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Comment by jlmorton | Hacker News Reader

We already have lots of data that says this is not true. For instance, on the Diamond Princess, widespread testing of a confined group initially found many asymptomatic infections, but the majority of those turned out to be pre-symptomatic, not asymptomatic.

Longer term follow-up found ~25% of infections were asymptomatic.

In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms. Even limiting our sample to people presenting with severe matching symptoms of COVID-19, we're finding ~20% PCR-positive for SARS-CoV-2.

Beyond that, we also have good evidence that the Basic Reproduction Number is somewhere between 2-3. Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet.

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> In the US, we're now doing significant amounts of testing, but we're still primarily testing only those with severe symptoms

Its not a significant amount of testing if we're only testing those with severe symptoms

Here in SF at least there are scores of people I know who all were sick with a "weird flu" at some point from February to now who would all kill for a test to show that they have COVID immunity. These are people who could potentially go back into society and do more work / enjoy their lives instead of being shuttered inside with anxiety

It is currently _IMPOSSIBLE_ to get any kind of test to prove that

Only way I know to get any COVID19 antibody test is through this study https://clinicaltrials.gov/ct2/show/NCT04334954?term=serosur... and the result may be inconclusive or take months.

This is weird to hear because there are several competing clinics in Phoenix all offering antibody testing.

Go do the Stanford drive-through blood antibody tests. It takes five minutes it’s free and they do it for everybody.

Do you need any kind of doctors order for that or health insurance?

Like how does it work? Would love to go do that

  it’s free and they do it for everybody

Do you have details on how to take advantage of this? Their website says nothing to to that effect:

https://med.stanford.edu/covid19.html

> These are people who could potentially go back into society

Do we know this for sure? I've read that we're seeing re-infections of people who previously had it, but it wasn't clear exactly what was happening.

we don't. he is (perhaps unknowingly) spreading disinformation, but that's really very normal behavior.

the hardest thing about this is finding real information and then accepting it.

Accusing someone of “spreading disinformation”

Is a pretty hard line to take when all the facts are evolving and we’re learning more every day

We're about as confident that people gain long-lasting immunity as we are that it's a simple respiratory tract infection. It's not beyond question, but to raise the questions without mentioning that we're pretty confident in the consensus answers is either misinformed or misleading.

For some people any statement which is not their preferred taste of doom, disaster and panic is considered misinformation. The post they are complaining about doesn’t even supply a concrete statement:

> These are people who could potentially go back into society

Nobody knows if they could go back or not but the statement that they might is somehow the most dangerous form of misinformation.

The US is doing a significant amount of testing compared to what's available almost anywhere else on the planet. I think Germany is still beating them, but they're basically the only large country that is at this point. Journalists here in the UK have actually been pointing to the US as one of the examples that proves we're the ones failing at testing for a while now.

Where are you getting that data? The 'Our World in Data' site says reporting is inconsistent, but the data they do have shows per-capita Germany, Italy, Belgium, and Austria doing more than the US, and France, the UK, and the Netherlands doing less.

https://ourworldindata.org/grapher/full-list-cumulative-tota...

(I'm using cumulative because the daily numbers are missing for Germany, France, and the Netherlands)

It's certainly possible other countries have passed the US since I last looked, the exact leaderboard does seem to vary depending on things like which country is hitting the biggest roadblocks in their test rollout right now. (Though Italy's lead in total per-capita tests is mainly because they were the first Western country to have their outbreak hit catastrophic levels and they ramped up testing fairly aggressively early on in response to that. I presume their testing wasn't so great prior to the collapse of their healthcare system, since they went from reporting only three cases to disaster alarmingly quickly.)

Are you using some metric other than "per-capita" for tests? I could understand something like "per-positive case", but it's unclear from your comments.

I ask because the data I have shows the US solidly in the middle for the big EU countries over the past month (Germany and France don't show up on the daily graphs)

- Italy started earliest, but the daily per-capita tests have been higher every day except Apr 4: https://ourworldindata.org/grapher/full-list-daily-covid-19-...

