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I’m not sure what the situation is elsewhere, but I don’t trust the death statistics here in Poland.

Authorities here will be quick to remove a person from the death toll if they can attribute the death to something else than COVID-19, even when the person in question was tested positive [1].

People who have died in quarantine, having had symptoms but never tested, are also not included [2]. For that matter, testing patients with full-developed symptoms is officially outright discouraged [3].

Press sources in Polish:

[1]: https://mobile.twitter.com/MZ_GOV_PL/status/1243090118270947... [2]: https://poznan.wyborcza.pl/poznan/7,36001,25818730,koronawir... [3]: https://dentonet.pl/wytyczne-gis-nie-wystarcza/#gref

There's three classes of countries.

Conscientious testers like South Korea and Germany. These countries have low death/confirmed_case rate and cases are only a small factor from reality.

Disinterested testers such as UK which only tests hospital admissions (and royalty). The case numbers for these countries are completely unreliable and useless. Deaths are probably quite accurate.

Lastly countries that are trying to perform a coverup, or developing countries where there is poor access to healthcare. Both cases and deaths are unreliable and there's nothing you can do about that.

It's the dark zones I really worry about.

A useful heuristic I've formed for anomolous situations (and especially disasters /emergencies / catastrophes) is that it's where there's no signal at all, or where the signal makes. no sense, that you should be most concerened.

After major natural disasters, looking for regions in which there are _no_ reports of damage frequently repressent worst-hit areas -- all comms and monitoring are knocked out.

In the case of pandemic, it's the capacity (and often willingnes) to sense which is lacking: medical infrastructure, personnel, diagnostics, reporting standards and organisations, etc.

First signs will come a month or two in as 1,000s are dropping suddenly dead. Or before, as "patriotic" and tourist cases emerge -- nationals being diagnosed after leaving the country (this occurred in China with SARS giving rise to the sardonic term), or travellers transiting or arriving from the country testing positive, as happened with Italy and Iran recently.

The flip side of that is over counting. I have read (but do not have source handy) that Italy may be over stating the death toll by lumping any death of a covid positive patient into 'covid deaths'. So if you die of a heart attack and are covid positive, its a covid death, even if you were not seriously ill with significant covid type issues (ie, respiratory).

I'm no kind of expert on medical decisions/statistics, but I can see a possible justification for this. The premise of "flatten the curve" is that there's only so much capacity in the medical system, and once it's used up, not just COVID-19 patients, but anyone who needs urgent hospital care, is going to be worse off.

If the situation is bad enough in a place (like Italy) that a heart attack isn't getting its usual level of care due to the COVID epidemic...it seems reasonable to count that as at least a "COVID-related" death.

Exactly. It's a very bad time to get cancer, an organ transplant, a heart problem or trauma needing ICU. The base rate of deaths from those conditions is well known, so in time we'll be able to see which patients died as a side effect of corona (due to being more vulnerable or due to a shortage of medical treatment). Obviously complicated by the lack of road trauma and industrial accidents, and increase in in-home causation due to being off work (and we shouldn't exclude domestic violence, alcoholism, anxiety, suicide, robberies).

> Because dead bodies tend to behave characteristically, are inconvenient both directly and via surviving relations, and present a smaller testing target (about 1% of total cases) as well as representing a full course-of-illness endpoint, these data should be generally more reliable and cross-regionally consistent than confirmed cases. Deaths are, however, lagged by about two weeks.

Completely agree. Just to add another source of differences between countries for this metric: Some countries test post-mortem (Italy) others don't (Germany).

Didn't realize that - that is also a good explanation for why Germany has less deaths per million in published numbers: they just aren't testing everyone that dies.

It's not completely impossible, but it's considered unlikely; people are sometimes tested post mortem (it's simply not a general policy), and people are usually tested before it gets that far.

cite: https://www.theguardian.com/world/2020/mar/22/germany-low-co...

Oooh....

Source on the DE lack of PM Dx?

See my answer to mns in this thread for sources.

Seen, as well as substantive corroboration elsewhere. Very concerning.

Thanks.

Do you have a source for that? Asking as a person living in Germany, I never heard something like that.

I have this info from one of Robert Koch institutes press conferences from a few days ago. If I remember correctly it was claimed by a journalist in the Q and A section and not objected to in the answer from Robert Koch institutes president Lothar H. Wieler.

EDIT: Here is another source in cold print (search for "posthum"): https://www.welt.de/politik/ausland/article206741617/Coronav...

I’m not going to believe that without a good source. Testing in Germany is at 5000,000/week now, so anyone admitted to hospital would definitely be tested. A friend of mine here in Berlin had symptoms. They called and a team came to their place the next morning. One day later, they were called and got the test results (negative).

