Coronavirus Update IV — Take A Deep Breath — If You Still Can

Apologies for the duplicate email! I hit the wrong button yesterday and published the incomplete update meant for today.

All the good stuff, caveats, and explanations are linked, some in Update III, and the most important in Update II, so go there first before complaining. Or skip to the bottom for the latest model.

Personal update: I haven’t seen any panic in NYC. Toilet paper still on shelves. On a flight to Florida on the weekend was one passenger wearing surgical gloves, and a mother insisting on wiping down everything her kids would come into contact with.

Condoms are selling out, because why? Because people are putting them on their fingers to avoid coronavirus. And this.

Panicked yet?

“Don’t joke, Briggs. You don’t understand. It’s much worse than they’re saying.”

That so? How do you know?

“Because the numbers they’re reporting are wrong, faked, too low.”

No kidding? How do you know?

“Because it’s much worse than they’re saying.’

That so? How do you know?…

Iterate ad nauseum.

Yes, because anything other than instantly reporting numbers on iffy tests in rambunctious medical circumstances points to a conspiracy. I’ve worked with medical data for twenty years, and the best you can say about it is it’s a mess. Look at our own data. It’s not like the entire world has got together to decide to release 100% accurate counts at 8 PM Eastern Savings Time. Numbers come in from all over, staggered and rough. We must account for this in our minds when wondering whether how much to trust the model.

Last Friday I did some numbers, which unfortunately I cannot update, because my number source stopped carrying totals for individual Chinese cities. A real pain in the kiester. Nevertheless, here’s what I did then. The idea is still sound:

Diamond Princess carried 2,670 and 1,100 crew, and had 696 coronavirus cases [still 696], or 18%. 6 dead [it’s now 7, but I’ll leave this as it is], which is 0.8% among cases, or 0.16% in toto.

This ship makes nice upper estimates: consider the tight quarters and mandatory mingling and isolation.

Then look at Shagnhai (close to Wuhan), which had Monday about 337 cases and 3 deaths—months after the outbreak. Shaghai has 24.24 million souls.

Thus: 0.14% case rate, 1% in-case death rate, 0.00001% death rate in toto.

A nice lower estimate.

A little too low, though. Applying Shanghai to world [7.7 billion] gives ~110,000 total cases, ~1,000 deaths.

We now have ~100,000 cases, ~3,400 deaths. But near the secondary peak.

Princess to world: ~142 million cases, ~12.3 million deaths. With no indication data trending that way.

China’s numbers have long since slowed, and almost stopped (not of flu, year by year!)—the rate of increase has slowed, I mean. The totals necessarily can only increase. The Wu Flu began in December, and it’s not growing worse at the hot zone, or really anywhere in China.

Hubei province, Google tells me, has 58.5 million people. China (Monday morning, EST) had 80,735 reported cases, which are spread all over the country of one billion souls. Even if all cases were in Hubei, the population case rate is 0.14%. China deaths (also Monday morning) 3,119. This is a 3.8% in-case death rate, or 0.005% death rate for the whole population. Tuesday morning update: 80,754 cases, 3,136 deaths, almost no change.

And the numbers are slowing fast (get it?) in China. Cities nearby Hubei aren’t “going exponential”—the most favored phrase I read—except in the trivial sense that going from 1 to 2 to 4 cases is exponential, but not especially concerning.

Panicked yet?

Here’s another take:

In case you can’t see it, it reads:

American Hospital Association “Best Guess Epidemiology” for #codiv19 over next 2 months:

96,000,000 infections
4,800,000 hospitalizations
1,900,000 ICU admissions
480,000 deaths

vs flu in 2019:

35,500,000 infections
490,600 hospitalizations
49,000 ICU admissions
34,200 deaths

Those stats are for the USA alone, not the world. Though I did see an ackshually guy say it’s not the whole AHA but just one professor. These kind of numbers are not uncommon from all kinds of sources, however.

Here’s another “As the coronavirus spreads, one study predicts that even the best-case scenario is 15 million dead and a $2.4 trillion hit to global GDP“. If you read the story, this is the “best-case scenario”, too.

On the other hand, some caution: Why Novel Coronavirus Fatality is Likely Overestimated.

CDC on the flu, week ending 29 February (these are always 1-2 week delayed):

CDC estimates that so far this season there have been at least 34 million flu illnesses, 350,000 hospitalizations and 20,000 deaths from flu.

USA deaths from coronachan: 22. Germany, incidentally, which had more than twice the number of USA cases had 0 deaths (so far).

