Iceland's COVID-19 random sampling results: C19 similar to Influenza

post by jacob_cannell · 2020-03-28T18:26:00.903Z · score: 0 (16 votes) · LW · GW · 44 comments

EDIT: updated with wider estimates to reflect potential sample bias

deCODE Genetics has tested a random-ish sample of about ~5K Icelanders for COVID-19 and about 0.9% tested positive, which naively indicates ~3K true infections in a population of ~330K.

However, if we consider that the volunteer based sample is perhaps biased (the article suggests they would control for this but doesn't describe if/how), that suggests an estimate closer to the ~1k confirmed cases - say 2K.

On the other hand, if we consider the potential of false negatives from failed tests for those who already recovered, that suggests a higher range, perhaps up to ~5k. (The PCR test is highly specific, so we can ignore false positives)

Iceland has only 2 deaths so far for a naive IFR in the range of 0.04% to 0.2% to (we can probably ignore false negatives for deaths - as they are harder to miss in Iceland). Iceland's cumulative case count is clearly in a linear growth regime (past midpoint of sigmoid). They have 6 patients in ICU (Iceland data), which has about a 30% fatality rate, and 19 in hospital with a 10% fatality rate so we can estimate the future total death count in the 2 to 8 range.

This results in a mean predicted IFR of 0.17% (6/3500)and a range of 0.04% to 0.4% (2/5k to 8/2k), similar to influenza but potentially a bit (2x) higher. The uncertainty range will eventually tighten as we know more about survival in their current hospitalizations.

This agrees with the Diamond Princess data which rules out IFR much higher than influenza. (see my analysis here, or a more detailed analysis here) In that same post I also arrived at a similar conclusion by directly estimating under-reporting (the infection/case ratio) by comparing the age structure of confirmed cases to the age structure of the population and assuming uniform or slightly age-dependent attack rates similar to other viruses. That model predicts under-reporting of ~20X or more in the US, so it's not surprising that the under-reporting in Iceland is still in the ~4X range.

The infection hospitalization rate of COVID-19 in Iceland is also in the vicinity of ~1%, similar to influenza.

This also puts bounds on how widespread C19 [LW · GW] can be - with IHR and IFR both similar to influenza, there couldn't be tens of millions of infected in the US as of a few weeks ago or we would be seeing considerably more hospitalizations and deaths than we do.

The 'common cold' is actually caused by over 200 virus strains of different orders, so I wonder if years from now SARS-CoV-2 will be lumped in as a non-influenza virus strain in the 'flu' category.

44 comments

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comment by CellBioGuy · 2020-03-28T20:30:30.276Z · score: 30 (13 votes) · LW(p) · GW(p)

I vehemently disagree with this analysis on multiple levels.

Firstly, Iceland is not 'randomly' testing people. People are signing up to be tested voluntarily. That population is likely to contain a larger fraction of people who have reason to think they were exposed or feel sick. Thus 0.8% is an overestimate of the fraction of the population that has been infected.

Secondly, the asymptomatic period is on average a week or so for those who develop symptoms, with hospitalization often occurring upwards of a week after symptoms, and death often occurring more than 2 weeks after symptoms. With doubling times in a mixing population of less than a week, deaths track infections several doublings before the current number of infections. Indeed, in both China and Italy new confirmed infections only began flattening out 2 weeks after a lockdown, with deaths lagging significantly later. This thing is damn infectious and still expanding, it is not anywhere near a steady state anywhere but East Asia that would allow naive numbers even in Iceland to be meaningful. That naive 0.06% becomes 0.5% if you take into account only 3 doublings, and easily 1% if you accept the sampling is biased.

I take issue with a LOT of things in the linked posts.

Regarding 'only 12 per cent of death certificates have shown a direct causality from coronavirus, while 88 per cent of patients who have died have at least one pre-morbidity ': Trying to make the distinction between 'death with the virus' and 'death from the virus' is just irresponsible and downright stupid at this point, given that the death rate right now in North Italian towns at the center of the situation is >10x the normal death rate per day. The virus is *causing* these people who were living with and managing these pre-morbidities to die. Similarly, even if the average age of deaths is only a year or two below the life expectancy right now, it's not like the human mortality curve is completely rectangular. People routinely die a decade before and a decade after the expectancy number. Unless somehow it's ONLY perfectly people who are less than a year from death who are kicked over, which we KNOW is not the case given the death rates among 60somethings and 50somethings and healthy young doctors, you are losing a lot of life years here.

