Stanford Professor of Medicine & Epidemiology’s COVID-19 “Fiasco” Article, + Some Critiques

There’s a giant, constant, global ping-pong match right now regarding society’s response to COVID-19. Some see it as a potentially population-crushing, catastrophic wipeout if drastic measures aren’t taken (or aren’t taken for a long enough period of time). Some see it as really nothing more to fuss about than the common flu. (And, of course, there are people in between, whether they be the ping pong ball or the net in this metaphor.)

I will say that I’m not taking any sides here right now. I’m following the directive to the T and self-isolating like a mo-fo, but I’m also not an epidemiologist with expertise in pandemics and I haven’t taken a sophisticated stats course in a very long time, so I’m mostly in listening mode while sharing information that may be helpful. When it comes to most individual cases, the clear directive right now from officials in charge is to self-isolate as much as possible, wash your hands, and be cool (don’t panic). I am definitely not saying anyone who has a choice should do otherwise at the moment, even though I think having a debate about the best path forward is still open and worth having.

Also, we are not setting out every day to cover COVID-19 — quite the opposite — but when we see a gap in discussion or something particularly noteworthy to discuss, some of us have been compelled to bring it up. In this case (this article), I was compelled to highlight an article that Elon Musk, among others, liked and basically endorsed. It was written by John Ioannidis, a professor of medicine, of epidemiology and population health, of biomedical data science, and of statistics at Stanford University who is also co-director of Stanford’s Meta-Research Innovation Center.

The title sort of gets to the point (but not quite): “A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data.” More specifically, Dr. Ioannidis contends that there isn’t enough data about COVID-19 to implement drastic governmental and societal responses that crush the global economy and might put it into a depression. His argument is that there are assumptions being made about COVID-19 that are incorrect or shouldn’t be made at this point. His argument is also that the harms from overreacting could very easily surpass the harms that would occur from moderate reaction. In other words, it’s the second argument among these two options: 1) if we react too slowly and too weakly, society might be much more screwed than if we take drastic action now; 2) if we take drastic action now, society might be much more screwed than if we hold off on hardcore measures until we have more information.

For a much more scientific, professional, detailed explanation of the good doctor’s argument, read the article.

Just in the comments of the article, however, there were some strong critiques of the Stanford professor’s assumptions and logic. Here’s one comment (without grammar and punctuation corrections):

“The contagion factor is excluded from the authors analysis, which makes his theory just as incomplete as the missing data he complains about. The contagion factor of this virus is far greater than influenza — so if you don’t take measures to slow the spread you get a higher death rate because you can’t treat all the sick at once. Italy versus China is an actual example of what happens — they are already surpassing China’s death rate even though their population pales in comparison (60 million versus 1.35 billion).”

Here’s another:

“In the same article that you use the Diamond Princess cruise ship as a case study for fatality rates, you estimate that 1% of the U.S population might be infected. The Diamond Princess cruise ship saw nearly 25% of the ship’s passengers infected. Perhaps multiple your ‘lost in the noise’ 10,000 influenza-like deaths by 20+.”

As always, I encourage you to base your opinions on logic and statistics, not appeals to authority. The article referenced above was written by a distinguished expert in epidemiology, statistics, and medicine. However, other distinguished experts in epidemiology, statistics, and medicine have been offering the opposite take-home message. This is an article with a starkly different point of view. It seems to be going viral at the moment. (Pardon the initially accidental pun.) That piece follows a related Imperial College report that is a top reason several governments have taken drastic actions to slow the pandemic in the past couple of weeks — a report Elon Musk has little (0%) faith in.

Anyone at any level of power right now is facing an important and difficult challenge. They must consider a variety of risks — very large ones — and determine which are greater and which are more likely. I don’t think it’s helpful to quickly write off and demonize anyone who is engaging on the matter. Instead, 1) let’s try to understand what we know and what we don’t know, 2) consider what the possibilities are in those gaps of knowledge, 3) consider the risks on all sides, 4) and do the best we can in our own personal situation in this time.

Here’s my short list of things we know:

• The virus spreads fast without strong containment/mitigation/suppression efforts. (See: South Korea versus Italy.)
• The virus is killing people, but to a very tiny extent kids and a much higher percent older people.
• The virus seems to be waning if not disappearing in a few early locations that took strong and smart measures to stop the spread: Korea, China, Taiwan, Israel, the first town in Italy to identify a case.
• The virus is not waning in locations that picked it up later and have had weaker responses: USA, much of Europe.
• We don’t have nearly enough tests and are not administering them to nearly enough people to have solid statistics to crunch.

And here’s my short list of important things we don’t know:

• The actual number of infections in most places — since there are not nearly enough tests and few places are testing everyone with symptoms, let alone people who might have the virus without symptoms at this point. (Also, people tend to be infected for a significant amount of time — several days — before clear symptoms appear, making it impossible to determine the infection rate without mass-scale testing.)
• The actual death rate among those infected (since we don’t know the actual number of cases).
• What portion of society may get the virus without even showing any clear symptoms.
• Whether shutting down almost all of society, as several places have done, will have a greater net negative effect on society than if we had not acted or had acted much more softly.

• Whether the virus will go away with the change of seasons, and whether or not it will come back (stronger or weaker) next winter.
• Whether the virus will mutate enough, and badly enough, to make this a problem that grows in the coming months and years, or whether it doesn’t mutate much and shrinks/weakens over time due to herd immunity or such.
• Whether potential treatments really work to avert death in the worst cases, and how long it will take to get the relevant drugs to patients. (Again, cases have nearly dried up in places using the methods referenced in the linked story above, yet some experts say there isn’t yet enough proof they work, in particular in the worst cases.)
• How long and how strong government measures will be implemented in an attempt to contain and remedy the health and economic effects of COVID-19.

To close, please wash your hands, and if you are able to self-isolate, please do that too for the time being.

Featured image via Johns Hopkins University & Medicine.