Here’s a quick Christmas Eve update of the Arizona Data by Zip code. This is a pretty interesting dataset because it allows me to look into much smaller areas than counties and see more granular trends. I can sort this data a number of ways and generally compare one or two weeks of data by zip code to see where the trends are. The below table is sorted by the percent growth in the zip code, but I also like to look at the data sorted by Normalized Growth (growth per 1000 persons in the zip code area).
As you can see, Pima county is topping the list for percent growth. This represents a surge in cases that is independent of the population in the region. It really surprises me that zip codes in Pima county are at the top of this list because Pima probably has the most restrictive anti-COVID rules in the state (including an evening curfew). The 85710 zip code is interesting because it is an older suburban area East of Tucson and the Median Age is over 40. This is kind of unique for a zip code in the top 10 by percent growth. Note that their normalized growth as a percentage of the population is very low, so what this tells me is that this zip code has had very little impact from COVID until the last week and then they saw a 23% surge. Note that the zip code in Douglas, AZ, (on the border with Agua Prieta, MX) has very different statistics. They saw almost 19% growth last week but have had a much bigger impact from COVID (their normalized growth is 4x larger than 85710). That means that their population was 4x more saturated by COVID last week than 85710. The next four zip codes by % growth are Pima county zip codes. The one with the highest normalized growth is 85706, which has had higher overall case numbers and also experienced higher normalized growth. Incidentally, it is also the zip code with the lowest median age and median years of education. Not sure what that means, but if I were to guess, I’d say this zip code has more people that can’t work at home.
Comparison of Normalized Case Growth with Population Density
Earlier I posted this interesting visualization showing how the zip codes with the lowest population density seemed to be experiencing higher than normal cases per 1000 persons. Below, I re-ran the data for last week and we see that at least for last week this interesting trend continues. There may be a multitude of reasons for this, but one interesting possibility is that the areas with higher population densities have more effective COVID restrictions in place and the areas with lower population densities may have less or no restrictions in place. This could be over-simplification, but it does seem to be the case that the counties with the most restrictive COVID measures are the largest by population.
Is the Arizona Surge Slowing?
Quickly, below is the cumulative case curve for Arizona as of 12/24. The blue dashed line is my polynomial curve fit, which as you can see has fit the red daily cumulative case counts very nicely until about a week ago when we saw the case acceleration rates start to slow. As I’ve noted in the past, the slowing acceleration rates are generally an indicator of the slowing of a COVID surge. So keep your fingers crossed. I also have another post that I recently put up that is looking at decreasing hospitalization as another leading indicator of the slowing of a surge.