Something on average killing people at the life expectancy is NOT the same as only losing very little life. To take it to an extreme, you could kill EVERYONE above the life expectancy and an equal number of people just below the life expectancy, and have knocked off on average a decade of life. It should also be noted that some all-cause death rates are coming out in North Italy, and the excess deaths over this time last year are 3x the confirmed covid deaths. A lot are being missed.

Not to mention all the people whose lungs are going to be permanently damaged after surviving and other morbidities, which is much less focused in the elderly than the deaths given that the ICU and hospital admissions are rather less focused in the elderly than the deaths are. According to links in the above writings, 0.5% of flu cases in the 20-45 age group result in hospitalization compared to 10% in the over 65 age group, and taking population into account that results in ~7x as many flu over-60 hospitalizations than 20-45. Current American test results, however, have only ~2x the over-65 covid hospitalizations as 20-45 hospitalizations. If hospital capacity is breached, the death rate of younger people could rise drastically as a result. For those who get this, it is NOT just as dangerous as flu.

The linked analysis dismisses hospital overload causing a higher death rate among ICU patients, on the assumption that severity is lower than reported and it just won't happen. But this is happening *right now* in Italy and Spain, and will be starting soon in New York. And data is indicating that surviving ICU stays for this disease are ~3x as long as ICU stays for flu.

comment by jacob_cannell · 2020-03-28T21:58:48.478Z · score: 3 (4 votes) · LW(p) · GW(p)
Firstly, Iceland is not 'randomly' testing people. People are signing up to be tested voluntarily. That population is likely to contain a larger fraction of people who have reason to think they were exposed or feel sick. Thus 0.8% is an overestimate of the fraction of the population that has been infected.

Technically true - and this is why in the earlier version of this on my blog, I used the word 'random-ish'.

Obviously the test is voluntary, but it's also clearly designed to estimate prevalence:

" This effort is intended to gather insight into the actual prevalence of the virus in the community, as most countries are most exclusively testing symptomatic individuals at this time,” said Thorolfur Guðnason, Iceland’s chief epidemiologist to Buzzfeed.

During this time of year less than 10% of the population has symptoms, so if it was a random sampling of only that subset, we would predict at most 400 cases, so we can reject that.

Nonetheless, I think this does justifying widening the prediction of #infections and moving the mean down a bit.

Secondly, the asymptomatic period is on average a week or so for those who develop symptoms, with hospitalization often occurring upwards of a week after symptoms, and death often occurring more than 2 weeks after symptoms. .. .This thing is damn infectious and still expanding, it is not anywhere near a steady state anywhere

Did you actually look at the Iceland data? They entered a linear regime (midpoint of the sigmoid) about 10 days ago, which defeats the brunt of this argument. Additionally the vast majority of the cases were discovered through normal testing after symptoms present, so subtract a week from your timeframe. And finally I already did attempt to predict future deaths based on ICU. I also considered adding another predicted death from the # in hospital now, but it's unclear if that is distinct from ICU or not.

Ultimately though only time will tell, but I find it unlikely they are going to get up to dozens of deaths without also growing case count.

According to links in the above writings, 0.5% of flu cases in the 20-45 age group result in hospitalization compared to 10% in the over 65 age group, and taking population into account that results in ~7x as many flu over-60 hospitalizations than 20-45. Current American test results, however, have ~2x the over-65 covid hospitalizations as 20-45 hospitalizations.

The hospitalization rate that matters is (hosp | infected), not (hosp | tested). You are comparing the estimated (hosp | infected) curve of influenza to the (hosp | tested) curve of COVID-19, which is a unit mismatch. For that comparison to be meaningful you need to first correct for age-specific (tested | infected) ratio.

And data is indicating that surviving ICU stays for this disease are ~3x as long as ICU stays for flu.

Source?

comment by CellBioGuy · 2020-03-28T23:29:17.616Z · score: 7 (4 votes) · LW(p) · GW(p)

I did look at the Iceland data. I divided the NUHI positive tests by the total tests, and saw a very noisy upwards-trending line in the fraction of positive test results.


As for hospitalizations, I was comparing the age distribution of hospitalizations for flu and confirmed covid. I found that the ratio of 20-45:65+ hospitalizations for flu was 1:7, and that the same ratio for covid was 1:2. Assuming a similar age distribution for actual infections, this means a larger fraction of young people is coming down with severe disease.


As for ICU periods, doctors are reporting that many covid patients require a ventilator for 1-2 weeks. https://www.nbcnews.com/health/health-news/what-ventilator-critical-resource-currently-short-supply-n1168641

I am looking for the resource I read yesterday that the typical flu ventilation period was 3-4 days.

comment by jacob_cannell · 2020-03-29T16:51:02.880Z · score: 2 (1 votes) · LW(p) · GW(p)
Assuming a similar age distribution for actual infections, this means a larger fraction of young people is coming down with severe disease.

