symptoms/diagnosis, not after, which makes more sense. I assume that extended close contact with a symptomatic infected person will result in very likely transmission.
Keep in mind that there may be substantial variation in the amount of viral shedding for infected people (there are superspreaders, presumably there are also subspreaders), as well as in the susceptibility of people to the virus (presumably there is some cross-immunity for people who have had a coronavirus-type common cold recently, for example.) So the transmission rate among household members can't necessarily be estimated from the per-contact rate assuming each contact is an independent chance of transmission.

[Epistemic Status: It's easy to be fooled by randomness in the coronavirus data but the data and narrative below make sense to me. Overall, I'm about 70% confident in the actual claim. ]

Iran's recent worldometer data serves case study demonstrating relationship between sufficient testing and case-fatality rate. After a 16 day long plateau (Mar 06-22) in daily new cases which may have seemed reassuring, we've seen five days (Mar 24-28) of roughly linear rise. We could anticipate this by noticing that in a similar time frame (Mar 07-19),... (read more)

Metaculus has extended the Li Wenliang prize series - win $$$ as well as internet points by forecasting the course of the COVID-19 pandemic!

And the prize money for the second installment has increased since I wrote this comment!

Today will always be the day that, for one hour, Facebook removed all posts/comments that had links to any of The Atlantic, Medium, and LessWrong. Because we're just that big and important.

(The issue is now fixed.)

Here's some perspective on U.S. stock market reactions to bad news (of nonfinancial origins):

  • 1918 Spanish Flu: -10% in slightly over 5 weeks?
  • 1940 Fall of France: -25% in slightly over 2 weeks
  • 1942 Pearl Harbor: -11% in slightly over 3 weeks
  • 2001 9/11: -12% in less than 2 weeks
  • 2020 COVID-19: -26% in 3 weeks (so far?)

These numbers are based on closing values for the S&P500 (for 1918: the DJIA), from the day before the obvious start of the crash, to an obvious low point where it stabilized. Note that the reaction to the 1918 flu is confusing, maybe

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Complete speculation here: Our economy in 1918 was based much more on agriculture and industry, whereas now it is much more based on services, aka people going to work, which they now can't do, and also much larger. So perhaps the coronavirus will, in fact, destroy more real value than the Spanish flu was able to, even as a percentage of the market.
>Maybe the U.S. and European markets had reflected a much safer world than anyone at the time of prior disasters had expected? that's part of what super low rates/yield imply right? That people expect a very stable world. Higher multiples are flimsier in the face of new evidence.
There are probably many factors that make this different now than before. However, I suspect that markets today are just smarter than back then. As a result, they react much quicker to information than before. I don't think you can estimate the drop magnitude by the looking solely at the rate of decrease.

1/13 people have Asthma. How much worse off are we?

Data point: There were no asthma patients among a group of 140 hospitalized COVID-19 cases in Wuhan. But nobody had other allergic diseases either. No hay fever? Seems curious.
Allergies and asthma are rare in China and other poorer countries. The standard explanation I'vev head is
That group also was only 1.4% smoker, while china-normal in 2015 was 27.7% (almost all of whom were men). I wonder if people worried they'd get worse care if they admitted to respiratory co-morbidities?
Right now I expect they just used hospital admission forms. If I was self-reporting 5 pages of medical history while I'm critically ill I'd probably skip some fields. Interesting that they did find high rates of diabetes etc though.

Here's a credible-seeming claim from a computational biologist that, if COVID-19 is like other coronaviruses, long term immunity is unlikely. I imagine this also means a vaccine is unlikely.

If true, this changes everything. Does this mean we are all going to be working from home for the rest of our lives? Or will we accept a world where there is an endemic disease that we get for 3 weeks every year?

