Some head-in-the-sand talk about this epidemic, you mean?
"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."
Without measures to slow down the rate of infection, you're not looking at infecting 1% of the US population, but 60-80%. Unless the author can point to figures that show significant pre-existing immunity in the population, that article made my bullshitometer explode. Writing "If" and then writing the following paragraphs as if your premise was true is fallacious at best.
"How can we tell at what point such a curve might stop?"
By asking epidemiologists to peer review what you write? The article is not even making a hypothesis as to why such a curve may stop (let alone a falsifiable one), it's just magical thinking, and ignores and entire field of science that experts are trained in.
Stunningly, the author is an epidemiologist, but I doubt he's going to let any of the other epidemiologists peer-review this -- it would get savaged, shredded and killed with fire.
His point about needing better data is accurate, but we can't wait until we have perfect data, and take our wishes for reality in the meantime.
"then flattening the curve may make things worse: Instead of being overwhelmed during a short, acute phase, the health system will remain overwhelmed for a more protracted period."
Again, that makes my bullshitometer explode. It engages in binary thinking, as if "being overwhelmed" is an all or nothing proposition. Given the choice, I know I'd rather be in a system that's overwhelmed and has to let 10% of the treatable people die than one that needs to pick the 10% to save...
"In the most pessimistic scenario, which I do not espouse, if the new coronavirus infects 60% of the global population and 1% of the infected people die, that will translate into more than 40 million deaths globally, matching the 1918 influenza pandemic."
That is not the most pessimistic scenario. That one is where the health services are completely overwhelmed and 7% of the infected people die.
The article first complains about the lack of data, but then makes a lot of conjectures that are *completely* unsupported by evidence, and even muses on scenarios outside of the confidence interval for the expected values for many things we can measure, albeit inaccurately (it's also untrue to say we have _no_ robust statistics. The number of deaths are an extremely robust statistic, even though it's a lagging indicator, and in Northern Italy the situation has become bad enough for the sample sizes to be large...)
For something a bit less "I just pulled some conjectures from where I should not have", and a published article instead of a shabby opinion piece, read this:
https://www.imperial.ac.uk/media/im...-College-COVID19-NPI-modelling-16-03-2020.pdf