Disease severity increases with age, and testing probability increases with severity and thus age (in most places). Thus the ratio p(tested | infection) is age skewed and typically much lower for younger ages.

After adjusting by dividing by age dependent p(tested | infection) you can correct that skew and you probably get something more similar to influenza hosp rate curve.

So again you aren't comparing even remotely the same units and it's important to realize that.

comment by jacob_cannell · 2020-03-28T23:59:04.931Z · score: 2 (1 votes) · LW(p) · GW(p)
As for hospitalizations, I was comparing the age distribution of hospitalizations for flu and confirmed covid. I found that the ratio of 20-45:65+ hospitalizations for flu was 1:7, and that the same ratio for covid was 1:2. Assuming a similar age distribution for actual infections, this means a larger fraction of young people is coming down with severe disease.

Age distribution of estimated hospitalizations for flu? or confirmed? (It seems difficult to get the latter) Source?

comment by CellBioGuy · 2020-04-13T23:54:35.293Z · score: 2 (1 votes) · LW(p) · GW(p)

Copypasting myself from another thread:


' New, amazing data from New York, as of April 13.

Hardly an unbiased sample, but of 200+ pregnant women coming into a hospital to give birth that were blanket-tested, 15.3% tested positive.

Of this set of positive tests, only 12% of them were symptomatic on admission, and a further 10% developed symptoms over the course of their 2-day-long stays bringing it to a total of 22% symptomatic upon discharge. Presumably already-symptomatic women were more likely to be in the hospital already.

Doing a little armchair epidemiology. Let's assume that half of the deaths of currently infected people have happened, due to the lockdown extending the doubling time from three days to more than a week. We get:

~8000 deaths * 2 / (15.3% of 8 million) = 1.3% infection to mortality rate.

If we assume that there were more symptomatic women who didn't show up to normal birthing due to going to the hospital for COVID symptoms, we get a lower death rate. If 20% of the total population is infected, we get a 1% mortality rate.

Compare this to what I wrote 21 hours ago, based on serology data from Italy and Germany:

'From this, I estimate that at least 10% and possibly up to 20% of New York City has been infected, given the delay between infections and deaths. (100*8000 = 800,000, out of about 8 million) '

---

Adding here, that if you assume there are people who would have previously tested positive and recovered, it goes down a bit more. Most places that we get good data these days are converging on a 0.5% to a 0.7% mortality rate, so I suspect that's also a contributor.

comment by jacob_cannell · 2020-03-28T23:41:54.061Z · score: 2 (1 votes) · LW(p) · GW(p)
It should also be noted that some all-cause death rates are coming out in North Italy, and the excess deaths over this time last year are 3x the confirmed covid death

Source? This is potentially interesting especially if it's for a large region like all of Italy or North Italy (i've seen models which estimate excess influenza mortality in Italy) - but the smaller the region the more likely it's due to chance or cherry-picking.

comment by Lukas_Gloor · 2020-03-29T00:12:52.268Z · score: 5 (3 votes) · LW(p) · GW(p)

This person has been collecting reports in Italian media and also contact the mayors of Italian district to request the information.

It's not for all of Northern Italy, but it's also not villages either. Those cities or provinces are much more populated than I initially thought (see Stefan Schubert's correction to my comment elsewhere).

comment by Jonathan_Graehl · 2020-03-28T20:06:07.053Z · score: 19 (5 votes) · LW(p) · GW(p)

That Iceland's currently 1% infected as of now doesn't say anything about how infected it would be after a few weeks of no-special-controls measures (comparable to folks' behavior in a regular flu season). This is the beginning of this virus's worldwide course. It's dishonest to compare a snapshot now with the accumulated total of a whole flu sason.

comment by jacob_cannell · 2020-03-28T20:30:00.303Z · score: 4 (2 votes) · LW(p) · GW(p)

Perhaps this isn't clear enough from the title (but should be clear from the post), that the similarity I"m discussing is in terms of outcomes given illness: IFR and IHR.

Absent controls and behavioral changes, I agree that it seems likely that considerably more than 1% of the population would be infected. Seasonal flu infects perhaps 10%. It's clear at this point that C19 is often asymptomatic/mild especially in younger people, and I recall some potential bio explanations like pre-existing partial immunity through cross reactive antigens. On the DP we know about 30% were infected and it could be higher - perhaps 50%, but that population is half retirees. So from this evidence alone my estimate is somewhere between 10% to 50% would be infected absent any behavioral changes.