A lot of people on our side of the divide are on Trump for on Monday pointing out last year saw 37,000 flu deaths in the USA. As if him saying it making its wrong or unimportant. Everything is political.

Italy and Iran had many more deaths. Iran might be slowly, Italy nearing its peak, probably.

Now you will remember what happened with SARS (see the links above where I keep repeating this). It was bad at the hot zone, and in a couple of other remote places, like Canada, which had very high, double-digit death rates. But it was almost benign in many other remote places. Similar kind of thing is happening with coronavirus. Whether is remains like this is only a guess. These guesses may be way off and this thing escalates like the AHA says. It hasn’t done so by now in China, but hey, we could have bad luck.

What has apparently (or might have) happened with coronavirus is that there are two strains, the worst in China and perhaps Italy and Iran, and the milder most everywhere else. I haven’t seen any confirmation this is so (about who has what), but it would explain the differences.

Incidentally, the tests people are using for diagnosing coronachan, and there are many, are not perfect. With the heightened publicity, i.e. panic, many more are going to be checked and surely some false positives are finding their way into the case numbers. That’s less likely with deaths, but not impossible. That means the true overall death rate might be higher than we think. But it also much less infectious than we think. We won’t know any of this for sure until long after, when it becomes the interest of obscure scholars.

Here’s another hot take. Barbie said, “Math is hard!”

No, wait. This one. This PhD said (click to see the whole thread):

We’re looking at about 1M US cases by the end of April, 2M by ~May 5, 4M by ~May 11, and so on. Exponentials are hard to grasp, but this is how they go. 4/n

I pointed out:

Exponentials sure are hard to grasp. Logistic curves are even harder.

Infections resemble logistic curves and not exponentials, for the excellent reason that exponentials always predict *everyone* will be infected in time. And this never happens. 1/

Look, even CHINA (a billion souls) does NOT have MILLIONS infected, even after 2-3 months of the outbreak. How is it we’re going to beat their numbers so far from the hot zone? 2/

I point this kind of thing out, and some get it. Some, though, are almost angry, as if any good news about this virus is unwelcome.

So many more headlines! Like Ross Douthat’s “My Sunday column: The Coronavirus is Coming For Trump’s Presidency” in which he among other cringey things wrote the eye-rolling “Obviously the White House isn’t to blame for everything that’s gone wrong with the coronavirus response.” Rod Dreher is taking the Fr James Martin role. Never Trumpers in general are trying to score political points.

The WSJ had a headline I’m too lazy to find that ran something like “How deadly plagues will become more common”, which was redolent of global warming concern.

Finally, a word on cancellations. I said it last time, but it bears emphasis. Many companies and politicians are banning travel, forbidding gatherings and the like. Some of this is surely concern and appropriate. But I’d bet much is fear—-fear of the crowd. Just what would happen to MegaCorp Inc. Ltd. if an employee gets coronavirus on an official business trip when all the other companies have stopped flying?

What would happen to the politician who wasn’t seen spending billions on brother-in-law contracts and sees an outbreak in his constituency? To ask is to answer. All this adds to the panic.

Onto the Numbers!

We had the initial peak, then the spread with the expected secondary peak. Will there be third and subsequent peaks? Will the coronavirus be like the flu or the ordinary coronavirus and be with us perennially? Will this really explode like it did in China everywhere? Hey, maybe, maybe not. Nobody knows. Not so likely though, because deadly contagious diseases tend to fade out or only pop up from time to time, like ebola or MERS.

One thing that we cannot do is this, which I see everywhere. Given “I don’t know what’s really going on” we cannot conclude “It’s really bad out there!” This is Talebism. The only thing you can say if you don’t know what’s really going on is that you don’t know what will happen. To say anything else is to take a black swan dive.

Here is the code and the data (see earlier posts for details). All numbers from 8 PM EST, Monday night. You MUST read updates II and III for the code notes if you’re playing along; all the caveats, and there are many, are there.

Here is the naive model applied to the total cases and deaths:

The guess for total cases is ~160,000; total deaths ~6,200. This is higher than last week, but I changed the date of the second peak start to make the totals higher, since it seemed model was catching the top of the secondary peak. That it might be is seen in the next picture.

Here’s the daily cases:

Have we reached the secondary peak? If so, then the model is probably not terrible, though I’d guess it’s an underestimate, as it was during the primary peak. If the same pattern holds, multiply everything by (today) 1.1 to 1.3. That multiplicative adjustments goes to 1 as we approach the secondary peak, naturally.

What if there’s a third peak? Obviously, this naive model can’t see it. But neither can we see it in the data. It’s only a guess one way or another. We have to wait and find out.