The explanation for the relatively low fatality rate I’ve heard is simply widespread testing catching many mild cases and relatively young patients because a lot of initial cases at least were linked to ski holidays and carnival events. Personally, I would add the hypothesis that Germans have far fewer interactions with family members across generations than especially Italy, but also the US. No one I know lived with their parents after finishing school. In the US, when Harvard shut down for the semester, the undergrads all went home to family. Here, students tend to live in regular apartments. And even those in student housing live there year-round, instead of vacating them during breaks and heading home.

I believe Austria and some other smaller European countries are also seeing at least similar CFRs, making Germany somewhat less exceptional.

We had a suspicious surprise death in the family 2w ago that the German hospital did not test (early outbreak + sudden death) nor autopsy and we suspect real chance COVID was a secondary factor that merited at least a check. Internal medicine md phd in our family, so no joke. Ok they didn't test, but we were surprised they did not autospy. Sad way to confirm SOP.

For others: In the US, you can ~always request an autopsy.

See my answer to mns in this thread for the sources.

>Some countries test post-mortem (Italy) others don't (Germany).

It's true and misleading at the same time. True: Germany doesn't do post-mortem tests on people not tested before. But at the same time, everyone who dies and has a SARS2-infection is counted as a COVID-death, whether or not they died from the infection.

> True: Germany doesn't do post-mortem tests on people not tested before. But at the same time, everyone who dies and has a SARS2-infection is counted as a COVID-death, whether or not they died from the infection.

But how do you know that they had a SARS-2 infection if you're not testing?

You test them ante-mortem.

> dead bodies [...] data should be generally more reliable

Not to be too heartless towards sick people, but I think deaths is the only data that's really useful. In addition to reliability as you mention, I have no idea if "infected" means "light cough with a fever and the sniffles" or if it means "on a ventilator in a hospital". Deaths and being maimed are permanent and way more significant to me.

(Hopefully you'll forgive my overarching editing in quoting you)

Also note that you can set the plot in the linked page to show deaths. It's just not the default.

There is a similar confounder for deaths: old and multi diseased. Yes you may know the body count with corona but you do not know the body count due to corona.

Nonetheless, dead + coronavirus symptoms + positive coronavirus test is a pretty objective way of measuring things. People who will end up dead are more likely to be tested, so it’s also a more complete data set.

Some people would have died anyway of the existing condition they are having. An interesting question is how much their life expectancy had been affected by having also caught the coronavirus.

Here is one calculation that estimates the Equal Value Life Year Gained as 15 years. Then, if we do nothing to mitigate the pandemic and 1 out of 200 people die, then the average person looses 27 days. https://www.forbes.com/sites/theapothecary/2020/03/27/how-ec...

This article says it's 7.8 years on average and up to 13.26 million QALYs are at stake in the US. So it's expected that life expectancy for the whole population will decline by at most 14 days due to Covid 19. https://www.nationalreview.com/corner/another-covid-cost-ben...

"if we do nothing to mitigate the pandemic and 1 out of 200 people die,"

Where does that figure come from?

Edit: also, I think 1 in 200 is very, very roughly 5-10 times all other infectious diseases in a normal year. So maybe that would provide perspective.

Let me rephrase it: If governments does nothing, 1 out of 200 people will die.

This study expects 510,000 people to die in the UK (depending on the R0 value) and 2200000 in the US. That's 1 in 135. https://www.imperial.ac.uk/media/imperial-college/medicine/s...

It will be between 1 in 200 and 1 in 100.

At population scales, anomalous excess mortality can be detected and shown actuarially, based on expected mortality rates.

Which raises another key point: in an epidemic, it's the population at large which is affected and diseased. Individual assessments (or treatment) are often of limited use or applicability.

I'm not sure if we will be able to separate the confounding factors such as economic impact at the population level. Do you have an idea how this can be done?

I have seen a few studies using this method to look at excess mortality during the great recession [1],[2], but there wasn't a pandemic at the same time.

https://www.thelancet.com/journals/lancet/article/PIIS0140-6...

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3070776/

To a certain extent the distinction is moot.

Deaths directly from an infectious agent, or due to society-wide institutional impacts ... are still deaths, and would have, at least in a statistical sense, have been avoided without the epidemic. Specific mechanism differs, but the ultimate avoidance measure is the same: avoid pandemic situations, as a society.

Don't forget the other direction: the people who die due to the shortage of ICU beds. There will be uninfected people who die that in normal times would have survived.

Only the excess deaths will allow us to have a true comparison, but sadly we only get those long after.