However social distancing appears to have already be crushing fever prevalence in the US.

comment by dvasya · 2020-03-28T22:22:10.199Z · score: 15 (8 votes) · LW(p) · GW(p)

That's terrible news! It means that on top of the meager coronavirus there's another unidentified disease overcrowding the hospitals, causing respirator shortages all over the world, and threatening to kill millions of people!

comment by jacob_cannell · 2020-03-29T00:21:33.692Z · score: -5 (8 votes) · LW(p) · GW(p)

Source for a virus making threats?

comment by Bucky · 2020-03-28T21:18:31.061Z · score: 10 (5 votes) · LW(p) · GW(p)

What’s your take on the South Korean data?

They were testing thoroughly (30 negative tests for every 1 positive) all the way through their outbreak so either they were useless at choosing who to test (seems unlikely as they got the outbreak under control pretty fast) or they were finding nearly everyone. Their CFR was 1.3%.

comment by CellBioGuy · 2020-03-28T21:28:26.086Z · score: 9 (5 votes) · LW(p) · GW(p)

Yes, if they were missing lots of asymptomatic contagious people, they would not have gotten their outbreak under control. If we assume a few asymptomatic locked-down contacts had false negatives, their numbers are approaching the numbers you would expect given the Diamond Princess data. I cannot see a situation in which there could plausibly be a huge number of missed asymptomatic people given these two data sets...

comment by ryanonthebeach · 2020-03-31T19:48:23.238Z · score: 1 (1 votes) · LW(p) · GW(p)

A simple answer, Masks. They wear them now, we don't

WHO Guidance that it spreads mostly from surfaces may be entirely wrong.

comment by jacob_cannell · 2020-03-28T21:31:20.514Z · score: 0 (2 votes) · LW(p) · GW(p)

South Korea is unusual in that the outbreak there is best understood as two separate outbreaks: an initial outbreak in a strange highly interconnected cult, and then the outbreak in the general population. They ended up testing everyone in the cult, but their testing strategy in the general population seems more limited, similar to other countries. So the testing of several hundred thousand cult members pushed both their CFR and test positive fraction lower than it otherwise would be, and rather obviously skewed their case age structure.

Nonetheless they have tested far less of their population than Iceland (about 5X less as of 3/20 according to ourworldindata), so if the ratio of infections/cases is 4x to 5x in Iceland it seems reasonable that it's 10x to 20x in SK.

comment by Lukas_Gloor · 2020-03-28T23:50:12.470Z · score: 10 (3 votes) · LW(p) · GW(p)
So the testing of several hundred thousand cult members pushed both their CFR and test positive fraction lower than it otherwise would be, and rather obviously skewed their case age structure.

It skewed the age structure toward a younger demographic. Were you aware of this or did you assume that the religious group is skewed toward old people like typical churches? I didn't realize this up until like ten days ago, but the Christian cult was predominantly pretty young people!

Nonetheless they have tested far less of their population than Iceland (about 5X less as of 3/20 according to ourworldindata), so if the ratio of infections/cases is 4x to 5x in Iceland it seems reasonable that it's 10x to 20x in SK.

The reason I don't consider it at all plausible that South Korea missed 80% or more of its cases is because of how quickly and lastingly they were able to gain control over their outbreak.

And about Iceland: Isn't it really very clear that Iceland is weeks behind South Korea, and that Iceland's numbers are therefore unrepresentatively low? For comparison, South Korea's IFR was 0.6% at a point when they had 7,700 confirmed cases. I think this was roughly 20 days ago. So 20 days for South Korea's IFR to go from 0.6% to 1.5% is how long it takes a majority of patients to die if the hospital conditions are favorable enough to give everyone good treatment. There weren't many new confirmed cases in the meantime because the current count is 9,500. So with respect to the IFR Iceland is currently at (0.21%), if Iceland had their outbreak under control, we should expect that IFR to rise by a factor >2.5x. 2.5x is the lower bound because South Korea's IFR was at 0.6% at a time when they already had dozens of deaths; by contrast, Iceland only has two deaths so they are way behind the timeline. (This comes from the effect that once true cases stop growing, the CFR rises up until all the illnesses take their course.) Expecting anything lower than a 4x increase from time delay is unreasonably low. So to make Iceland's reported CFR comparable to South Korea's, we should think of it as 0.84% rather than 0.21%. And then we can think about how many cases went undiagnosed in both countries (but maybe you did factor this in).

