trentmkelly/LessWrong-43k huggingface dataset:
SARS-CoV-2 pool-testing algorithm puzzle
by Steven Byrnes — 2020-03-20T13:22:44.121Z

According to this article, it's possible to test a pool of up to (at least) 64 people for SARS-CoV-2 at once, and the test will say whether at least one person in the pool is positive. So, here's the puzzle:

We have a large number N of people that need to be tested. Each has SARS-CoV-2 with probability P. (The cases of interest are P<5%, maybe even P<1%, see comment.) We can test any subset of the N (or maybe up to a maximum pool size S), with the test returning positive if at least person in the subset is positive. (Bonus: allow that the tests are imperfect, with a per-test false positive rate FPR and false negative rate FNR.)

Your mission is to develop a testing protocol, i.e. an algorithm for what tests to run in what order. The simplest example (proposed in that article linked above) would be: Test non-overlapping groups, and if the test is positive, test each individual within the group. But is there a better way?

Score your algorithm's success on some combination of: (1) minimal total expected number of tests, (2) trying not to ask people for too many samples (lower priority on this one I think[1]), (3) false positive and false negative rates for individuals, (4) minimal serial time (i.e., minimal number of steps where we need results from step N to figure out what tests to run in step N+1).

(I'm not sure how to combine these criteria into a single score that reflects practical goals; if anyone knows, please comment. Or tell me if I'm leaving something out.)

Bonus: What if we have prior information, in the form of a N×N correlation matrix? (This could reflect the fact that for cohabitants / colleagues / neighbors, it's likelier that both or neither have it.)

The swabbing process is mildly unpleasant, so other things equal, better to not require lots of swabs. I don't know whether or not it's possible to split the sample one swab and put it into multiple test-pools. ↩︎
Preprint says R0=~5 (!) / infection fatality ratio=~0.1%. Thoughts?
by Hauke Hillebrandt — 2020-03-20T11:37:34.488Z

What do people think of this preprint from March 13th?

It suggests:

R0=~5 in Wuhan in January (pre-containment measures)
Infection fatality rate=~0.1% (several orders of magnitude smaller than the crude CFR estimated at 4.19%)
~2 million infections in Wuhan on Jan 23rd / ~20% of people infected

The authors are very reputable (GScholar profile first author, senior author, also quoted in the NYT).

If this is true, might there be many more (asymptomatic) cases everywhere now than people think?

[Reddit thread]

From paper:

"Recently more evidence suggests that a substantial fraction of the infected individuals with the novel coronavirus show little if any symptoms, which suggest the need to reassess the transmission potential of this emerging disease"
Online Fun LW/SSC Meetup, March 24
by JoshuaFox — 2020-03-20T10:26:08.267Z

In this online video-chat, we'll start with personal introductions for some sociability, and then do a Rump Session: That's where anyone can step up and give a four minute talk; then, if you want to keep talking, the audience votes on whether to permit another three minutes.

Talks can be spontaneous rather than prepared, and on any subject that turns you on: Science topics, poetry readings, history tidbits, or anything else (except for COVID-19--that's strictly out!).

At LessWrong Israel, we've found this to be a lot of fun--no risk of being bored or boring, as talks are so short.

If you are going a bit stircrazy and want to meet people worldwide who have the same set of LW/SSC interests, this is for you.

Sponsored by LessWrong Israel and inviting the worldwide LW/SSC community.

The meetup is March 24, 2020, at 19:00 IST, which is 17:00 UTC.

Please sign up at this form by 18:00 IST so we can send you an invitation.

