https://blogs.scientificamerican.com/observations/leading-with-the-unknowns-in-covid-19-models/

As the U.S. tops the chart on COVID-19 cases and growth rate, the theme of regret is ubiquitous in the media. Lost time that could have been spent enacting more stringent distancing measures weighs on the minds of many leaders and citizens. As a researcher in uncertainty visualization, I fear a different sort of regret from our response to COVID-19.

Many visualizations, including variations on the widely distributed Flatten the Curve graph represent estimates produced by models. These models simulate the number of people who would be infected, require hospitalization, or die under different conditions. Flatten the Curve adapts a visualization first presented by the CDC in 2007 to compare such estimates under different levels and durations of social distancing. The author added a dotted line to represent his estimate of the number of available hospital beds in the country.