It is the glory of God to conceal things, but the glory of kings is to search things out.
(Proverbs 25:2 ESV)
Living in Missouri, I got curious about how population density affects the number of cases of COVID-19 per million people. So looking up case data from the John Hopkins website and demographic data from the census bureau I put together some graphs.
Figure 1 show the case density vs population density for counties in Missouri. It appears that case density does not take off until you reach a population density > 100 people per square mile. Two outliers are Saline county and Perry county, both of which have populations of ~20,000 and ~40 cases of COVID-19 (as of 4-14-20).
Breaking the data into 2 sets of PD < 100/sqmi and PD > 100/sqmi we have Figures 2 & 3.
Missouri has few real high population density areas, so let’s pull the data from the Top 50 counties in the country on the John Hopkins website and add it to Missouri.
Figure 4 makes it look like you don’t really take off in case density until around 400-500/sqmi. So let’s convert it to a log-log scale.
Figure 5 shows there is a definite trend toward increasing case density as population density increases. Around 62% of case density can be explained as a result of population density. Other factors affecting this are probably local culture, climate, politics, etc. For Phelps county Missouri, PD = 67 and population is 44,573. The equation in Figure 5 implies that Phelps county’s case load should be 27.448 x 67^0.6305 = ~389 per million population. For 44,573 population that implies there should be ~17 cases of COVID-19. There has only been 1 as of April 14, so Phelps county is doing fairly well. (Phelps county actually has the lowest case density in Missouri at 22/million.)
The point of all this is that efforts at containment (aka lockdown) should be focused on high case density areas–major cities, not the entire country.