I think this doesn't quite change everything, for the following reasons: * Even if long-term immunity is unlikely, short-term immunity will push this back towards the flu category, where most people are not getting it acutely at the same time. This will significantly improve the healthcare situation vs what we're seeing in the pandemic phase. * Diseases evolve towards increased spread, which usually involves evolving towards reduced lethality / severity. If this becomes endemic it's likely to do the same. * If it turns out that this does become a severe endemic disease, there will be a lot of pressure on the development of a vaccine, much more so than has been true for human coronaviruses in the past (when they were much closer to being mostly a nuisance, and included in the general "common cold" category.) Even if long-term immunity is unlikely, we can still improve the situation like we currently do with influenza, giving people periodic boosters based on the current circulating strains.
7Chris Hibbert
Diseases normally evolve toward increased spread by reducing lethality because they don't have a superpower like Covid2019's ability to spread while the carrier is asymptomatic. I don't think there's much evolutionary pressure on this disease toward lower severity. Even if we do a good job of enforcing shelter-in-place in populous areas, there will be hidden reservoirs until we reduce the number of new cases in connected communities all the way to zero. The normal evolutionary pressure works because there's some variation between different strains, and whichever variant can reach the most people comes to dominate. With a normal infection, once everyone is aware, you can quarantine people with evident symptoms and thus squelch the spread. Any variant that has milder symptoms has a better chance of spreading and becoming dominant. Covid2019 already has the ability to escape surveillance if there's any of it in the population, so a less lethal variant doesn't have a selective advantage.
My understanding is that asymptomatic spread is pretty common.
4Chris S
That's a good answer, and consistent with this very good article by Johns Hopkins epidemiologist Justin Lessler. He makes many of the same points you make, and adds that there will likely also be partial immunity even within individuals. (At least, I suppose, if we aren't facing antibody-dependent enhancement.)

A friend of mine (who lives in the SF Bay Area, currently somewhat of a coronavirus hotspot) posted to Facebook that he hasn't been feeling well recently and he thinks he might be sick (and was having trouble focusing at work yesterday). I posted the following; I don't know him well enough to know how he'll take it, but we'll see. I feel like we're still at a point on the curve where this kind of individual outreach can potentially have substantial value, so I'm offering it as perhaps a template for other people to use.

Yikes, good luck -- I hope you feel

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Does anyone have updated figures on the fatality rate for different age groups, compared to the ones posted in this comment?

I imagine that that table is mostly based on data from the early outbreak in China, which may or may not generalize well to say, my parents.

1Christoph Richter This provides a more detailed overview of the china data. Specially, most patients have been ill before. As Cadiovascular conditions mostly are with elderly persons this makes them a high risk group.

Questions about buying chloroquine:

1. Is it better to buy hydroxychloroquine or regular chloroquine? The studies I've found suggest hydroxychloroquine is safer and more potent, but it is a bit more expensive.

2. How many days worth of the drug is it reasonable to buy per person?

3. How much should someone take per day and how should the dosage be timed?

4. Can someone confirm that the products you can find on when searching for "Lariago" (500 mg chloroquine as phos) and "OXCQ" (200 mg Hydroxychloroquine Sulfate) are the right things to buy? If not, is there any other reputable or semi-reputable source that sells the right product?

That's the right stuff I think (chloroquine phosphate, very bitter tasting), would you say that reliablerxpharmacy is a good and trustworthy source? (not for chloroquine, for meds generally without a prescription)

Hi, I haven’t posted in a while, and I hope that people are still reading new comments in this thread, because I need an answer fast, and this is the best place that I know to get a good one. (Well, second best. I posted to SSC first.)

My parents, age 70, live in Lincoln NE (population 285 thousand, no reported cases of Covid-19 yet, 17 reported cases in the State, schools just closed and are preparing to go online). They pretty much run their bridge club, most of whose members are in their 70s but generally in good health. The club has an event planned f

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Here is what I wrote my dad in attempt to get him to close up the church of which he is an elder, in a similarly sized city. My dad is a statistician and 30% prepper, so this was more about giving him evidence to take to others than convincing him: I didn't think of this at the time, but in retrospect it would have been helpful to suggest replacements for an in-person service. I'll bet it is easier to convince your parents' friends to switch to online bridge with voice chat than to give it up entirely.
I have good news and bad news. The bad news is that the game went on last night as planned. The good news is that my parents won't be attending any more large games. The bad news is that there are still going to be more large games, at least one tonight. Although it's mostly the same population every time.

The club is now closed until further notice.

Asked a general version of the question here
Previous versions of this question:

I have created the top two graphs of my previous post on outbreak speeds as interactive versions here (thanks to Ruby for helping with getting this uploaded). The labels on the right are clickable to remove or add countries (double click selects only that country or all countries). The buttons at the top change the y-axis (annoyingly the y-axis range buttons auto-set to a linear scale) and the slider at the bottom zooms the x-axis.

We started an effective altruist coronavirus discussion group on Facebook and there are a lot of posts in it. The link is here if you're interested.

From a friend who is a microbiologist Phd "Oh and drink plenty of water. My lab group discovered that humans and cows partially rid their body of viruses (at least adenovirus) through their urine. "

It also apparently helps with lessening the spread from the mouth/throat to the respiratory tract making it more likely to stay mild.