Here’s the daily deaths:

Just as we cautioned last week, the daily deaths necessarily had to lag daily cases, for you can’t die until after you get sick. Again, look for the media to tout the deaths and not the cases. But because the deaths haven’t yet reached the secondary peak, the daily forecasts are surely too low. Also, deaths are more than in the primary peak, which is of interest, and suggests there might be a third peak, but smaller.

Looks like we have a couple more weeks of madness ahead of us.

Addendum

The daily data per country is here; see China, for instance. The model can be used on the country data, too, and it would make a great exercise to do so.

I also said this:

People are taking actions to prevent spread of the disease (especially hyper vigilant actions) as absolute evidence of the prevalence of the disease. This is like saying the number of people who buckle up makes a good estimate of number hurt or killed in car crashes.

Many normally sober people with expertise who are making predictions are very scared, it seems, of being on the wrong side. They’re fearful of hearing “You said it wouldn’t be bad, but look how many died!”

But they’re willing to hear “You way over-forecast.”

This is wishcasting and wrong.

The decision people make based on the forecast can be weighted lopsidedly; very willing to suffer false positives, say.

But the best forecast is always the most accurate, regardless of the cost-loss of decisions.

We’re aiming for accuracy here with the most unsophisticated model we can make, taking only into account the “shape” of viral outbreaks (this is also a stats class post). It hasn’t been terrible. It might turn terrible, but then it also might stay un-terrible.

Of course, I have to guard against the opposite, and be careful not to under-forecast because of all the over-forecasts.

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32 Thoughts

  1. “American Hospital Association “Best Guess Epidemiology” for” terrorizing as many Americans as possible. All estimates are politically motivated at this point and spreading fear and loathing is the goal. No one really cares about the disease. I mean, look at the PANDEMIC HIV/AIDS that continues to spread, cost millions a year to treat but can be treated at a cost of over $1000 per month, and no one cares at all. In fact, talking about it gets you jailed for discussing reality.

    It’s reported that Oregon has told its homeless people to stay 6 feet apart to stop the spread. The writer laughs, but that is the one recommendation that remains. But never let that influence one’s insane response. Keep believing the virus lives decades in suspended animation on everything you ever touched or will touch. After all, fear is freedom, or something like that….

    A friend called last night to say one of his relatives went to a Super Walmart in a fairly small town in Missouri and the shelves were empty of toilet paper, paper towels and hand sanitizer. He remarked these people are totally insane. NYC may not be this crazy, but some places are.
    (The good news seems to be if you like “rough” TP the Scott or Pom tissue like I do, those are the last brands to go so you’re going to be fine.)

    DAV: An insidious virus indeed.

  2. Somehow, I suspect we will see an additional spike in US active cases now that the CDC test kit snafu is being straightened out and many more people are getting tested. I suppose it is also possible that the number will decrease if the tests contradict an initial diagnosis of COVID-19, but it seems more likely that more testing will find more cases. But I think that along with good hygiene the key to containment (i.e. reducing the effective reproduction number below 1) is isolating those who have the disease and quarantining those who have been exposed, so I don’t think it is a problem if a spike arises from testing.

  3. RE: “But they’re willing to hear “You way over-forecast.””

    If you under forecast, people get impacted — imagine under forecasting mileage and skipping a stop to refill the gas tank, pretty inconvenient. More so where potential death is involved. Better safe than sorry…

    Sometimes, the long shot happens:

    Recall how hindsight was applied in Italy about what those scientists should have said about the severity of the earthquake nobody could reliably predict, but which later quaked L’Aquila Italy in 2009. They were prosecuted (2011-2012) for not predicting the severity.

    Under-predicting an unlikely earthquake is a guess (same as saying it just might be time for The Big One). But prosecuting for it – like receiving anger when numbers show the virus severity might not be so bad – is insane. These are examples of emotional-reasoning (where people presume their feelings are credible guides to reality … and we are thankful for flying with pilots who never buy into that line of reasoning, by the way, and trust their flight indicators instead).

    The whole world seems to be going insane, bit by bit. Wonder how many data sets might be compiled to track how that’s going. That’d be metadata, but perhaps enlightening…

  4. In The Netherlands people got Corona from skiing in Italy, or from an unknown source. That Italian strain won’t stay in Italy.

    Further, Italy has the same problem as China, more sick people than they can take care of properly. If IC patients are put in hospital corridor’s, they are going to die from bad care because Corona has swamped the system, not because of the virus itself.

