It all made sense. To a certain extent, it still does. Most graphics depicting flattening the curve, such as in The New York Times, showed two curves. Typically, the first was associated with no lockdowns that peaked well above the capacity of the health-care system, while the second, “flattened” curve was associated with lockdowns with its peak hovering near capacity. The areas under each curve, representing the total number of Covid-19 infections, were roughly equal.
Flattening the curve made two assumptions. First, it assumed that a certain amount of deaths and infections were inevitable and the best we could do was delay the process. No one promoting flattening the curve talked of stopping the disease; there were no graphs showing that if we locked down, infections would go straight to zero.
It didn’t take long for the “flattening the curve” storyline to be abandoned. For example, California had more than 26,000 hospital beds available for coronavirus patients, but they locked down when they had about 200 coronavirus hospitalizations on March 20. That was less than 1 percent of their coronavirus hospital capacity. It quickly became clear that the California hospital system was not under threat, yet the lockdowns remained and “flatten the curve” was abandoned in favor of “suppress at all costs.”