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...
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.
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
...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.)
Update: the positions are now filled. See here for the official announcement.
Help wanted: pandemic.metaculus.com project lead
The high interest and proliferation of questions on the novel coronavirus calls for dedicated attention, which led to the formation of pandemic.metaculus.com. 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:
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 jobs@metaculus.com.
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: https://www.washingtonpost.com/health/2020/04/02/coronavirus-facemasks-policyreversal/
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
...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.
(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...
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?
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...
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.
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 https://en.wikipedia.org/wiki/Compartmental_models_in_epidemiology#The_SIR_model .
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 https://www.medrxiv.org/content/10.1101/2020.03.05.20030502v1 (
...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 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."
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.
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).
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.
Incidentally, also strong evidence against it being a lab-strain. It's a wild strain.
Closest related viruses: bats and Malayan pangolins
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)
(Just following the recommendation to move this out of shortform so it can be tagged later.)
More specifically:
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.)
Two facts:
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:
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?
Hypotheses:
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)
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?
https://www.sacbee.com/news/local/health-and-medicine/article241047391.html
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?
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 https://www.quora.com/At-what-temperature-does-the-cold-virus-die/answer/Thomas-Basterfield (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
...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.
An review of Ferguson et al's paper by Nassim Taleb has come out: https://necsi.edu/review-of-ferguson-et-al-impact-of-non-pharmaceutical-interventions
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...
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
Masks help prevent infection in schoolchildren:
In a group of 10,524 Japanese schoolchildren, masks and vaccination decreased the chance of catching
...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.
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.
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
Read the Imperial College COVID-19 Response Team report tonight. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf
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...
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
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
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: https://twitter.com/silviast9/status/1236933818654896129
But I guess skeptics will want a more authoritative source.
Should poly people consider stopping intimate contact (hugs+) at some point? The network structure of polyamorous relationships might make people particularly vulnerable.
[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),...
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):
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
...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?
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
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 reliablerxpharmacy.com 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?
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
...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.
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. "
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.
The one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers. The case fatality rate there was 1.0%, but this was a largely elderly population, in which the death rate from Covid-19 is much higher.
Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%.
John Ioannidis is making an interesting (and reassuring, if true) claim here. Has anyone looked at the demographics and done the compa...
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...
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.
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
...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...
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)
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
...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?
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?
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.
https://trends.google.com/trends/explore?date=today 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...
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.
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
...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.
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: