All the good stuff, caveats, code, and explanations are linked, some in Update III, and the most important in Update II, Update IV, Update V, and Bayes Theorem & Coronavirus, so go to them first before asking what-about-this-and-that. Skip to the bottom for the latest model. Thanks to everybody emailing me sources. Sorry I’m slow answering emails.
If you can keep your head when all about you
Are losing theirs and blaming it on you,
If you can trust yourself when all men doubt you,
But make allowance for their doubting too…
— NBC Los Angeles (@NBCLA) March 22, 2020
WATCH LIVE AS PEOPLE PLAY IN THE FRESH AIR EXPOSING US ALL TO DEATH!
Item California police to use Chinese-made patrol drones with night-vision cameras during coronavirus lockdown “It seems a little Orwellian, but this could save lives.” Yes, ladies, it is Orwellian.
Here’s New York Gov. Cuomo saying the coronavirus lockdown could last as long as 9 months and that up to 80% of the population will get the virus pic.twitter.com/ghsmthfRmU
— Aaron Rupar (@atrupar) March 22, 2020
CUOMO: “This is not life as usual. None of this is life as usual. We talk about social distancing — I was in these parks, you would not know that anything was going on. It’s just a mistake. It’s insensitive. Arrogant. Self-destructive. It’s disrespectful … and it has to stop.”
As one mathematician put it: “330 million X 80% x 2% mortality rate = 5,340,000 dead Americans”. You heard it here first, friends.
Shut down the world for eight months! Hey, if in Cuomo’s words it “saves just one life”, let alone 5.34 million, it will have been worth it.
Since this is the internet, I am forced to write: Saying do not hysterically overreact is not equivalent to saying do nothing. Wash your hands, don’t be reckless with old folks. Do I have to be your mother? Do not panic.
Maybe you remember how this came upon us, and how scary it was. Here is a recapitulation of events as they unfolded in the United States. This is all information direct from the CDC.
—6 October 2019. The CDC begins receiving news of positive tests of a “influenza-like illness” (ILI). The CDC tracks these assiduously in its “U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet)”. Only 1.5% of all patients tested (at hospitals around the country) had an ILI. This low number did not raise an alarm.
—2 December 2019. The number of patients testing positive for an ILI rises to 3.3%. Still no alarm is raised.
—6 January 2020. The number testing positive soars to 6.2%. Faints bells clang through the media. People begin speculating about reports out of China. Some are already reported to have died from these ILIs in the USA.
—14 March 2020. The number of new patients testing positive for an ILI jumps to an alarming 85,284. The dead body count increases. The full storm is upon us.
The rest you know.
Or maybe you don’t. Because these are not just influenza-like illnesses. These are actual flu illnesses.
Week ending 14 March, “CDC estimates that so far this season there have been at least 38 million flu illnesses, 390,000 hospitalizations and 23,000 deaths from flu.”
Thirty-eight million cases! Nearly 400 thousand supply-chain ICU-stressing hospitalizations! Twenty-three thousand dead bodies! How many more were left permanently scarred from this horrible disease with reduced lung function and other comorbidities? And this is only in the USA!
Not 16,448 dead, our current coronavirus worldwide total (all numbers current as of Monday evening 8 PM EST), but 23,000 dead. And not 23,000 dead, either. That’s only this year. In 2016-2017, and again later in 2017-2018 the number of cases reached official epidemic proportions.
That kind of chart look familiar to you? Shows cumulative hospitalizations by flu season. Our current season is on the high end, but nowhere near the highest (this data is only since 2000). Point is this: over roughly four decades, flu has slaughtered about a million American souls. Mostly 50+ and 0-4 year-olds. What about the children!? A lot of dead kids. Over the entire earth, every two to three years a million souls are given early exits.
Flu will go on killing in horrendous numbers unless we do something about it! What that something is, is obviously this:
Every day beginning in the upcoming flu season (starting September 2020), each new case, from each state and large city should be blared across the headline of every news report. MONDAY: ONE CASE REPORTED. TUESDAY: CASES DOUBLE! WEDNESDAY: CASES SOAR TO FOUR. THURSDAY: WE HAVE GONE EXPONENTIAL.
Each death should receive nonstop coverage. All networks and newspaper should devote time exclusively to the flu. Politicians should issue immediate precautions about washing hands (always a good idea) and social distancing. Businesses not run by oligarchs should be shuttered.
As soon as the number of deaths rises above 10, in a way similar to what happened to COVID-19, full-on panic should become official policy. This should happen by about 15 September, since flu kills so many so effectively. Get ready for it.
By 1 October we’ll have already reached the same point of martial law we are now experiencing.
We’ll have to do this every year forever, too, because there is no other way to save lives taken by the flu.
So last year 37,000 Americans died from the common Flu. It averages between 27,000 and 70,000 per year. Nothing is shut down, life & the economy go on. At this moment there are 546 confirmed cases of CoronaVirus, with 22 deaths. Think about that!
— Donald J. Trump (@realDonaldTrump) March 9, 2020
After you get over your the-flu-isn’t-the-same-as-deadly-coronavirus dudgeon, did you notice anything else peculiar about that picture above? If not, go back and stare at it. Stare hard. I don’t want you to miss this.
Every flu season started, ramped up, became exponential, hit in clusters, slowed, trickled out, stopped. All without active interdiction, except for initial vaccinations.
Yes, I’ve made this point before, week after week. But it can’t be overemphasized. It is certain that we can affect the course of disease by our actions or inaction. Put a guy in solitary confinement with a stack of sterilized dry bread and tank of distilled water and he will by this active intervention avoid catching a cold, or any other communicable disease. We can in this case justly award a kudos to the jailer for keeping the prisoner disease-free.
In other cases, it’s not as clear. Keeping a ship off the coast flying the Yellow Fever flag is wise. Locking healthy and sick together in their homes, visited only by the same delivery man going to everybody else’s home—well, it’s not so clear if it’s wise or not.
Even the New York Times—and I am still reeling over this—agrees the current policy of martial law lite is wrong-headed, and likely more harmful than letting all but the chronically unhealthiest roam free.
Ever notice how ebola comes and goes in waves? What happened to all the other diseases that were going to kill us all? Who stopped them? Rather, what stopped them? What’s that? I didn’t catch what you said.
My only point is that we think too well of ourselves. We give ourselves too much grief for the spread of the disease, and we’ll certainly give ourselves far too much credit for stopping it. That should be kept in mind for when the next outbreak happens and the government moves to re-implement its “successful” martial-law-lite policy.
The naive model we have been using, which started as a class project, is confusing some. Rather, the numbers are. What are they?
Reports. Our model is a model of the reporting of numbers. That’s it, and nothing more. To the extent these numbers represent real cases, accurately ascribed deaths, and diligent records, then our model will attempt to describe the real extent of the outbreak. It’s “attempt” because, of course, the model is far from perfect.
Now, even in the case of measurement error in counting cases, improperly ascribed deaths, and chaos and inconsistencies in reporting, the model will still attempt to describe what numbers are being reported. Reporting is a very human process, and that’s what we’re modeling, the process.
How accurate are the numbers in reflecting Reality? It wouldn’t surprise anybody who has worked with medical data over a long period of time to say “not very”. Take Italian reports of deaths caused by coronavirus. It’s become clear that what they are reporting and the true caused numbers of dead bodies are at variance.
One professor said “The way in which we code deaths in our country is very generous in the sense that all the people who die in hospitals with the coronavirus are deemed to be dying of the coronavirus.”
This is that point the pulmonologist Woflgang Wodarg was trying to make (we linked his video last week, but I didn’t do a good job emphasizing it). Having coronavirus and dying of it are different things. Right at the beginning of this we were wondering how many deaths due to flu were being ascribed to coronavirus. We can now say “some”.
Here is an analogy if you don’t understand this: every patient in Italy who died had a sex, male or female. If we ascribed each death to sex, because everybody had it, we would be making a pretty dumb error. The error of ascribing death to coronavirus just because a person has it, when it is not truly the cause of death, is the same kind of error.
The Italian professor said “On re-evaluation by the National Institute of Health, 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 – many had two or three.”
Some say this is in an exaggeration in the opposite direction. Maybe so. But Italians seem to be prone to keeling over due to the flu, as this paper unearthed by or own C-Marie. “More than 68,000 deaths attributable to flu epidemics were estimated in the study period” over two flu seasons. “Italy showed a higher influenza attributable excess mortality compared to other European countries. especially in the elderly.”
Study claimed “99% of Those Who Died From Virus Had Other Illness“. Not so unusual, given the virus kills mostly the old, and the old often have comorbidities.
In any case, there is zero evidence this bug is wiping out young, healthy individuals.
Everybody by now has seen by this piece by John Ioannidis: “A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data“.
The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed. We don’t know if we are failing to capture infections by a factor of three or 300. Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population.
Ioannidis, like we did last week, also brought up the Diamond Princess cruise ship: “The case fatality rate there was 1.0%, but this was a largely elderly population, in which the death rate from Covid-19 is much higher.” The population fatality rate was even lower. The population infection rate was about 18%—in a mandatory lockdown.
There is in decision analysis a technique—which I do not favor—called minimax. It begins by, à la Nassim Taleb, imagining the worst possible scenario, and then moving to minimize that. That’s what we’re doing here.
People look at models like “Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand” by Neil M Ferguson and a slew of others, which conjures all sorts of awfulness. Even in their best theoretical case looking only at the USA and UK they say:
We find that that optimal mitigation policies (combining home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease) might reduce peak healthcare demand by 2/3 and deaths by half. However, the resulting mitigated epidemic would still likely result in hundreds of thousands of deaths and health systems (most notably intensive care units) being overwhelmed many times over.
The CNBC, always a reliable source, said “The coronavirus could kill millions of Americans: ‘Do the math,’ immunization specialist says“. Here’s another: “A report that helped convince Trump to take coronavirus seriously projected that 2.2 million people could die in the US if we don’t act“.
America is about 5% of the world’s population. If we extrapolate these numbers to the world, we get at least 40 million dead.
That’s a lot of bodies. Where are they?
We’re three or four months into this thing and we only have 16,448. China, the locus in quo, only had about 3,300 deaths. The virus is going to really get to work if it’s going to achieve its potential!
Japan was also supposed to be whacked. They’re further along than the USA, infection-timing wise. “A Coronavirus Explosion Was Expected in Japan. Where Is It?”
Japan was one of the first countries outside of China hit by the coronavirus and now it’s one of the least-affected among developed nations. That’s puzzling health experts.
Raise your hand if you’re tired of hearing from “experts”.
Japan did not engage in widespread testing, didn’t confine people under martial law lite. They carried on much as usual, encouraged wearing masks, washing hands, and not freaking out. Japan did not do minimax. Yet they survived.
Germany, you ask? “Germany’s low coronavirus mortality rate intrigues experts.” More experts!
We, on the other hand, minimaxed the hell out of the situation. We did our best WHAT-ABOUT-THE-CHILDREN! maximum death scenario, and then moved an entire country to war footing to avoid this worst case. Don’t forget what Cuomo said: any cost is worth it if we save just one life.
An alternative to minimax is Bayesian, meaning according all relevant information its due weight. And then acting on that cumulative knowledge, not on the worst damn thing that could happen. This is not a do-nothing policy, but a do-only-what’s-likely-necessary policy.
Minimax is effeminate. Our own country used to have hardier stock. Want proof?
Who recalls the 1957-1958 flu pandemic? The CDC said the “estimated number of deaths was 1.1 million worldwide and 116,000 in the United States.”
The 1968 pandemic? “The estimated number of deaths was 1 million worldwide and about 100,000 in the United States. Most excess deaths were in people 65 years and older.”
The wimpy 2009 pandemic had nothing on these guys. “From April 12, 2009 to April 10, 2010, CDC estimated there were 60.8 million cases (range: 43.3-89.3 million), 274,304 hospitalizations (range: 195,086-402,719), and 12,469 deaths (range: 8868-18,306) in the United States due to the (H1N1)pdm09 virus” and “151,700-575,400” worldwide.
We survived all these. We survived without martial law lite.
Incidentally, those earlier death tolls are worse than they seem because the USA population was much less than now.
Can you even imagine the apoplectic reaction our current leaders and populace would have to an outbreak like the 1957-1958 pandemic today? Hysteria isn’t in it.