- Austria, Czechia, and Portugal have been higher than the US more often than not: https://ourworldindata.org/grapher/full-list-daily-covid-19-...

- Belgium is on par; the UK & the Netherlands are definitely worse: https://ourworldindata.org/grapher/full-list-daily-covid-19-...

It depends on where you draw the line for "large", but the US is really not doing all that great (though it has caught up significantly over the last month): https://www.worldometers.info/coronavirus/

Drawing the line at ~5M inhabitants, the following countries/territories have conducted more tests per million population than the US: The UAE, Norway, Switzerland, Germany, Portugal, Italy, Ireland, Austria, Hong Kong, Australia, Spain, New Zealand, Israel, Czechia, Singapore, Canada, Belgium, South Korea, and Russia.

The U.S. has more resources per capita at its disposal, but if everyone is starting at zero tests, I'd still expect smaller countries to be able to ramp faster relative to their population, and all the countries you've listed are indeed smaller than the U.S.

There's the old adage "nine women can't make a baby in a month". Sometimes there are real-world limits to scaling, and the U.S. does have an incredible amount of tests to create.

Yeah. One big reason I'm not counting small countries (that is, anyone much smaller than Germany) is that there's a limited global supply of pretty much every consumable you need to test for coronavirus, and smaller wealthy countries can get a major boost in per-capita testing by just buying up more of the supply. So there's a whole bunch of smaller countries with really substantial per-capita testing advantages over all the larger ones.

I'm not expecting the US to rise to the lofty levels of the Faeroe Islands, but it seems to me that you're grading on an excessively lenient curve here. Germany is the 19th most populous country in the world, and of the top 19, only 3 are bona fide first world countries (the US, Japan, and Germany) , and even one of the marginal candidates (Russia) is beating the US in tests.

And it's not like Portugal, Italy, Spain, or the Czech Republic are particularly small or particularly wealthy.

Likewise, South Korea reports a fatality rate of about 2%

https://www.worldometers.info/coronavirus/country/south-kore...

Since they have coronavirus relatively under control and have been doing extensive testing and contact tracing for months, it's plausible that they've caught most cases. It's wishful thinking to believe the infection fatality rate is an order of magnitude lower.

It is not plausible they caught most cases.

Here's the result of randomized testing in Iceland, which also has the virus under control and has done even more testing per capita (https://www.nejm.org/doi/full/10.1056/NEJMoa2006100?query=fe...)

Randomized testing was still finding 0.6% of the population (outside those otherwise quarantined already) actively infected. This means even in Iceland, less than half of infections were being caught.

Iceland's CFR right now is 0.74% using deaths/recovered (or if you use an ultimate 20% hospitalization fatality rate, around 0.87%). If they missed half of infections, you get an IFR down to under 0.5%, though I'll admit they are doing better by keeping their most vulnerable population from being infected. (note the low infection rate for people 70+ at https://www.covid.is/data).

So no, not an order of magnitude lower, but 3x lower (0.7%) is looking pretty reasonable. Imperial College's latest estimate is 0.66% for China (https://www.medrxiv.org/content/10.1101/2020.03.09.20033357v...).

The comparison between the two countries is so difficult. The population of Iceland is around 360K, while South Korea is over 51 million (~140x). The population density is in the same order, 3 per Km^2 to 500 per Km^2 respectively (~160x).

Half of Iceland's population lives in the Reykjavik area. The rest are thinly spread out over the country - which of which is still inaccessible due to ice (usually until April/May). Comparing this to a densely populated South Korea is incredibly difficult.

Also, different genetics, different climate, different culture, different population density, different connectedness to China, and a 2 orders of magnitude difference in population size. As a rule of thumb, whenever you want to compare Iceland to another country, you probably shouldn't.

But you just ignored the evidence from the diamond princess?

and meanwhile germany's data points toward a similar conclusion as the south korean data

singapore also has a 1.5% deaths/recovered... and it's been higher in the past if you've been following closely (as high as 2%... question is where have all the new cases been coming from?)

icelands data could easily be skewed if they avoided a nursing home getting infected, given their low number of cases, and even there 1% fatality seems plausible.