  5. Shack Toms, I agree. The lack of available tests in the US is well known, and there are many anecdotes of people with symptoms who have to wait several days until testing, and results take another 2 days. That, along with long incubation periods, may mean that the actual number of infected people is quite a bit higher than the current confirmed cases.

    Also, I appreciated the extra attention to caveats on scenarios and separation of forecasts and decisions in this post. Thank you, Briggs, for your analysis.

  6. Italy’s higher fatality rate

    Maybe another strain…

    Maybe something else — The International Journal of Infectious Diseases, Vol 88, Nov 2019; Investigating the impact of influenza on excess mortality in all ages in Italy during recent seasons (2013/14 – 2016/17 seasons)…

    …reported that death rates in Italy from flu were above average.

    IF that’s a pattern it suggests something going on there, or that genetic subtype, or…, makes some virus types deadlier.

  7. @Ken – Italian population is much older. >50% of the population is “over the hill” and definitely skewed older (with very low fertility) vs US.

    Almost a quarter of the population is *really old* and in the high mortality segment.

  8. The irony is this cold virus may be able to accomplish what thirty years
    of unremitting global warming brainwashing was unable to do, in a matter
    of months no less.

  9. Apparently from many reports the American public is responding to the virus crisis like they always do — by panic buying everything on the store shelves.

    Could there be a problem? Then we must rush out to buy 55-gal drums of peanut butter.

    The retailers are wringing their hands — not from a shortage of shoppers but due to hand cramps from counting all the extra cash they’re taking in.

    Unfortunately it seems that robots are controlling the stock market via moronic AI, aka “program trading” by computers loaded with algorithms. Robots are not your friend. Any decent scifi movie makes that pretty obvious.

  10. The new surge could either be:
    1. Delayed reporting; and/or
    2. Surge of a second type of Corona virus.

  11. I am curious why the fools are buying toilet paper and paper towels. I can see the hand sanitizer, but shouldn’t they be buying thermometers, flu medicine, alcohol, plenty of fluids, vitamins, etc? Things you need when “self-quarantined”.

    Actually, most of the problem here is (a) panic and (b) failure to plan ahead. How many people know how much TP they use? Or do they just run to the store when they need TP. I live where people routinely have a month’s worth of supplies because we can be snowed in that long or lose power for a couple of weeks. No reason to run out and stockpile. It seems most people wait for the actual emergency before stocking up. Horse/barn door……

  12. I might be too short for this ride, but I think I get this much: if you work off of

    Premise 1: The best comparable event is SARS.
    Premise 2: Epidemics follow logistic curves, not exponential ones.

    Then you end up feeling cool as a cucumber, like Mr. Briggs.

    And I get that tests may give false positives, so I index the reported numbers with one raised eyebrow.

    And let’s be honest, I enjoy a good toilet paper joke at the expense of the unwashed masses.

    But my hypochondriacal mind keeps circling back to the following:

    a) WuFlu transmission is like RegularFlu, not SARS.
    b) We observe plenty of airplane driven international spread.

    So how important are (a) and (b)? Not to my hypochondriacal self, that is, but to Mr. Briggs. I mean, flu outbreaks follow logistic curves, but even without projecting flu transmission out to the moon, I can still logistically expect flu to infect tens of millions of people. And it is – dare I say it? – obvious that WuFlu has already hitched some sort of ride all over the world.

    One thing I’ve learned from the Statistician to the Stars is to think about concrete realities, and not be bewitched by abstractions.

    A plane lands at JFK from Milan. A guy gets off the plane carrying Coronachan, but he’s not symptomatic. He coughs, sniffles, picks his nose, drools, wipes his hands on one railing, another railing. His traddy wife greets him at the door with a big ol’ kiss. In about five days he has the sniffles and she goes to the pharmacy to find him some relief.

    Women pick their noses too.

    This happens again, and again, and again, all over the country, for months.

    And so I can’t stop buying toilet paper.

  13. For your city data from china.
    https://ncov.dxy.cn/ncovh5/view/pneumonia

    I left Beijing on the 24th of Jan, landed in Seoul, took a 3 day trip to seattle
    and returned to Seoul.
    unlucky I guess, or lucky

    About Mr exponential. The pandemic should follow Farr’s law.
    IFF people use their brains and practice social distancing and good hygiene.
    Evolution.

    China practiced these, like a mother. They still are. You have no idea.

    If you DON’T practice it, then expect to see bad results. Italy. Or compare deaths in St Louis versus those in Philidelphia during the 1918 flu. Both had a Farr’s law shape, but vastly different amplitudes. One practiced social distancing, the other did not. One flattened the curve, the other did not.
    In both cases, Farr’s law was followed, but the deaths were dramatically different. St Loius learned BEFORE seeing deaths. Philidelphia learned AFTER.
    Kill enough people or swamp your hospital and yes, the herd will isolate and the nasty critter will die out. Farr again.