I recommend people write covid-19 things here rather than in shortform, because soon we'll have tagging properly implemented for posts, but not for shortform, and it'll be easier to find all coronavirus related commentary if it's here.

This can't be right. I've looked into Diamond cruise studies and some stay at 1% even after adjusting for age (they factor in that more people might have died in the meantime – even though that didn't happen so far, admittedly – and the unadjusted number is 1% at least already; makes you wonder whether elderly cruise goers are healthier than their stay-at-home cohorts). I've found this study which, after doing some adjustment steps I don't understand but find dubious (maybe they double adjusted something by accident?), ends up estimating 0.5% for China's total outbreak. You might think this makes the 0.125% figure mentioned by Joannidis somewhat plausible, because China's outbreak had a majority of cases in Hubei where patients didn't all have access to hospital care. This is likely to drive up the fatality rate. However, the study didn't account for that. They just implicitly assumed that people who got sick on the cruise ship had the same prospects as people who got sick in China. And they may or may not have halved their estimates in some dubious way too. So, 0.5% seems like an absolute lower bound here, and more li... (read more)

Yeah, the 1/8th multiplier sounded hard to believe. A 1/2 multiplier based on demographic correction sounds a lot more plausible, and it's nice to have confirmation that someone else actually did the math. Thanks for finding/sharing it!
I should flag that I didn't do the math for age correction. I only got this from another Diamond cruise study where the age correction provided a smaller update (and I didn't really like other things about that study). So, I think it could be valuable to investigate this claim more: (But even if this point was right, there's still South Korea to explain.)
Reading the Ioannidis article, it seems to say that he did his own calculations, and he doesn't show them. Okay. I'm curious about this, so I'm going to try a ballparking estimate myself. Tl;dr I intially arrived at a result that suggested 0.125% was way off, but then found better info on the cruise ship's age distribution and had to revise my judgment. I now find it debatable whether 0.125% is defensible or not, but it's not "way off." My own estimate would be more in the ballpark of 0.3%, but I don't anymore consider the cruise ship to be evidence for IFR estimates at 0.5% or higher. Update March 24th: In the couple of days, 3 new patients who had tested positive on the Diamond Princess have died. In addition, the Wikipedia article has been edited to list another death that previously hadn't been included. So total deaths per confirmed cases on the Diamond Princess are now 11 / 700 instead of 7 / 700. All my calculations below are based on the older, outdated numbers. To get the most updated estimates, just multiply the results below by 11/7. --- Note that I have never done age adjustments for anything, so I have no idea what the proper methdology would be. I'm just curious to see if 0.125% is potentially reasonable rather than (as my current intuition suggests) very dubious. From this paper, I found the following info: At the end of the outbreak, roughly 700 people had tested positive. I'm going to assume that the 66 patients not yet in the above statistics fall into age categories in the same proportion. So a bit more than two thirds of the 66 patients get added to the 476 figure for people aged 60 and older. With this adjustment, we have 700 diagnosed cases, of which an estimated 525 patients were aged 60 and older. Of those 700 diagnosed cases, 7 people died. 525 out of 700 corresponds to 75%. (I'm going to mostly ignore the death risk for people below age 60 for the analysis below, because it will be negligible given that people older than that anyway
You found an age distribution for the infected population on the Diamond Princess, but you're using it as if it's the age distribution for everyone on the ship. Older people are more likely to get infected, so the infected population in the US will lean older as well--closer to the distribution on the ship. To do a good age adjustment we need to know the ages of the people on the ship who were not infected.
Interesting! Do you think this is established? I haven't looked into this, but my guess would have been that the risk is similar because young people are less scared of the virus. But yeah, good point about further adjustments being needed to get the best estimate.
Hmm, maybe you're right. The South Korean distribution of cases by age here suggests that it's actually most common by far among people in their twenties, and the larger number of confirmed cases among older people is a statistical artifact resulting from test criteria. The data do look a bit suspicious though.
Right, I got that it was them doing the math correction not you. Still, they did the math and give an age breakdown of the passengers and a crude sanity check gives a number within about 30% of what they report.
I don't think the view in that piece here is consistent with what happened in Lombardia in Italy, but I haven't seen a detailed numerical argument against it.
I also thought that in Lombardia, the estimates given by Ioannidis are rapidly trending toward coming in contradiction with SIR models. :( Lombardia has a population of 11 million people and 2,500 reported deaths. Some doctors are raising alarm that many deaths are going undetected because people are dying at a rate that's 4 times higher than the same month last year. In addition, the death counts always lags behind because some people are sick for a long time before they die (though maybe this start to be the case less strongly in conditions of extreme hospital overstrain). All of this suggests that an estimate of 10,000 deaths for Lombardia alone might soon prove to be accurate. But according to the IFR provided by Ioannidis, this would correspond to an expected 8 million people infected (72% of the population). I don't understand SIR models well enough to calculate what the R0 would have to be for 72% of a population to get infected. I suspect that Covid-19's R0 is high enough to be consistent with this, but it wouldn't leave a lot of room for estimation errors. That said, I think the above calculation is naive, so the argument doesn't work (at least not in this crude form). If hospitals become as overwhelmed as they are in Italy, I'm sure that even someone with Ioannidis' view would expect the IFR for Lombardy to become a lot higher than 0.125% because a lot of people aren't getting life-saving hospital attention. So, this means that Lombardy isn't necessarily a knockdown argument against Ioannidis's estimate in the same way South Korea is. However, I think Ioannidis's estimate would have counterintuitive implications for the percentage of people infected in Lombardy. It would have to be in the double digits already at the very least. The most trustworthy estimate I saw about Wuhan suggested that only 5% of its population had the virus. However, there's some disagreement about this, and the people who tend to argue for an unusually low IFR also tend to argue t

