Disclaimer: All of these graphics rely on data from The New York Times published in their GitHub repository. Please visit there and especially read the section on Methodology and Definitions. I think it is a very honest account of the shortcomings of the data that everyone, from the CDC to Johns Hopkins University to The New York Times, is compiling.
The graphic below shows the number of newly infected people per capita for each day averaged over a 7-day period. Seems like the hotspots from a month ago are likely no longer overrunning healthcare capacity. However, it looks like some more rural counties now may be having capacity issues. Unfortunately, I have no idea what rate of new infections per capita would overwhelm a given counties healthcare resources.
The graphic below shows the number of deaths attributed to COVID-19 per capita for each day averaged over a 7-day period. I’m not sure what to make of it but it seems to be homogenizing as one would expect.
The graphic below shows the percentage of the population in each county that we know has had or currently has COVID-19. I cut off the chart at 4% (1 in 25) but there are many counties with more than 4% that have been infected.
The graphic below shows the percentage of the population in each county that has died from COVID-19.
The graphic below shows the ratio of the number of people that have died to the number of people that have been infected (that we know of). There is quite a lot of variation from county to county. If a county has reported less than 10 infections, a mortality rate was not determined.
The upper slice in the graphic below shows the number of COVID-19 deaths per capita over the dates shown. The green slice shows the number of flu and pneumonia deaths per capita over the same time period in 2019. The death rate is cut off at 1 in 2,500 so the 2019 flu/pneumonia death rate is visible.
The graphic below is the full view of the previous animation so you can see how COVID-19 deaths dwarf those typical for the flu and pneumonia in many states.