Wednesday, March 18, 2020

Surviving the Coronavirus: Part 3

Diamond Princess Edition

I begin with a quick review of previous posts in this series.

In Part 1, I introduced the concepts (and an itsy bitsy teeny weenie bit of math) behind the spread of a virus. I predicted that, left unchecked by anything other than natural herd immunity, 1.6 million of us Americans would die.

In Part 2, I tooted my horn that I had beat the Brits to press by one day, conceded that they carried their work substantially further than I had mine, and then offered what I believe to be our only hope to avoid hundreds of thousands of deaths. We need to hunker down while we get an effective treatment widely distributed. The two leading candidates are a malaria drug and an AIDS drug.

In this Part 3, I want to consider an article arguing that the Diamond Princess experience indicates that we, both as a nation and as a planet, are over-reacting to the virus.

From Wikipedia, we get a nice overview of the Diamond Princess and its unfortunate transformation into a gigantic, floating, petri dish.
Diamond Princess is a British-registered cruise ship owned and operated by Princess Cruises. She began operation in March 2004 and primarily cruises in Asia during the northern hemisphere summer and Australia during the southern hemisphere summer. [...] Diamond Princess and Sapphire Princess were both built in Nagasaki, Japan by Mitsubishi Heavy Industries. [...]
Diamond Princess (ship, 2004) - cropped.jpg
2,670 Passengers + 1,100 crew (nominal)
On 20 January 2020, an 80-year-old passenger from Hong Kong embarked in Yokohama, sailed one segment of the itinerary, and disembarked in Hong Kong on 25 January. He visited a local Hong Kong hospital, six days after leaving the ship, where he later tested positive for COVID-19 on 1 February. On its next voyage, 4 February, the ship was in Japanese waters when 10 passengers were diagnosed with COVID-19 during the 2019–20 coronavirus outbreak.
The ship was quarantined on 4 February 2020 in the Port of Yokohama in Japan. The infections included at least 138 from India (including 132 crew and 6 passengers), 35 Filipinos, 32 Canadians, 24 Australians, 13 Americans, 4 Indonesians, 4 Malaysians, and 2 Britons. Home countries arranged to evacuate their citizens and quarantine them further in their own countries. As of 1 March, all on board including the crew and the captain had disembarked.
As of 5 March 2020, at least 696 out of the 3,711 passengers and crew had tested positive for the virus. On 6 March, the death toll reached 7.
The Diamond Princess based article that has drawn my attention and prompted this post is "A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data" by John P. A. Ioannidis, an epidemiologist at Stanford University. (Uh oh!) For those of you keeping track, I am seriously outgunned here. I am not an epidemiologist. I don't even play one on television. I am but a self-admitted recovering engineer. "Hi. I'm the Skeptical Juror, and I'm an engineer. I haven't solved an equation in three days."