An average age of 59 on the Diamond Princess (1.8% CFR) is not representative of the general population. This is a substantially more at-risk group.

Germany and Singapore are also missing many infections. A recent serological study in Germany actually argued for 0.4%.

You are correct that IFR is skewed by who the population is and what interventions are done. But then again, so is the often cited flu benchmark (where we have targeted vaccinations of at-risk groups).

(And age is a huge thing to be aware of skewing the data. e.g. the pediatric IFR from covid is on the order of seasonal flu)

https://www.reddit.com/r/medicine/comments/fyf0yh/megathread... you mean this serological study?

And taiwan is at 1.5% CFR as well?

And still 60 or so unresolved diamond princess cases with ~7 in critical condition?

Yes, I agree it is preliminary and not too much should be drawn off it.

Every country is missing large numbers of cases, so CFR doesn't mean much - randomized testing is what is needed.

Imperial College's paper (linked above which gives a 0.7% population IFR) uses Diamond Princess as an input. The relative risk ratio they give for someone age 70 (mean age on Diamond Princess) is something like 4.5x (IFR ~3%), so you'd natively guess about 80 deaths from the 2,666 passengers.

69 is the mean age of the passengers, the crew was like less than or equal 39 (about 2/3 passengers 1/3 crew I think)

hence why I divided by the passenger, not total, count

whoops, sorry it's 567 infections in passengers with 13 deaths. 2.3% CFR. Expected IFR 3% from Imperial College (17)

That's a much more reasonable interpretation of the available data, although there are still plenty of unknowns here, as sibling comments are pointing out. My interpretations the last week are converging on the same ballpark figures.

I'd just like to point out that this is still a far cry from the wishful thinking a lot of people are putting forth, claiming an IFR of < 0.1%, that 30% of the population have already had the disease and that herd immunity is both imminent and feasible.

These interpretations seem less likely to be true today than they did two weeks ago, and even then they were making assumptions on the optimistic side.

An IFR of 0.5% and a hospitalization rate in the high single digits is still a big frickin problem for society, when the disease has a reproduction number greater than 2 (and in the absence of countermeasures, more likely in the region 2-5).

There is a very economical way to figure out this: test the majority of the US population. Sure, the government will have to spend a few billion dollars, but that would possibly save a few trillion dollars in GDP losses. The fact that people and businesses are not requiring this right now from the government makes my head explode!

Yeah, claiming an IFR of 0.1% is laughable; it would mean everyone in NYC has been infected twice over.

South Korea cases peaked 45 days ago, Iceland peaked 2 weeks ago so their CFR are not directly comparable. Compare Iceland with a South Korea at a similar point post peak infections and the CFR look similar. https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_S... https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_I...

South Korea had 5 deaths per day on both 2/29 and 4/13 that’s a horrible sign.

I'm extrapolating from hospitalization rates for that reason. Otherwise, you'd get a 0.45% CFR in Iceland.

Looking at the raw data, I don't think Korea ever had below 3% using deaths/recoveries. Iceland is at 0.75% right now. Two weeks after peak, Korea was at a crude CFR (deaths/total confirmed) at 1.1%

With a sample size of 8 deaths, 0.45% is easily comparable to 1.1%. We are talking different infected populations, different healthcare systems, and so forth it’s expected to see that kind of a range. The US had what ~19 deaths out a single nursing home.

Also, deaths/recoveries is the least useful metric to compare countries as people with minimal symptoms recover first, again look at the South Korea or China graphs of the number of infected over time.

The Diamond Princess likely had a very atypical (older) population than the general population though.

The CDC is currently estimating an R0 of 5.7, which has likely been repressed by shelter in place orders. But even if it was only 4 before any interventions, there's still a chance there there are closer to 20M cases in the US rather than the 660,000 now.

My point is just that there's still a lot we don't know, and small changes in our understanding could implicate massive changes in the reality on the ground.