Does this thread welcome asking for highly personalized advice? I'm stuck with a few possible action options and the explanation is quite lengthy and the answers will probably be relevant to very few. I can't decide whether this thread is only about posting globally useful things or not.

That would be discouraged in a top level post but is exactly the kind of thing this post is for.
Oddly specific advice is fine.

In the usa, much of the workforce is paycheck to paycheck and does not have paid leave or short term disability, and health issues are a common cause for bankruptcy. So the following is applicable to a lot of people who probably are not in this (rationalist/lesswrong) community:

If you don't work, you don't get paid, so you don't make rent. If you get quarantined by the state after a positive test, you don't go to work, you don't get paid, and you don't make rent. If you don't make rent, you probably will not have a place to live. If you end up in the h

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I have been taking NAC (n-acetylcysteine) as a supplement for a while.  You can (still) buy it on Amazon.  From an Elsevier press release "The authors draw attention to several randomized clinical studies in humans that have found that over the counter supplements such as n-acetylcysteine (NAC), which is used to treat acetaminophen poisoning and is also used as a mucus thinner to help reduce bronchitis exacerbations, and elderberry extracts, have evidence for shortening the duration of influenza by about two to four days and reducing the se... (read more)

I'm particularly interested in people sharing models / spreadsheets that they're currently working through here. (Posting them as top level posts is also fine, but I thought it might be good to encourage more "thinking out loud" in quantitative ways, even while you're still fleshing a model out and still have a lot of open questions about it)

Here's my bay area hospital capacity model:
Here's a basic SIR model created by Metaculus user Isinlor. (I haven't looked at it, so don't interpret this comment as an endorsement.)
Buck's tentative Guesstimate model of Wei Dai's "hospital crowding" catastrophic scenario. Many folks have already seen his comment, but I'm posting a link to it for completeness.
Daniel Filan's Guesstimate model on whether he should stay home for work. Many folks have already seen his comment, but I'm posting a link to it for completeness.
3Lukas Trötzmüller
When to cancel events due to Coronavirus? Calculations by Linch Zhang [1], I've put them into a Guesstimate with some slight changes and adaptions for Austria [2] [1] [2]
3Lukas Trötzmüller
Dating during Coronavirus: What's the risk of going on a date with a random new person at the height of an outbreak? Under my assumptions, if 1 in 7700 people gets newly infected every day, it translates to an infection risk of 0.2% per encounter (range of 0.45% - 0.053%). Feedback welcome.
3Tobias H
Here's a tool to estimate how badly hospitals will be overfilled in your community. It's by Richard Neher and colleagues and an early stage tool. Might nevertheless be interesting to play around with. Here's the source and some explanations about the underlying model:
Unfortunately it doesn't let you modify the assumptions about disease severity or number of undetected cases. It assumes that the majority of cases have been undetected (which seems questionable) and that 4.31% of cases are severe (which seems low even if the majority are undetected). It gives a case fatality rate of 0.97%, which doesn't seem to depend on any of the other parameters. In their baseline scenario (for a small Swiss city with good infection control) 0.26% of the population dies. With no infection control this goes up to 0.76% of the population dying, with no change in the CFR. If you also increase the length of a hospital stay from 10 days to 20 days, the total number of deaths actually decreases slightly because the spread is slower. So while the graph is a nice way to see how long hospitals will be overwhelmed in different scenarios, it doesn't show you anything useful about how this affects outcomes. I would love to be able to add in some parameters for fatality rate for severe and critical cases with/without a hospital bed.
Sad laugh. I'm in Switzerland, we have exponential growth and there's no infection control to speak of. They just told people with non-severe symptoms to not bother getting tested. Schools are open. Haven't seen even one person wearing a mask.
Another basic SIR model, which considers impacts on hospital capacity (and resulting deaths) from infection controls of various degrees.
2Eli Tyre
Coronavirus automatic tracking and population modeling v.2
The Medium article that Wei Dai cited in his comment links to an "open-source model". I haven't examined it closely, though I did notice that some of the formulas are weirdly constructed (e.g. using INDIRECT rather than absolute cell references) and that some of the assumed parameters are overly pessimistic (e.g. a 3.4% CFR).