Those are confounded too by the reduction in other deaths such as traffic related ones.

Why is it a confounder? If people have less traffic accidents due to staying at home, that makes the virus a little less destructive in terms of lives (just remember to account for the economic cost).

Because you won't be able to break out Covid-19 caused deaths from the aggregate.

I disagree, as noted elsewhere in this thread. Pandemic effects should be consider society-wide. Specific causal and medical or other mechanisms will differ, but it's the net effect which matters.

what about “number of people hospitalised with flu-like symptoms” possibly adding “not provably unrelated to coronavirus” (i.e. untested people get included, even those with flu get tested included unless it's proved they don't have both)

not every country has comparable death handling, but you can't hide a person on a respirator.

(alas, i guess it's not widely reported)

Flu, and numerous other infectuous diseases, are independently testable. Within reasonable error bounds, COVID-19 is "respiratory disease. not otherwise indicated", or "ideopathic pneumonia". Diagnosis by exclusion is nonideal, but often accepted, at least for other conditions.

"Infected" means exposed to and replicating the SARS-COV-2 virus. Antigen or antibody tests should be able to detect this (subject to false positive/negative rates), if systematically and comprehensively administered.

The tests are not being administered, for numerous reasons, chiefly availability.

Infected is obviously "tested positive". I'm not sure how that's any different whether they have a light cough or they're dead? They still tested positive for covid 19

I am not a fan of these semi-log plots of total cases. They don't really tell much.

If the question is "how bad it is?", than the linear plot makes more sense. Going from 1000 deaths to 10000 is 10 times as bad as going from 100 to 1000, it shouldn't be shown in the same interval if that's the info you are conveying.

If the question is "are thing improving?" it is not that helpful either. Here, what we want to know is if the growth is exponential or not, and there is no obvious feature in the plot telling us that. The plots of South Korea and Italy have similar shapes, one just looks more stretched out than the other, and yet, they describe completely different situations.

The only case when a semi-log plot can be useful is when it shows a straight line, meaning an uncontrolled exponential growth. But such a phase never lasts, it can't, even in a worst case scenario.

The point is to see if it's flattening out or not over time. Clearly for the USA it isn't. Exponential curves start getting useless after a while from a trendline perspective .

>Because dead bodies tend to behave characteristically, are inconvenient both directly and via surviving relations, and present a smaller testing target (about 1% of total cases) as well as representing a full course-of-illness endpoint, these data should be generally more reliable and cross-regionally consistent than confirmed cases.

Are you accounting for healthcare system overload? The case fatality rate in northern Italy is probably going to be very different than in Japan for example.

First, the relevant comparison is the relative reliability of deaths vs. confirmed cases data.

That clarified: overloaded healthcare would probably exacerbate this. Dead bodies don't require medical treatment, though registration as a COVID casualty requires post mortem testing. Live infecteds might well be turned away from facilities, choose not to seek treatment, or expire before receiving it. All of which contributes to case undercounts.

The difference in overall CFR would likely be at best a modest multiple of best-case treatment -- admissions are stil only a fairly small fraction (4-20% figures that I've seen, lowest in Iceland) of total infecteds.

Italy's nominal CFR is still 55%, and has ranged as high as 75%. (https://www.worldometers.info/coronavirus/country/italy/) That suggests to me (and far more qualified commentators) a huge undercount of actual total cases.

At 1% mortality with 10,000 dead, Italy would have had 1 million cases two weeks ago. The current confirmed total is 92,000, an undercount by a factor of 10, even discounting the time lag. We might assume Italy's CFR is higher than elsewhere, but pick even fairly high values and testing still seems higghly inadequate. Two weeks ago, total confirmed cases were 21,000. A fifty-percent mortality is not credible.

TL;DR: Deaths are a vastly more reliable, though still approximate and undercounted metric, than confirmed cases.

Something feels wrong here. But I am just a clueless programmer and armchair expert. A thing I see is that you shouldn't use CFR this way because the CFR is only known after the end of the pandemic. Hoever I agree with the conclusion that the number of cases is not reliable, but not with the way you deduct this.

If I'm understanding you, that's largely the point I'm making. Italy's apparent anomolously high CFR is all but certainly a measurement artefact and not a clinical actual ground truth.

The deviation itself, though, points to insufficient monitoring rather than exceptional lethality. You cannot just look at apparent CFR and without question.

One valuable property of plotting deaths (total) vs. deaths (last week), or cases vs. cases, is that the shape of the plot is immune to consistent distortions in reporting; if country A is consistently down-playing the death rate by x%, the slope will still be the same, although the position along the line will be x% smaller in both axis. If the distortion is changed, to y%, then there will be a departure from the common slope, but if the real rate has not changed the graph will return to a positive (but shallower) slope after a couple of weeks.