In addition, we have to factor in that Iceland doesn't have their outbreak under control. Or do they? I didn't check up on this, but I'd be surprised if they had the outbreak contained. My guess is they caught fewer cases than South Korea! Yes, Iceland did more testing per capita. But South Korea knew where to look! They really managed to get their outbreak under control. It's very impressive and I feel like they're not getting the credit they deserve.

Anyway, assuming Iceland still has community transmission, this would mean that through new testing, new confirmed cases will be added constantly to the total. Those cases will predominantly be recently confirmed cases where not enough time had passed for people to die. This will keep Iceland's reported CFR at a low level for quite a while to come, but this provides basically zero evidence for the actual IFR being low.

UPDATE: I ended up looking up Iceland's numbers, and it seems like they had almost 10% of their total cases confirmed only yesterday. So whether the growth regime is "linear" or not, I think this is definitely not comparable to South Korea's numbers where the growth has been around 1% or 1.5% for several weeks.

comment by jacob_cannell · 2020-03-29T00:10:34.640Z · score: 2 (1 votes) · LW(p) · GW(p)
It skewed the age structure toward a younger demographic. Were you aware of this or did you assume that the religious group is skewed toward old people like typical churches? I didn't realize this up until like ten days ago, but the Christian cult was predominantly pretty young people!

Yes, I should have made this more clear - but it skewed it younger. Or at least that's my explanation for their much higher than expected # cases in younger cohorts vs elsewhere. That should lower their CFR of course.


And about Iceland: Isn't it really very clear that Iceland is weeks behind South Korea, and that Iceland's numbers are therefore unrepresentatively low?

No this isn't clear. Iceland's case count entered a linear regime roughly 2 weeks ago - ie they do seem to have it under control (at least for now). Modeling one country as "X weeks behind" some other country is hazardous at best and also unnecessary as Iceland provides direct graphs on their daily #tests and #positive.

comment by Lukas_Gloor · 2020-03-29T00:35:05.216Z · score: 12 (4 votes) · LW(p) · GW(p)

Edit: changed some numbers slightly after looking things up, to make them more accurate.

Modeling one country as "X weeks behind" some other country is hazardous at best and also unnecessary as Iceland provides direct graphs on their daily #tests and #positive.

I agree that it's tricky to do the modelling correctly, but I feel like you're not engaging with my point properly. I think the following argument I made is watertight:

  • There was a point when South Korea had several deaths (50ish) and thousands of cases (7,700) and their IFR was at 0.6%.
  • That's roughly when they got their outbreak under control. The numbers slowed down tremendously, and 20 days later they are only at 9,500.
  • So in those 20 days, the reported CFR 2.5xed.
  • Iceland's reported CFR never 2.5xed so far.
  • Therefore, they are way behind South Korea's timeline even if we grant the point that Iceland has its outbreak contained (you may be completely right about this, because I didn't follow it EDIT: I don't think you're right about it because Iceland's numbers grew by almost 10% two days ago, which is still a somewhat large portion of new cases!).

The way I see it, this point is only wrong if somehow Iceland going from 1 deaths to 2 deaths is the equivalent stage of the timeline as South Korea's deaths going from 50 to 144 (or whatever the numbers were). That seems highly improbable to me because it would mean that South Korea's outbreak was 50 times larger than Iceland's. That doesn't seem right to me. (Though I guess if I had a strong belief that the hypothesis you're defending is consistent with other data points, then this may not be a knockdown argument by itself? Would you expect South Korea's outbreak to be 50x larger? No need to answer, of course. But if this argument updates you somehow, I'd be curious to hear!)

comment by jacob_cannell · 2020-03-29T01:22:38.173Z · score: 2 (1 votes) · LW(p) · GW(p)

If you look at my estimate I'm already effectively predicting that their CFR will increase via predicting additional deaths. I think it makes more sense to predict future death outcomes in the current cohort of patients we are computing IFR rather than predicting future CFR changes based on how they changed in other countries and then back computing that into IFR.

The CFR can change over time not only because of delays in deaths vs stage of epidemic but also due to changes in testing strategy and or coverage, or even changes in coroner report standards or case counting standards (as happened at least once with china).

In terms of true number of infected, I'm predicting that SK has on the order of 100K to 200K cases and say 4K in Iceland, and I don't find this up to ~50x difference very surprising. Firstly, it's only about an 18 day difference in terms of first seed case at 25% daily growth.

