I'm not saying I agree with him, but his point of view isn't that far out of bounds. "Exponential growth" can happen over a short time
t or a long time
t. Capacity of hospitals are a time-dependent variable, total number of deaths may or may not be (see caveat below). Think of it this way:
Assume every person gives it to four others. Assume the capacity of my local hospital is 300. Assume 5% die who get it.
No controls.
I get it. I give it to four people today. They each spread it today. Those people spread it tomorrow. The new people spread it tomorrow. We're now at 1+4+ (4x4)+(4x4x4)+(4x4x4x4) = 341. Fourteen days later, we all get symptoms, hospitals maxed out. Problems ensue, 17 (roughly) die, but still more than 300 need care.
We flatten the curve, we social distance.
I get it. On day 13, I give it to four people. On day 13, they give it to four people. After 26 days, flat curve, but we have 21 people still sick. On that 13th day, they all give it to four people, which is another 64 people, but of the 21, 1 dies and the remainder get well. So there's only 64 sick at this point (39 days), not 85. More capacity. Those 64 give it to 4 more each after 13 days, so we have 256 more sick, but 3 die and 61 get better after 52 days. Still under capacity. The 256 spread it on day 13; that 256 are still going to lose about 13 people, so we're still at 17 deaths, but after 65 days, the burden on the healthcare system is far lower.
Now, I get it; the "flaw" is - or the theory is, depending on how you look at it - is the social distancing means that the "four infect four each" doesn't hold. And that's the real key, isn't it? Is that really true? Are the letters they're mailing, the packages their sending/receiving, the Door Dash they're ordering, really making that assumption hold? I don't know. "Common sense" says yes,
but that's an equally flawed methodology.