I'm still pondering the implications of transmission being mainly about air, not touching. What interventions does that suggest? Besides the obvious things (opening windows, HVAC filters etc, masks & goggles), one thing I thought of is ... perfume!

We could all encourage everyone to wear perfume / cologne when they leave their home, and if anyone can smell anyone else, then they know you're not sufficiently well physically-distanced (too close or not enough air circulation).

Assuming this would work, I'm not sure how to get it to take off. Maybe an unusu

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Suppose one of the drugs under investigation for COVID-19 effectively reduces its morbidity and mortality. For simplicity let's say that it quickly and completely cures 90% (or X%) of patients but does nothing to the remaining 10%, and we manage to scale up manufacturing enough to be able to treat everyone with the drug. Would the major developed countries then decide to relax the current mitigation/suppression policies and let the pandemic run its course (thereby accepting the morbidity/mortality of the refractory 10%) in order to revive their economies? What do you think the threshold for X would be for the major developed countries to do this?

I feel like there's wet spaghetti code at both ends of this? On one side we have economic impact projections that vary about an order of magnitude and the other we have expected death projections that vary over 1-2 orders of magnitude.

Someone on Hacker News had the idea of putting COVID patients on an airplane to increase air pressure (which is part of how ventilators work, due to Fick's law of diffusion).

Could this genuinely work?

2Chris Hibbert
Airplanes pressurize to levels that aren't as high pressure as being on the ground, I'm pretty sure. They're trying to reduce the consequences of being at altitude, not increase above sea level.

The New York Times heavily implies that many sick package delivery workers are feeling pressured to show up to work despite their illness.

A sneak peak at the coming economic impact:

Google trends: How to file for unemployment. 3-m&geo=US&q=how to file unemployment

Many have probably seen the threads (e.g., here and here, and this Medium post by Yishan Wong) about how massively scaled up testing is the key to threading the needle between economic collapse (long-term suppression tactics) and unacceptably high mortality (mitigation only, or worse, doing nothing). Aggressive and scaled up testing infrastructure is the key enabler for contact tracing, which appears to be the cornerstone of the South Korea model, which notably does not rely on draconian suppression tactics like lockdown, and they are currently the only ot... (read more)

Is somebody keeping track of the "what if we're wrong and it turns out this is another Y2K" scenario? Social distancing, closing borders, heightened awareness and preventative measures -- seems like a lot is happening that could make this way less scary, at least in the US, than most of the mainstream scenarios.

I'm not interested in the hearing from denier-types who think this is "just another flu", but rather the thoughtful people who have specific testable predictions that would demonstrate this is more social contagion than most of us suspect.

That is, a combination of "prevention work successfully means no big disasters" and "absence of prevention work doesn't cause any major disasters"? I think that cat is already out of the bag on the latter one; people might end up disagreeing on whether it was better to be in Iran or Wuhan, but they won't be able to disagree that the lockdown in Wuhan had an effect. I think there will be variation in what sorts of social distancing happen, which we should be able to back out data on, and similarly demonstrate that social distancing had an effect. (I expect it'll be smaller than many people hope it'll be, but it'll still be noticeable.) Like, we could see the effect in 1918 influenza data, and we have a much better ability now to track how people come into contact with each other. [I expect the main thing to happen is that people take insufficient protective measures, which makes them look like a waste, or we get stuff like "ah look, extensive social distancing meant the peak happened two weeks later!", which is of unclear value compared to the costs.]
Those arguments make sense, but for example what if despite our best modeling, the cases just start to decline and then the whole thing just disappears in a month? At what point would we have to seriously re-evaluate everything we know about this virus? Say new cases plunge 90% next week? 50%? Scenario planners try to think of every possible alternative, including those that seem far-fetched. I'm trying to figure out what the positive alternatives would look like.