I extract the Stanford epidemiologist's article below. I emboldened the portion where I think he makes a mistake so glaring that even a recovering engineer might catch it.
The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco. At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-CoV-2 or who continue to become infected. Better information is needed to guide decisions and actions of monumental significance and to monitor their impact. […] 
The one situation where an entire, closed population was tested was the Diamond Princess cruise ship and its quarantine passengers. 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.
Projecting the Diamond Princess mortality rate onto the age structure of the U.S. population, the death rate among people infected with Covid-19 would be 0.125%. But since this estimate is based on extremely thin data — there were just seven deaths among the 700 infected passengers and crew — the real death rate could stretch from five times lower (0.025%) to five times higher (0.625%). […] 
If we assume that case fatality rate among individuals infected by SARS-CoV-2 is 0.3% in the general population — a mid-range guess from my Diamond Princess analysis — and that 1% of the U.S. population gets infected (about 3.3 million people), this would translate to about 10,000 deaths. This sounds like a huge number, but it is buried within the noise of the estimate of deaths from “influenza-like illness.” If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year. At most, we might have casually noted that flu this season seems to be a bit worse than average. The media coverage would have been less than for an NBA game between the two most indifferent teams.
He bothered to extract a case fatality rate (CFR) from the Diamond Princess petri dish, but then he simply assumed that 1% of the U.S. population gets infected. Perhaps if he had read my first post in this series, he would not have made such a silly careless self-reinforcing mistake. He might have instead homed in on this tidbit from my earlier august post.
According to the International Journal of Infectious Diseases, the estimated Ro value for the Wuhan COVID-19 coronavirus, based on the Diamond Princess Cruise Ship trip to hell, is around 2.28.
Then, with the R zero value of 2.28 (which the International Journal of Infections Diseases derived from the Diamond Princess petri dish), the epidemiologist could have made a first order estimate of the percentage of U.S. infections as per my earlier august post.
Thanks to the wonders of mathematics, we can estimate the percentage of the population that must become immune to provide our entire herd with herd immunity. The equation is A = 1-1/Ro, where A is the herd immunity threshold (as a percentage of the population) and Ro is the reproduction number that you now understand so thoroughly and so well. Given that we have no vaccine, and probably will not soon have a vaccine, we are going to calculate the number of Americans who will have to get sick, survive, and develop a natural immunity. 
The next paragraph is rated S, for shocking. Get ready. Brace yourself. Here we go. 
If the starting R value for the coronavirus is indeed 2.28, as the poor folks aboard the Princess Cruise Line Ship have helped establish, then we will reach the herd immunity threshold once 56% of the population has been infected and has survived. Given there are 325 million of us here in the good ol' USA without a vaccine, then 182 million of us are going to have to get sick and survive.
Given that the herd immunity threshold is equal to the number of expected infections within a population, assuming the virus is left to its own devilish devices, then the Diamond Princess experience tells us that the percentage of the population that could be infected is 56%, not 1%. For those of you who might be particularly disinclined towards math, my engineering estimate is 56 times greater than that of the Stanford epidemiologist. My engineering estimate may be wrong, certainly, but at least I provide some basis for it. The epidemiologist simply said "If we assume."

Please do not include me as part of that scholarly pronoun.

If, instead, we derive both a case fatality rate (CFR = 0.625% as per the epidemiologist) and a starting reproduction number (Ro = 2.28 as per the IJID) from the Diamond Princess experience, then we're looking not at 10,000 deaths, but 1.1 million deaths. That, I am certain, would draw more media coverage than "an NBA game between the two most indifferent teams."

As I made clear in my first two posts of this series, our best strategy is to flatten the hell out of the curve and work like hell towards mass distribution of an effective treatment, at least two of which may be on the way.

As I pointed out in Part 2 of this series, the 31 authors from the Imperial College of London followed close on my heels in predicting more than a million deaths in the U.S. Their calculation was even more frightening, though, since it presumed serious flattening-the-curve efforts such as those now in effect within the U.S.

Since the Brits actually presented some defensible basis for their numbers other than "If we assume," I spent no time trying to dispute them. Instead, I faulted them just a wee bit for failing to even mention the possibility that cheap, effective treatments seem to be on the horizon.

According to the "we do not simply assume" Brits, we have to get even more aggressive at flattening our curve. I'm concerned that articles such as that of the Stanford epidemiologist do just the opposite.

I meant to include this thought in the original post, but the sun got in my eyes, or some other equally lame excuse.

One might argue that 56% infection rate cannot be correct since only 18% of the 3779 pax and crew (nominal) aboard the Diamond Princess got infected, despite close quarters.

One might respond that the Diamond Princess was quickly quarantined, internally and externally, once the initial infection was recognized. One might therefore argue that the Diamond Princess experience demonstrates the importance of flattening the curve as soon and as much as possible, reducing the infection rate from 56% to 18%, saving two-thirds of the 21 lives that would have otherwise have been lost.

The correct lesson from the Diamond Princess experience might be exactly the opposite of that being taught by the Stanford epidemiologist.

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