And indeed, every country but South Korea and Japan show pretty much the same pattern. South Korea had a pretty vigorous response, but Japan? Perhaps reporting standards in Japan keep changing?

Hm, Iran deaths look funny, too. They suddenly leveled off at 900/wk (linear chart). Ah... cases log chart shows a short deviation, then resuming slope (even steeper!) So, reporting change?

[Edit: SK also outlier, Iran, added cases vs. cases]

This looks like an actual log-log plot, but of new cases vs existing cases. Not a super useful view except to point out that yes, growth rate tends to be proportional to infection count (pure exponential growth) until something majorly changes.

A linear plot would tell exactly the same story, just be compressed too far towards the origin to be very readable.

Yes, I realised that and edited my comment, apparently before you'd completed yours.

The view is useful in that it makes departure from the exponential growth trend blindingly clear. A bit fiddly trying to work out timelines however.

These are fascinating. But all of this data seems to indicate to me that this virus has a far longer incubation period than what I was led to believe. Right, how can it be that it continues to spread at the same rate weeks into quarantine?

It’s likely due to a lack of testing.

What I heard was an average of 5 day incubation period (rarely up to 2 weeks). But early symptoms are often things like slight sore throat or mild fever or a slight cough, which might be easily confused for other respiratory viruses or seasonal allergies. People with minor symptoms are told to stay home and not tested in many places.

People often start experiencing more serious symptoms 1 or 1.5 weeks after symptom onset. Then getting a test result can take another 0.5–1.5 weeks.

Deaths are typically not occurring until something like 3–4 weeks after initial infection. Then in some cases data about deaths can take at least a few days to be aggregated in regional/national statistics.

So any public health measure instituted today will take at least 2 weeks to show up in the data about number of cases, and at least 3 weeks to show up in the data about deaths. Full effect of public health interventions is probably not seen in the data until a month or more later.

And keep in mind that public health interventions are only as effective as the public’s willingness to follow them. If someone is getting their news from a source which repeatedly claims that this is all overhyped and there’s nothing to worry about, they might not take appropriate personal action.

Most mainstream news has moved away from their earlier “we should more worried about the flu” consensus they were pushing during the democratic primaries.

A possible (I think probable) explanation is that we're seeing in this graph a ramp in testing, not a ramp in infection.

If we were to just randomly select individuals for infection and antibody s teeming, we could generate a clearer picture of this. Absent that, look at total death figures 14 days later for a decent proxy...

Among information I've heard:

- Testing ramp catching up with community spread. A US congressional source was saying a week ago that the disease waas spreading faster than testing. Likely still the case.

- Entrenched community outbreak and transmission.

- High-density regions with rapid transmission. The US east coast has leapfrogged early outbreaks in WA and CA (though these also likely have undertesting). New York State (overwhelmingly NYC) alone would be the world's 6th largest outbreak.

- Many regions remain in denial, have grossly inadequate response, or are mishandling the outbreak. In the US, Florida, Alabama, and Mississippi are saying and doing innane things, even by standards set at the national level. Mexico is in fiull denial. Brazil's mafia are imposing quarantines where the. government won't. And rumblings (see Tyler Cowan) are that Japan may come unglued again.

The virus does spread asymptomatically, and many (mostly younger) patients can carry the infection with mild or no symptoms, but infecting others. See: https://www.worldometers.info/coronavirus/coronavirus-incuba...

Deaths lag by three weeks.

...the China National Health Commission reported the details of the first 17 deaths up to 24 pm 22 Jan 2020. A study of these cases found that the median days from first symptom to death were 14 (range 6-41) days, and tended to be shorter among people of 70 year old or above (11.5 [range 6-19] days) than those with ages below 70 year old (20 [range 10-41] days.[6]

https://www.worldometers.info/coronavirus/coronavirus-death-...

You are missing the 6 day incubation period.

Fair point.

Not to dispute, but to note the critical importance of definitions and measurement ability, this raises a few other points:

- Are we comparing and rating deaths vs. cases on time of viable exposure or first clinically detectable presentation?

- What is the earliest an infection is reliably detectable?

- At what point during incubation is a personnthemselves infectuous?

Probably others.

I'm pretty certain based on past experiences that these discussions are being had among medical and epidemiological circles.

At what point though is the question one of failing to achieve potentially complete coverage versus fundamental limits of detection?

That said, deaths lagging exposures by ~20 days is valid. Thank you.