Here is a reference for the R0 = 5.7 estimate: https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article

5.7 in Wuhan. That could be true for NYC as well, but is far less likely to be true in the rest of the lower density country. That said I agree with you that infections are likely in the 10M range.

> The Diamond Princess likely had a very atypical (older) population than the general population though.

This would dovetail with the fact that places like sub-Saharan Africa and India haven't been hit very hard yet; they also happen to be _very_ young compared to Western countries.

I don't know if people are aware of this, but there's an increasing suspicion that countries still using the BCG vaccine for tuberculosis might be seeing [1]way lower infection rates.

If that's the case, it'd explain why developed countries are bearing the brunt of the pandemic. A very interesting example of similarly developed countries with comparable (but not equal) populations and population density, but different vaccination regimes are Portugal and Spain. Looking at their [2]respective [3]charts, the differences are stark. A similar difference can be seen between Ecuador and Argentina, even though the Greater Buenos Aires area is very population dense.

If this pans out, following the trends and [4] this map would validate that hypothesis.

[1]https://nypost.com/2020/04/14/coronavirus-death-rates-lower-...

[2]https://www.worldometers.info/coronavirus/country/portugal/

[3]https://www.worldometers.info/coronavirus/country/spain/

[4]http://www.bcgatlas.org/

"there's an increasing suspicion that countries still using the BCG vaccine for tuberculosis might be seeing [1]way lower infection rates"

Obvious to me, perhaps dumb, question - if countries that were slower to change vaccination regimes have some advantage, then wouldn't we see older people in the countries that did change also at an advantage? Yet all reporting seems to be that older people are harder hit.

BCG vaccine requires a booster every few decades, so it becomes less effective over the years. Apart from health issues related to age, this would explain why old people are at higher risk.

Thanks for the 4th link, I couldn't really understand the really sad images and videos coming out of Guayaquil (Ecuador) when comparing them to the rest of South America. Apart from Buenos Aires there are also big metropolises like Sao Paulo or Rio de Janeiro where you couldn't see the same things that were happening in Guayaquil. That vaccination map for South America partly explained the difference for me, at least by correlation.

Yeah, what's happening in Ecuador is incredibly sad. My whole family is in Argentina and I was worried sick for them for a while... who knows, this BCG theory gives me some hope things will be better for them than they are here. Fingers crossed.

The map in [4] suggests that every adult in France would have received the BCG vaccine, as they only stopped in 2017 (and receive it as an infant). There are so many confounding variables here, I don't think anyone should be deriving any evidence by looking at the case charts like that.

I agree. I'm not arguing this is 'fact', just an interesting correlation - until proven anything stronger than that - that would explain why some countries got hit worse than others.

As someone else pointed out, the BCG needs a booster. While growing up I was given the initial one and two boosters. Most countries stopped doing that, which could also explain the effect. There's also the matter of which strain was used to create the vaccine: apparently some strains were better at fighting tuberculosis than others, so the same might apply (if the BCG vaccine actually made a difference) to COVID-19.

Anyway, my objective wasn't to start a conspiracy theory. We already have enough of those going around.

>We already have lots of data that says this is not true... Longer term follow-up found ~25% of infections were asymptomatic.

Based on other available data the severity of the Covid symptoms are dependent on both the length of exposure and total exposure to the virus. A cruise ship with recirculated air likely means prolonged exposure to high concentrations of the virus that won't fit most other patients exposure.

> good evidence that the Basic Reproduction Number is somewhere between 2-3.

May be about double that. Per wiki article, I noticed this a few days ago (https://en.wikipedia.org/wiki/2019%E2%80%9320_outbreak_of_no...)

"Initial estimates of the basic reproduction number (R0) for COVID-19 in January were between 1.4 and 2.5,[381] but a subsequent statistical analysis has concluded that it may be much higher.[382]"

From that link wiki provided (https://wwwnc.cdc.gov/eid/article/26/7/20-0282_article) (edit: and note this is published on the CDC website)

"...we calculated a median R0 value of 5.7 (95% CI 3.8–8.9)"

So this sucks harder then.