SK's first recorded case was much earlier in Jan 20 vs Feb 28 for Iceland. SK's epidemic exploded quickly in a cult, Iceland's arrived much later when they had the benefit of seeing the pandemic hit other countries - they are just quite different scenarios.

comment by Lukas_Gloor · 2020-03-29T01:53:49.781Z · score: 8 (2 votes) · LW(p) · GW(p)
In terms of true number of infected, I'm predicting that SK has on the order of 100K to 200K cases and say 4K in Iceland, and I don't find this up to ~50x difference very surprising. Firstly, it's only about an 18 day difference in terms of first seed case at 25% daily growth.

I see. BTW our confidence intervals for the IFR have some overlap: 0.4% is my lower bound and your higher bound. :)

comment by CellBioGuy · 2020-03-30T22:45:40.230Z · score: 4 (2 votes) · LW(p) · GW(p)

Of note:

https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30243-7/fulltext

The latest professionals are suspecting a total infection-to-death rate of a normal population (not a cruise ship) of ~0.6%.

comment by jacob_cannell · 2020-03-31T06:05:58.710Z · score: 3 (2 votes) · LW(p) · GW(p)

That's interesting. Over the weekend I wrote a monte carlo simulation for the Iceland data incorporating a bunch of stuff including a lognormal fit to know median and mean time from confirmation to death. Going to write it up, but the TLDR: the posterior assigns most of it's mass to the 0.2 to 0.4 range for reasonable settings. Want to do something similar for Diamond Princess and other places.

I expect the real IFR will vary of course based on age structure, cofactors (air pollution seems to be important, especially in Italy), and of course the rather larger differences in coroner reporting standards across jurisdictions and over time.

You can avoid alot of that by looking for excess mortality - which right now seems null in europe except for in Italy. But Spain has about the same cases and deaths per capita and no excess mortality.

comment by CellBioGuy · 2020-03-28T21:39:48.191Z · score: 2 (3 votes) · LW(p) · GW(p)

This would not be consistent with them having gotten the spread under control and stopped without lockdowns.

comment by Lukas_Gloor · 2020-03-29T00:02:38.503Z · score: 3 (2 votes) · LW(p) · GW(p)

Minor point because I agree with all the other things you said: While it's true that South Korea didn't have a China-style lockdown, I think the behavioral changes at the city level must have been really quite extreme. Perhaps in part also culture-driven rather than government imposed (maybe South Koreans actually followed government recommendations almost perfectly?), but I think it could be overupdating on the evidence to assume that South Korea didn't need some kind of "lockdown" (loosely spoken) to get the situation under control initially. I'm not 100% sure this is what happened, but I heard at least one expert say that people who claim South Korea didn't have a lockdown are being misleading, and that point also seems to make sense based on priors.

comment by CellBioGuy · 2020-03-29T04:34:51.690Z · score: 2 (1 votes) · LW(p) · GW(p)

Point taken!

comment by jacob_cannell · 2020-03-28T22:19:10.963Z · score: 1 (3 votes) · LW(p) · GW(p)

There seems to be good evidence for asymptomatic transmission - you've probably seen those papers, which indicate that tracking and isolating cases doesn't work.

What does seem to work is social distancing.

comment by CellBioGuy · 2020-03-28T23:11:09.080Z · score: 12 (7 votes) · LW(p) · GW(p)

Contact tracing and isolation empirically does work, since places that did them did not need to go into the severe lockdowns that stopped spread elsewhere. It would not empirically work if most people were asymptomatic. Additionally, if most cases were asymptomatic or weakly symptomatic there would be few cases of multiple close contacts becoming ill. These are common. There's even a case study of 45 out of 60 members of a choir all becoming ill at once...


Asymptomatic transmission is definitely happening, both in the period before symptoms appear and in the 20-50% of people who do not show symptoms. Contact tracing catches these people once one of their contacts - that gave it to them OR got it from them - becomes visible and all their contacts are quarantined.


The decline in fevers is probably mostly flu going away, with a lower replication number that requires less distancing to die out.

comment by Lukas_Gloor · 2020-03-29T00:05:20.430Z · score: 7 (4 votes) · LW(p) · GW(p)
Additionally, if most cases were asymptomatic or weakly symptomatic there would be few cases of multiple close contacts becoming ill. These are common.

+1

I think this point is really underappreciated.

comment by avturchin · 2020-03-29T13:13:13.336Z · score: 9 (2 votes) · LW(p) · GW(p)

Interestingly, there were explosions of H1N1 flu in 2009 on cruise ships, but no reports of death clasters on cruise ships. Thus covid is at least 10 times worse.

comment by Jonathan_Graehl · 2020-03-28T19:58:05.301Z · score: 9 (5 votes) · LW(p) · GW(p)

How many times more contagious (if uncontrolled) and critical/fatal (without hospital overcrowding) is it than a typical flu?