---

(P.S. In coordination with the LW admins, I am posting this duplicate of the original event post, as it is difficult to make non-geographical event posts.)
What information, apart from the connectome, is necessary to simulate a brain?
by Richard_Ngo — 2020-03-20T02:03:15.494Z

Knowing a brain's connectome tells you which neurons can pass signals to other neurons, but presumably neurons differ in how they process that information. What are the most important things to know about an individual neuron in order to predict how it would fire given certain input signals? And to what extent is that information preserved when a brain is cryonically stored?
Sarah Constantin: Oxygen Supplementation 101
by habryka — 2020-03-20T01:00:16.453Z
Link: https://srconstantin.github.io/2020/03/19/oxygen-supplementation-101.html

New post by Sarah on oxygen supplementation. Excerpt:

COVID-19 causes shortness of breath and in severe cases requires artificial ventilation. There is a shortage of mechanical ventilators in hospitals, and a shortage of medical personnel to treat patients with severe COVID-19, so there’s widespread interest in contributing to open source ventilation projects. For these efforts to be effective, though, we need to understand what COVID-19 patients need in terms of ventilators and other supplemental oxygen sources.

COVID-19 Symptoms and Clinical Guidelines

Most patients who go to a hospital for COVID-19 have pneumonia or infection of the lungs, which is visible on a chest X-ray. A large fraction (41.3%) receive supplemental oxygen therapy; a smaller fraction (5%) needed to be admitted to the ICU, and 6.1% needed mechanical ventilation.[1]

ARDS Severe cases of COVID-19 result in developing Acute Respiratory Distress Syndrome (ARDS). Fluid builds up in the lungs; the lungs may collapse; blood oxygen drops; and mechanical ventilation is required. Merely providing air with a higher oxygen content than room air isn’t enough; pressure needs to be administered to keep the alveoli open.
Thinking About Filtered Evidence Is (Very!) Hard
by abramdemski — 2020-03-19T23:20:05.562Z

The content of this post would not exist if not for conversations with Zack Davis, and owes something to conversations with Sam Eisenstat.

There's been some talk about filtered evidence recently. I want to make a mathematical observation which causes some trouble for the Bayesian treatment of filtered evidence. [OK, when I started writing this post, it was "recently". It's been on the back burner for a while.]

This is also a continuation of the line of research about trolling mathematicians, and hence, relevant to logical uncertainty.

I'm going to be making a mathematical argument, but, I'm going to keep things rather informal. I think this increases the clarity of the argument for most readers. I'll make some comments on proper formalization at the end.

Alright, here's my argument.

According to the Bayesian treatment of filtered evidence, you need to update on the fact that the fact was presented to you, rather than the raw fact. This involves reasoning about the algorithm which decided which facts to show you. The point I want to make is that this can be incredibly computationally difficult, even if the algorithm is so simple that you can predict what it will say next. IE, I don't need to rely on anything like "humans are too complex for humans to really treat as well-specified evidence-filtering algorithms".

For my result, we imagine that a Bayesian reasoner (the "listener") is listening to a series of statements made by another agent (the "speaker").

First, I need to establish some terminology:

Assumption 1. A listener will be said to have a rich hypothesis space if the listener assigns some probability to the speaker enumerating any computably enumerable set of statements.

The intuition behind this assumption is supposed to be: due to computational limitations, the listener may need to restrict to some set H of easily computed hypotheses; for example, the hypotheses might be poly-time or even log-poly. This prevents hypotheses such as "the speaker is giving us the bits of a halting oracle in order", as well as "the speaker has a little more processing power than the listener". However, the hypothesis space is not so restricted as to limit the world to being a finite-state machine. The listener can imagine the speaker proving complicated theorems, so long as it is done ...
March 18th: Daily Coronavirus Links
by habryka — 2020-03-19T22:20:27.217Z

As part of the LessWrong Coronavirus Link Database, Ben, Elizabeth and I are publishing daily update posts 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 top links that we added yesterday (March 18th), by topic.

Aggregators

Aggregation of PubMed C19 papers

Collection of every academic paper (including preprints) submitted to pubmed about coronavirus

Dashboards

Florida Health Department's Case Map

A comprehensive and detailed dashboard on the COVID-19 statistics in Florida (Gender, Age, County), people tested, cases monitored etc

Everyday Life

A group house describes their precautions and plans

Medical System

Interactive model: when will US states run out of hospital beds

This model attempts to determine at what point hospital beds will be filled by COVID-19 patients and hospitals will be above capacity. Uses hospital beds, not ICU beds or ventilators

Testing labs worried about basic supply shortages

Commercial labs are gearing up for a huge testing effort, but warn that they'll quickly run out of basic supplies like cotton swabs

Progression/Outcome

C19 can sicken children

If you survey enough people (denominator unclear), you will find children with moderate and even severe symptoms

Science

COVID-19 may kill some through cytokine storm

Accumulating evidence suggests that a subgroup of patients with severe COVID-19 might have a cytokine storm syndrome. They recommend identification and treatment of hyperinflammation using existing, approved therapies with proven safety profiles to address the immediate need to reduce the rising mortality.