Want more evidence panic is official? Fellow names Aaron Ginn published a piece on Medium, “Evidence over hysteria — COVID-19“. Filled with the same kind of thing you get here, but in a lot more colorful detail, and citing all sorts of competent sources. Medium suppressed it. (The link is to an archive.org version.)
My guess is the block is not because the report was inaccurate, which it doesn’t seem to be, but because of the fear of lawyers, which is justifiable. All it would take is some dumb citizen to say they read Ginn’s article, felt hopeful, went outside, and got the virus. The she sues. I, on the other hand, have no fear of lawyers, because I always wear a necklace of pure garlic.
Do yourself a favor and buy this award-eligible book, which you can use to comfort yourself in the quarantine.
Why this model? (Code and data). Because when all this started I saw far too many nervous people fainting over “exponential” increases. It is impossible—not unlikely: impossible—for numbers to stay exponential. If they did, then in just a few weeks everybody would be infected and die. Instead, outbreaks resemble logistic curves. These fit historical data marvelously. Why not try it here?
We saw the last two weeks that our own model was under-predicting, as predicted (if you follow me). It did a great job with the initial peak in China, but only after we were sure we had reached the peak and were on the way down. Another (more prestigious!) fellow found similar results as we did. Model for China did an okay job predicting the timing of the peak, and got close to the number of reported cases and dead in China.
How about the rest of the world? Have we reached the secondary peak yet? Maybe we’re close. Spring is upon us, in many places. With sunshine comes germ-blasting fresh and humid air.
Here’s the overall totals in reported cases and deaths—and not necessarily in actual totals.
There’s that lovely logistic. Again, we’re working with world totals, which smooths out “nations”, where we know nations are not homogeneous. Shutting down all of the USA, for instance, when there are case bumps in a couple of coastal cities as if these cities are representative of everywhere is official policy. Again, as I said last week, everybody expects this virus will be equally destructive everywhere—which never happens.
Anyway, predicted totals by April 19 are 840,000 cases, and 39,000 deaths. Worldwide. If we get to the peak in a few days or a week, these totals are likely to be good guesses.
The model week-by-week, since it has missed the secondary peak, has under-predicted. If the peak is more than a week away, then the model will certainly under-predict again.
Here’s the daily new reported cases, which gives a hint of peakiness.
There’s a seductive bend at the top which may indicate the peak is peaking. But this could be our eye fooling us, by mistaking the model for the data.
On the other hand, take a look-see at this, a new graph:
This is the acceleration of new cases. (Ignore the dashed spikes, which comes from stitching together the two peak models, and is an artifact. The spikiness in black lines comes from chaos in reporting, as previous posts have discussed.)
Daily cases are rate of change of the total. This is the rate of change of that rate of change; hence, acceleration. Which has been decreasing. The predicted peak comes when the acceleration turns negative; i.e. a deceleration. The signal is not strong enough to be perfectly convincing. But it’s strong enough to give some hope.
And here’s the daily new reported deaths.
Same hint of a slow down! A hint or a tease? Look, friends. We have seen predictions of millions slaughtered by coronavirus, yes? These are the actual daily death reports. In order to get two million, this curve has to (a) soar into the skies, adding 500 new deaths per day to the daily per day total (1750 today, 2250 tomorrow, 2750 next day, etc.) for 60 straight days to reach 30,000 per day or (b) get to about 2,000 a day and stay that way for every day for three straight years.
Either of these maneuvers would give a total of about two millions deaths. Either of these look like they’re going to happen given these pictures? Yes, they could happen. But are they likely?
Acceleration, you ask?
Death reporting is much choppier, maybe because the numbers are so much smaller, and smaller numbers are more variable. But if you squint, the same deceleration seems to be happening.
One Last Thing
My friends, I’m going to say something that will seem, to a few of you, harsh. People on the right are posting images and videos of sufferers of coronavirus and saying “This is why we need to take this as seriously as we do.”
This is equivalent to posting pictures of “migrant” kids washed on up on shore and saying “This is why we need open borders”. Which people on the right wisely condemned.
God bless everybody who gets this dread disease, and Godspeed to those who succumb. But we cannot make policy based on sad pictures.
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