Diamond Princess indicates at *least* 2x on both counts IMO. I think it's a bit shady to say that 2x is ' well within the range of uncertainty ' as if that means something.

I hope it's only 2x worse; I believe 5x on contagion and 3x on severity pre-overcrowding.

comment by jacob_cannell · 2020-03-28T20:19:53.240Z · score: 3 (2 votes) · LW(p) · GW(p)

For the contagious part - I guess what really matters is what % of the population it could infect, and how fast that could occur. But most of the world has gone into social isolation, which at least in the US appears to already have been highly successful.

The kinsa thermometer dataset is quite interesting and worthy of it's own post. If you look at places that didn't do much social isolation in time, like Miami, it appears that the answers may be that it causes fevers in about the same % of the population as the flu does, and cycles through the population in perhaps half the time-frame (viruses move through cities faster in general).

comment by jacob_cannell · 2020-03-28T20:11:08.547Z · score: 1 (3 votes) · LW(p) · GW(p)

The ICU admission rate for hospitalizations and the ICU fatality rate are very similar to influenza (links in this post), and those conclusions are from larger datasets than DP.

I disagree that the DP data indicates 2x higher than influenza in either count. My analysis in the post linked above failed to factor in under-reporting (small but still likely given late testing), adjustments for expected deaths and probably had too many deaths in the 70-80 age group. The analysis in this post from Nic Lewis is more detailed and in closer agreement with influenza mortality.

From the current evidence at this point I think a reasonable bayesian should have a log-normal distribution on all-age IFR, but it's surely centered on influenza IFR - something like LogNormalDistribution[-2, 0.5].

comment by CellBioGuy · 2020-03-28T21:45:49.467Z · score: 4 (2 votes) · LW(p) · GW(p)

How can the ICU admission rate be similar to the flu, when fever levels (healtweather.us) in New York are lower than the peak of flu season but they are strapped for space?

comment by jacob_cannell · 2020-03-28T22:24:24.969Z · score: 0 (2 votes) · LW(p) · GW(p)

Are you saying that some significant fraction of NY hospitals are currently overcrowded with C19 patients right now? Or that one hospital is? What is the actual dataset source for "they are strapped for space"?

comment by CellBioGuy · 2020-03-28T23:04:04.327Z · score: 9 (5 votes) · LW(p) · GW(p)

Yes I am. As should anyone actually paying attention.

News reports, which are usually behind reality, indicate >1000 out of ~1800 ICU beds in the city (which normally run at ~80% capacity for literally everything else) are currently occupied by Covid patients and that it is rising at >30% daily.

https://nypost.com/2020/03/28/coronavirus-in-ny-citys-icu-bed-capacity-ranks-in-bottom-quarter-nationally/

Paramedics are scrambling, responding to more calls daily than on 9/11.

https://www.nytimes.com/2020/03/28/nyregion/nyc-coronavirus-ems.html

comment by jacob_cannell · 2020-03-28T23:37:13.513Z · score: 2 (1 votes) · LW(p) · GW(p)

From Govenor Cuomo's briefing:

Everything we do now (procure ventilators etc) is in preparation for possible apex (when curve hits the highest point)
Apex in New York is estimated in 14-21 days from now
172 new ICU admission in the last day, vs. 374  in the preceding day, may indicate a decline in the growth rate

A demand of 1000 ICU beds suggests about 300K infected in NY assuming influenza like IFR of ~0.1% and ICU mortality of ~30%, so this isn't in disagreement. More likely if 1M are infected demand should be for ~3000 ICU beds.

There may or may not be a difference in mean ICU/ventilator length of stay - that isn't something I've looked at yet. According to Cuomo C19 patients need ventilators for 11 to 21 days vs 3 to 4 days for all other causes. This paper indicates 6 to 17 days for H1N1 in 2009.

comment by CellBioGuy · 2020-03-31T19:55:59.901Z · score: 4 (2 votes) · LW(p) · GW(p)

Very first serology data coming out.

164 close contacts tested by PCR and serology. 16/164 of contacts PCR+ & all PCR+ also serology+. Additional 7/164 were serology+ but PCR-. Overall 23/164 close contacts + in at least one test; 10/23 were asymptomatic.


Asymptomatic fraction circa 50%. Upper range of what I thought likely. Not the vast majority at all. Actual death rate in the normal population most likely circa 0.6%.


https://t.co/nPiD6UP1eY?amp=1

comment by jacob_cannell · 2020-03-31T21:08:31.558Z · score: 2 (1 votes) · LW(p) · GW(p)

Interesting - hopefully it's not long until someone publishes a serology random sampling study.