Biologist-targeted intro to CVs in general

An overview of the coronavirus family, including physical form, pathogenicity, and epidemiology

Slightly more technical biologist-targeted intro

An overview of the coronavirus family, including physical form, pathogenicity, and epidemiology

Spread & Prevention

Twitter: Exposure dose matters

Immune response starts as soon as you're infected, but damage is a function of dose. So if your infection starts small, you will have an immune response at a lower level of infection

Full Database Link
Alignment as Translation
by johnswentworth — 2020-03-19T21:40:01.266Z

Technology Changes Constraints argues that economic constraints are usually modular with respect to technology changes - so for reasoning about technology changes, it’s useful to cast them in terms of economic constraints. Two constraints we’ll talk about here:

Compute - flops, memory, etc.
Information - sensors, data, etc.

Thanks to ongoing technology changes, both of these constraints are becoming more and more slack over time - compute and information are both increasingly abundant and cheap.

Immediate question: what happens in the limit as the prices of both compute and information go to zero?

Essentially, we get omniscience: our software has access to a perfect, microscopically-detailed model of the real world. Computers have the memory and processing capability to run arbitrary queries on that model, and predictions are near-perfectly accurate (modulo quantum noise). This limit applies even without AGI - as compute and information become more abundant, our software approaches omniscience, even limiting ourselves to special-purpose reasoning algorithms.

Of course, AGI would presumably be closer to omniscience than non-AGI algorithms, at the same level of compute/information. It would be able to more accurately predict more things which aren’t directly observable via available sensors, and it would be able to run larger queries with the same amount of compute. (How much closer to omniscience an AGI would get is an open question, but it would at least not be any worse in a big-O sense.)

Next question: as compute and information constraints slacken, which constraints become taut? What new bottlenecks appear, for problems which were previously bottlenecked on compute/information?

To put it differently: if our software can run arbitrary queries on an accurate, arbitrarily precise low-level model of the physical world, what else do we need in order to get value out of that capability?

Well, mainly we need some way to specify what it is that we want. We need an interface.

Our highly accurate low-level world model can tell us anything about the physical world, but the things-we-want are generally more abstract than molecules/atoms/fields. Our software can have arbitrarily precise knowledge and predictive power on physical observables, but it still won’t have any notion that air-pressure-oscillations which sound like the word “cat”...
Cost of a COVID-19 test that uses shotgun RNA sequencing?
by ChristianKl — 2020-03-19T21:33:42.485Z

We seem to have sub-1000 Euro DNA sequencing. From my reading an emergency room visit in the US can cost over 1000 Euro for a person who thinks they have COVID-19. How expensive would it be do to shutgun RNA sequencing the way we use nucliodtide sequencing for DNA when we want to diagnosize RNA viruses like SARS-COV-2?
My Bet Log
by philh — 2020-03-19T21:10:00.929Z

I occasionally make bets about future events. I think I probably should do that more often than I currently do. Given that, I think it's good practice to have a public record of the bets I've made and their outcomes, when available.

I'll try to keep this updated going forward, if I continue to make bets. (But only on my original blog, I won't copy the edits over to LW.) Currently I'm down £72.46 with one win and one loss.

(This has nothing to do with the matched betting that I previously wrote about. There I was earning money from sign-up bonuses. Here I'm trying to earn money by being better at predicting the future than other people.)

In order of date I made the bet:

Undecided: NO on Trump leaving before the end of his first term.