From A Technical Explanation of Technical Explanation:

How would I explain the event of my left arm being replaced by a blue tentacle? The answer is that I wouldn’t. It isn’t going to happen.

If a miracle happens, then a miracle happens. I'm not holding my breath.

The ways in which I do expect Vaniver_2021 to look back at Vaniver_2020 and think "yeah, he was worried about that but it didn't turn out to be relevant" are various unknowns about the virus that might be fine or might be bad. For example, we don't know how bad surface transmission will be, but that's a big factor in what sort of isolation protocols you need to have. We don't know whether existing anti-virals will be effective. We don't know how long immunity will last, but that's a big factor in whether or not 'herd immunity' strategies will work, and how valuable it is to not catch it. We don't know how big a deal antibody-dependent enhancement will be, or how that will interact with the duration of immunity. We don't know what long-term effects of infection (think fatigue, disability, infertility, etc.) look like. We don't know how long people are infectious before they show noticeable symptoms.

For all of those things, I

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I thought that we were right about Y2K, people spent a lot of time preparing for it, and their hard work saved us all. Is that wrong? (I understand if you just link to somewhere else and don't clutter up your thread any further with this digression.)
According to some as summarized by wikipedia, there's not all that much evidence that people who didn't prepare were bitten by it, or that fixing ahead of time was cheaper / better than fix-on-failure.
I mean Y2K in the sense of lots of fretting about something that turns out not to happen, whether because of significant preparation or from just being wrong about the urgency. I realize it doesn't seem likely, but in the spirit of humility before humanity's collective ignorance, how might we know we were wrong? Like, clearly nobody's expecting US cases to suddenly level off and then disappear, but what if that happens anyway? At what point would we say we were just totally wrong?

Ohio health official estimates 100,000 people in state have coronavirus:

This sounds crazy, but I don't understand the methodology so I'm not sure... Do people think it's plausible?

I can't rule it out, but it doesn't sound like this estimate was arrived at through sound practice.

Follow-up: Trevor Bedford has also debunked the claim in this twitter thread, saying that by the time Wuhan had 100,000 infections there were 1000 severe cases and 300 deaths. For Ohio to be in that state now the disease would have had to be spreading there since about mid-December.
6Michael McLaren
This ^...Another way to spot check the "100000 cases" estimate without knowing the Wuhan numbers is to consider that that would imply roughly 1e5 / (2^4) = 6250 cases 3 weeks ago (the typical delay between infection and death; assuming 6 day doubling time), which corresponds to 31-125 deaths by today for a case fatality rate in the interval of [0.005, 0.02]. That would be for Ohio alone. As of March 13, the US CDC is only reporting 36 deaths for the country as a whole (source; though reported as 47 deaths here) and Ohio is currently reporting 0 deaths (source). Not to say that this is a definitive argument against there being 100000 cases in Ohio, but it does suggest that this estimate wasn't based on current understanding of the virus and its spread. Update: On March 13 Trevor Bedford also tweeted a rough estimate of 10K-40K cases nationally.
I hope that there is some actual epidemiology going on behind the scenes here that is being oversimplified for the press, but there's nothing in the article to really indicate that the estimate has anything meaningful behind it...
I believe it's obviously wrong and the stated methodology makes no sense. The fact that community transmission is occurring does not by any means mean that 1% of the population is affected. It's possible there's some other information that justifies this but I would be *extremely* surprised if it were actually the case that 100k people are infected in Ohio right now.
If this was the case it ought to be visible indirectly through its effect on Ohio's healthcare system. I haven't heard of such reports (and I do follow the situation fairly closely), but I haven't looked for them either.
1Lennard Iosif
Adding to this - what impact would this have on Wei Dai's estimates on mortality rates skyrocketing if health systems are overburdened? If significant portions of the population already have the illness, then would that imply a significantly lower mortality rate than expected? Or could this simply be a leading indicator that we are closer to the peak than we originally thought?

How should I disinfect objects with complex surfaces (e.g. box cutters, door knobs) if I don't have access to alcohol? Is brushing with soap likely to be sufficient or should one just avoid touching these objects for a few days if they're possibly contaminated?