For reference, ~19% of people get the flu and are asymptomatic.

Source: https://www.contagionlive.com/news/asymptomatic-influenza-in...

> Study results revealed an overall pooled prevalence for asymptomatic carriers of 19.1% for any type of influenza, 21.0% for influenza A, and 22.7% for influenza A(H1N1). For subclinical carriers, the overall pooled prevalence of was found to be 43.4% for any type of influenza, 42.8% for influenza A, and 39.8% for influenza A(H1N1).

What's "significant amount of testing"? In Santa Clara country, for example, 16585 tests have been done[1], that's less than 1% of the population. I know from personal experience of several people that it's next to impossible to get tested if you don't have very severe symptoms. Positivity rate is 10.8% - over people which are sick enough to get tested.

> Given a seeding of cases in mid-to-late January, even without social distancing measures, it would be unlikely to have 10% of the population infected yet

This sounds like circular logic - how we know it indeed started in January and not before? How do we know how many had it asymptomatically if we didn't test 99% of the population? We're making assumption based on knowledge gathered by select sample of 1% chosen by severity of symptoms - how can we make conclusion about how it works in the rest of the population and what's the dynamics there?

[1] https://www.sccgov.org/sites/covid19/Pages/dashboard.aspx

> This sounds like circular logic - how we know it indeed started in January and not before?

Indeed, without serological testing, we're necessarily making some assumptions. But there's other evidence that points this way, too.

Genetic analysis based on samples from around China and the world point to a single index patient in Hubei Province around late November. China's case tracing has not gotten to an index patient, but it appears to be pretty close, and also points to an initial case around the same time.

If there was a single case in late November, then we'd expect a few hundred cases by January. Some number of these will have traveled, but many would not.

While the US clearly had major blind spots in testing, we were explicitly looking for symptomatic cases from China. The first detected case was Jan 21. There may have been a few earlier, but genetic analysis of cases in Washington point to an index patient in the Seattle area around that time.

If you already have severe symptoms the PCR test from a throat sample is likely to give a false negative.

The BPR is estimated from the known cases, so it cannot tell you anything about a hypothetical large number of unknown cases.

Antibody tests in a recent German study of households gave 15% infection rate.

It wasn't a study of representative German households, but just those in a Gangelt. A small town that was basically the ground zero for the epidemic in Germany. Those numbers do not generalize to Germany as a whole, let alone other countries.

Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.

It does generalize to my point, because we're talking about the basic reproduction number of the virus. It is not supposed to vary dramatically across populations.

If COVID-19 can spread to 15% of that particular population within that timeframe, and the estimate of a basic reproduction number of 2-3 predicts that this is not possible, then the estimate must be wrong.

> Also, the particular antibody tests they used appears to have a much higher FP rate than they claimed. Another study found 4% FPs rather than <1% like the press release for the Gangelt testing claimed.

Perhaps, but that doesn't put much of a dent into the results.

R0 isn't a fundamental constant, but just an estimated average. It's affected both by human behavior and random chance. In this case, the town had a very early superspreader event, which shifted them far ahead of the curve.

A FP rate that high will make a very significant difference in the results. (How large a difference depends on whether the 15% is a raw number or if it's been adjusted based on the expected test specificity and sensitivity. One would hope nobody would just report the raw numbers. But since all we've gotten from this study is basically a press release, expecting scientific rigor seems ill advised.)

It's worth noting that the German study in Gangelt was done because it was considered a hot-spot - this wasn't an attempt to estimate the infection rate across the country. It does however demonstrate that even in places where lots of people have had it, herd immunity still looks a long way off.

It is worth noting indeed.

However, if we apply the estimated mortality rate (0.37%) based on that to 11500 deaths in hot-spot New York, it would amount to over 3 million cases, again roughly 15% of the population.

Now perhaps Germans are so much healthier and their healthcare is so much better, making their real mortality rate so much lower. It's all speculation at this point, either way.

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