I placed this bet on 20-Oct-2019, on Betfair, after a friend said on Facebook that the odds seemed very favorable to him. The odds at the time were 1.3, giving an implied probability of ((1.3 - 1) / 1.3 = 30%) that he'd leave. I bet £50 against this, giving me £15 profit if he doesn't. (Minus commission, so £14.25.) As of 19-Mar-2020 the odds are 1.12, for an implied probability of 11% that he'll leave. (I could cash out now, taking my £50 back immediately and £7.56 minus commission when the market closes[1]. I'm not inclined to do that.)

I lost: NO on a large increase in working from home.

LessWrong user Liron said:

I also bet more than 50% chance that within 3 years at least one of {Google, Microsoft, Facebook, Amazon} will give more than 50% of their software engineers the ability to work from home for at least 80% of their workdays.

I took him up on this for $100 each. We confirmed on 02-Jan-2020. I don't think I'd heard the term "coronavirus" at the time.

This cost me $100 (£92.69 over Paypal, which I think included £2.99 transaction fee). But I got a bunch of LW karma for it. Swings and roundabouts.

Undecided: YES on someone contracting Covid-19.

In a Telegram group chat I'm in, I bet another member €30 each that at least one person in the chat would contract Covid-19 by 28-Feb-2021. (We made the bet on 28-Feb-2020.)

I wasn't confident of winning at the time, and I'm still not. Confirmed infection rates are lower than I'd anticipated - for example, Hubei has had just over 0.1% of its population confirmed as having had the disease at one point, and Italy just over 0.05%.

I think an ambiguous result is more likely than I used to,

...
How to optimize my time fighting COVID-19?
by Ian David Moss — 2020-03-19T19:15:26.147Z

Hi all, I could use some advice. I care a lot about having a positive impact on the world through my work, and over the past few years, I've tried hard to put myself in a position to be of service in a moment when our institutions are struggling to make effective decisions that carry huge consequences in the face of great uncertainty. And yet now that such a moment has arrived, I find myself feeling incredibly frustrated at how little I am capable of helping, because this crisis seems almost surgically designed to immobilize parents of small children (of which I have two). We are all healthy and safe for the time being, but with no third-party caretakers to lean on I am lucky if I can manage even three hours of concentrated work time a day, and that is with my wife still on maternity leave from her job. In addition, while I have access to several meaningful assets (see below), I don't have a lot of relevant domain expertise or connections to public health decision-makers. So I am struggling both with very limited time and bandwidth to work on this and a lack of clarity around how best to prioritize the time I do have.

Here are some assets I am theoretically able to bring to the table:

General intelligence and strong strategic thinking capabilities
Direct or second-degree connections to a wide network of decision-makers at important institutions, especially among US foundations
Expertise in synthesizing research (with the caveat that my knowledge of biomedical research is limited)
Expertise in coaching or otherwise assisting teams to integrate evidence into their decision-making
Expertise in modeling risk and policy decisions
A prominent voice in a small community of do-gooding young adults with time and smarts on their hands

I would welcome any thoughts or suggestions relating to the following:

How to think about balancing my responsibility to the world (huge scope, but widely distributed burden of care) against my responsibility to my children (tiny scope, but burden of care almost entirely concentrated on me and my wife)
Strategies to create more time for work without harming my kids' health, mental wellbeing, or socio-emotional development, particularly my adult-attention-craving 5-year-old
Strategies to mobilize the communities where I have credibility in ways that are extremely time-efficient and likely to lead to good outcomes
Problems that are

...
Robin Hanson on whether governments can squash COVID-19
by DanielFilan — 2020-03-19T18:23:57.574Z
Link: http://www.overcomingbias.com/2020/03/do-you-feel-lucky-punk.html

Summary: Hanson argues that Western governments are unlikely to be competent enough to both squash COVID-19 and prevent new cases from entering from neighbouring lax countries. Final two paragraphs:

Before we all jump off this cliff together, can we at least collect and publish some honest estimates of our chances of success? Such as perhaps via conditional betting markets? If you aren’t willing to exactly copy the whole China policy, or have them manage it, how serious could you really be about succeess?