    Also, Don’t be this guy. Don’t be the guy who compares this to the flu.
    Aint the flu. just don’t beclown yourself by even mentioning the flu.

    https://clutchpoints.com/jazz-video-rudy-gobert-touching-reporters-audio-equipment-surfaces-after-game-vs-thunder-postponed/

    Focusing on death rates is beyond stupid, because it’s not the mortuary that gets swamped. It’s the ICU. So in Wuhan they got swamped. Hence building a hospital in 10 days. In Beijing, by mid January companies, hotels ect were handing out masks. (Shitty masks so I bought a respirator.) Contact surfaces
    ( elevators, lobbies) were all being sanitized several times a day.
    the smell of bleach in the hotel was unbearable. But critters dont like that either.

    After I left friends let me know what kind of additional measures were taken in Beijing.
    In an elevator? no more than a couple people. Same here in Seoul. Going to work? only 50% of staff can show up. 2 meters between every desk.
    temperature check? twice daily by medical staff. Leave your home?
    temperature check. get on a bus? only half the seats can be occupied
    go into the store? temperature check. take the subway? you have to register
    Come back home? temperature check. And ya there is an app to report on yourself during self quarantine. ( same in Taiwan)

    wanna know how to slow it down? See what HK is doing. Also, they have driven their flu number to ZERO, weeks ahead of schedule. Wanna know how to slow it down? See what Taiwan is doing. See what cities outside Wuhan did. you won’t like it.
    at all.
    So YES you can slow it down and wipe it out. It will follow Farr’s law.

    Make no mistake. It will slow down. Farr’s law. That’s Not the question.
    The question is not, will you get it?, or will you die.? useless statistics, stupid questions. Basically distrust anyone, especially statisticians, who compares it to the flu or talk about death rates. The question is what will you do to the flatten the peak. Because if the peak overloads your health system then ya gots grade A trouble. And yes, after you have grade A trouble
    the infection will follow Farr’s law, and Mr exponential will be thwarted. woo hoo. ! Hell, herd immunity will do that. That’s not the question. The question is how high will your peak be, and can your health system (BEDS) handle the critical cases. your morgue can handle the deaths. stack em high!. can your health system handle those who DONT do us the favor of dying quickly.
    that requires more analysis than Mr Bayes.

  14. Steven Mosher: Both flu and coronaviruses are infectious respiratory illnesses. The symptoms at this point are virtually identical or we wouldn’t need that stupid lab test to tell us what someone has. “severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)” as the name of the new virus on 11 February 2020. This was later changed because the same idiots buying out toilet paper can’t figure out what the actual name means and think it’s SARS. Actually, we should have let them think that. We know what SARS does and it’s so much harder for whip up the useful idiots using a known disease. People love doom so we have to make sure we have a “new disease” name so they don’t get confused and actually might not freak out.

    Gino: Okay to buy, evil to hoard. The fools in Wyoming have gone insane and stripped the shelves on local stores of TP. Looks like African fields after the locust go through.

  15. An excellent expert comment on the inexactitude of the numbers/data being used in analysis of this virus:

    https://www.bmj.com/content/368/bmj.m606/rr-5

    Why Novel Coronavirus Fatality is Likely Overestimated

    “Dear Editor,

    “While the case fatality rate (CFR) of 2019-nCoV, the virus that causes COVID19, remains unknown, recently published figures likely overestimate the true rate.(1) Previous reviews of H1N1, MERS, and SARS highlight the difficulty of early estimation of CFR of novel viruses related to an absence of consensus on defining and measuring incidences and severities of infection.(2,3) Early estimates of H1N1’s CFR were susceptible to uncertainty regarding asymptomatic and subclinical infections, heterogeneity in approaches to diagnostic testing, as well as biases in ascertainment, survivorship, confounding and selection, and reporting.(2,3) These biases are difficult to overcome early in a pandemic.(3)”

  16. In Noord-Brabant, the southern part of The Netherlands, which is the most affected by this plague, doctors project the health care system to be swamped beginning next week. And they are talking openly about triage, i.e. assessing people’s changes and putting the ones with the biggest change of survival in an ICU.

    In modelling terms this means that more people will die because of Corona, because now you make sure that the person with the biggest change to die gets as much of that change as possible. You don’t pull the trigger, but that is about it.

    One needs a model with a limited care capacity, if such a thing is modellable, to predict how many people will die.

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