Now, if we had infinite medical capacity, then actually "getting it over with" could, from a number of deaths perspective, be advantageous. No lockdowns! No economic distress! However, you also overshoot a little. You would have deaths due to more of the population being exposed than required for herd immunity.
Of course, if you're a no lives lost at any cost, you'd still want to reduce deaths by slowing the spread until something like herd immunity or a vaccine. But most don't seem to have that sort of political or economic calculus.
Note also that the herculean effort to reduce all other cold/flu viruses by an order of magnitude only reduced R of covid-19 to around 1.
On the other hand, the results from the recent antibody testing in California[1] (if they're accurate) would suggest a much lower death rate - around 0.1% - 0.2%.
I fully agree that social distancing is the right move with the current data, but I wonder if that will continue to be the case as we come to understand the virus and its actual infection-fatality-rate more.
1) The antibody studies are incorrect, and over-counting the infection rate.
2) COVID-19 spreads much more easily than influenza, and so a large percentage of the population has become infected much quicker than typical influenza spread patterns.
Neither option is great, though to me of the two, #2 seems more hopeful, since assumedly we'd get herd immunity relatively quickly.
Is there a valid statistical model for letting COVID-19 spread quickly, and "getting it over with", compared to flattening the curve and letting it create fewer mortalities over a longer time?
I suppose even if the total number of mortalities is projected over time, there's real hope that we could find more effective treatments over time.