Look, this is like starting a war. Its not enough to ask “would it be nice to win such a war”, we need to ask “can we actually win?” Don’t start what you can’t finish.
Is the Covid-19 crisis a good time for x-risk outreach?
by Adam Zerner — 2020-03-19T16:14:45.344Z

With what's happening with the coronavirus, I'd think that people would be particularly receptive to the ideas that:

1) We need to be prepared for long term risks.

2) Things with exponential growth are super scary.

3) We should trust the professionals who predict these sorts of things.

I wouldn't expect anyone to be willing to open their wallets right now, but it could be a good time to "plant the seed".
North Korea and COVID-19
by jmh — 2020-03-19T15:51:48.428Z

North Korea has still never publicly acknowledged any infections though most believe there are many. Some reports are indicating a massive problem for the regime.

China seems to have resumed returning North Koreans in China to their home county and cutting off further interaction with the country. That was attributed to fear of reigniting the outbreak.

Many countries have maintained both diplomatic ties with the NK, and allowed significant travel and trade between the countries despite UN or US sanctions.

Will one of the fall outs from the pandemic be near total isolation for that country if it continues on the path it currently is on? That seems reasonable -- and would seem to imply a very high cost in human life within the regime.
Covid-19 Points of Leverage, Travel Bans and Eradication
by Roko — 2020-03-19T09:08:28.846Z

Covid-19 has become a major topic for discussion with talk about many different interventions and ideas that might help, from 3-D printing parts for respirators to drafting medical students into hospitals to thorough hand-washing procedures.

However as rationalists we should be asking which actions have the highest expected utility, not which actions have some positive utility. In an exponentially growing process, the actions with the highest expected utility are those actions which intervene early in the process, and actions like drafting medical students which intervene late in the process when the disease has already grown to a huge size are "nice to have" but by that point most of the damage has been done.

Proper and Prompt Travel Bans do Work

As early as January 26th, I called for cancellation of flights to limit the spread of covid-19; there was some pushback based on the idea that travel restrictions don't work which upon closer examination was actually the idea that late or half-hearted travel restrictions don't work:

During the height of the SARS outbreak in 2003, he had a colleague who wanted to return to the UK from Toronto, one of the cities most affected by the virus. So she caught a domestic flight from Toronto to Vancouver, then boarded a flight to London. “When she arrived at Heathrow [airport] and authorities asked her, ‘Have you been to Toronto,’ she said no and walked right through.”

A policy that allows people to travel from an infected area to to an uninfected area is not a travel ban. It's containment theater. A real travel ban would be grounding all international flights and stopping passenger trains and boats until the disease had been eradicated or at least very well contained, as well as aggressively tracking down and contact tracing people who slipped through before the lockdown, for example using cellphone data from intelligence agencies. A key point here is that mopping up a small number of cases that slip through is in fact possible.

It would have been expensive to do all this, but the cost of not doing it is that the developed world is now on lockdown, the stock markets have fallen by around 33% and we have about 10,000 deaths at the time of writing. And we have ended up implementing the travel bans anyway!

#Don'tFlattenTheCurve

The optimal strategy to defeat the disease is cur...
Should we build thermometer substitutes?
by RobertM — 2020-03-19T07:43:35.243Z

China and South Korea both take people's temperatures (via non-contact thermometers) in a broad variety of situations. Is testing someone for a fever a useful diagnostic in isolation, without the other parts of their operational workflows, i.e. reverse GPS tracking for contact tracing?

If so, it may be useful to research or brainstorm methods of taking a person's temperature that do not require an actual thermometer. Thermometers appear to be in short supply on Amazon, but it looks like you'd have no trouble getting one on eBay. That said, there maybe not be enough thermometers in stock to implement a testing program where every single place of business has one (or more) to test all of their employees and customers.

My first idea was to use a smartphone camera and attempt to extract some signal from that, but it turns out that not only do many smartphone cameras come with infrared filters to improve image quality, even those that don't still aren't capable of detecting thermal IR.

Can anyone think of any other plausible side-channels by which you might estimate a person's body temperature within sufficient tolerances?