Not surprised at symptomatic fraction of 50% - was already indicated by DP, Iceland, and other data.

One thing that is surprising/mysterious to me is how steady the PCR test positive% has been across space and time. When the sampling is of general populations outside hospitals, it's ~1% in Iceland without changing much over time, and 2% in NBA players and 1% in expats flown home from china.

The test positive fraction for tests conducted by clinics/hospitals in the US and Iceland is steady at about ~10% and hasn't fluctuated greatly over time.

Of course there are some places where it's much higher like 30% on DP, but that's an exceptional environment.

Now the typical PCR test of nasal/throat swab is only accurate for about a week or so after infection, so it's more of a blurred measure of the infection derivative, but still it doesn't look like there's any recent exponential growth - suggesting it was in the past.

comment by romeostevensit · 2020-03-28T20:10:08.436Z · score: 4 (2 votes) · LW(p) · GW(p)

This isn't a random sample afaik. That said, 2x worse than a very bad flu year falls well within the current projections (flu: 8% of population, up to 60k dead, COVID maybe 15-20% infected 100-200k dead). Could also do 3x that though pretty easily.

I'd like to see a model for knock-on deaths from hospital overwhelm.

comment by jacob_cannell · 2020-03-28T20:40:35.981Z · score: 0 (2 votes) · LW(p) · GW(p)

Naively if ICU fatality is ~30%, and we worst-case assume those all become deaths absent ventilators, that suggests about 3X higher deaths sans ventilators. However in reality we would/will probably just quickly produce more ventilators, start sharing ventilators, jury-rigging C-pack machines into ventilators, etc.

comment by romeostevensit · 2020-03-28T22:14:16.978Z · score: 2 (1 votes) · LW(p) · GW(p)

Those are direct effects, but many other people won't receive care or will have care postponed by general capacity overwhelm.

comment by Jonathan_Graehl · 2020-03-28T20:02:26.153Z · score: 4 (2 votes) · LW(p) · GW(p)

If it's very contagious (it is), the damage could easily become 50x current. It's true that as and if we learn outcomes per infection are not as bad as feared, we will relax. While we should be skeptical of hype, we need to act aggressively early on until we know more about how to treat and how important it is to slow or limit the spread.

comment by EngineerDude · 2020-03-31T19:48:17.739Z · score: 1 (1 votes) · LW(p) · GW(p)

Good analysis, close to my calculations of 0.04% - 0.17%(from Iceland data) averaging around 0.1% which is almost perfectly in line with seasonal flu. I actually suspect that coronavirus will in the long run(after a vaccine and treatments/medication) actually be a lot closer to swine flu(0.03%), implying that seasonal flu might be quite a bit worse than Cov2 NOT the other way round as reported thus far by the media. The only mitigating factor I can think of is the shorter incubation period for swine flu which might mean that Cov2 has a little more time to get around the population asymptomatically thus increasing it's transmissibility or R_0.

I also did a crude but interesting analysis based on the symptomatic testing conducted in the States. It turns out that about 16% of all symptomatic people tested have the virus in the US. If we consider the widely accepted figure of ~3 flu like illnesses for every adult per year(more for kids) we can estimate that in the US alone some 990 million flu like infections occur every year. Flu season and similarly "cold" season lasts for about 16 weeks from mid December to mid April where thereafter the regular summer/late spring/early fall rate of the flu virus drops to less than half(0.4 to be exact). Using this information we can work out that for a period of two weeks during flu season some roughly 52 million Americans have some sort of flu-like virus(a lot of whom show no symptoms). Knowing that Cov2 is about 19% as common now as would be other viruses any other year this leaves us with ~9.925 million infections. As of today there have been 3,402 deaths and 3,893 that are critical. Given that the mortality rate of all critical/serious cases is around 27% we can assume that the total death tally will be around 4453 assuming no more spreading occurred as of about a week ago( a big assumption I know, but there is also a lag in testing percentages so I think this is a safe assumption and works for our example). You might ask why I am using a two week interval and well I am assuming that most cases have occurred within that 2 week interval(I did say this was a crude analysis). In any case, if we crunch the numbers this works out to about 0.045% IFR, which is actually surprisingly similar to Iceland and within it's range of 0.04% - 0.17%.


Something interesting to note is that the deCODE tests are done on asymptomatic cases only(according to Kári Stefánsson). This wildly skews the results since as much as 50% of cases are asymptomatic or so mildly symptomatic as to go mostly unnoticed. Which means we could safely double the rate of infection his data reveals...?