In my last couple of TIGC posts, I’ve reported that Covid-19 case and death rates are now higher in counties that sided with Governor Brian Kemp, a Republican, over his Democratic opponent, Stacey Abrams in Georgia’s 2018 gubernatorial election.
That resulted in a handful of unkind comments from readers who apparently felt it was impolite to apply such a political lens to Covid-19 data, so I decided to take an entirely apolitical swing at the numbers.
If anything, the results are even more striking. Where coping with Covid-19 is concerned, size does seem to matter: the bigger the better.
For this analysis, I’ve divided the state’s 159 counties into six population groupings — more than a half-million people (four counties); between 200,000 and 500,000 (seven counties); between 100,000 and 200,000 (14); between 60,000 and 100,000 (14); between 30,000 and 60,000 (21), and less than 30,000 (99). Then I pulled today’s county-specific Covid-19 data from the Georgia Department of Public Health (DPH) website and sorted it into the appropriate buckets.
The truth is, I’ve probably put an unnecessarily fine point on the population groupings. There’s not a great deal of difference in the results for the three largest groups of counties — in other words, counties with populations of 100,000 or more.
As the popuation groupings get smaller, though, significant differences do emerge. Taking the worst beating, collectively, are the 99 counties with populations of fewer than 30,000 people. That group of counties had the highest Covid-19 case rates and far and away the highest Covid-19 death rates, as this table shows.
The big takeaway from this is that the 99 smallest counties have a combined Covid-19 death rate that is more than double that of the four largest counties — 102 deaths per 100,000 people in the under-30,000 counties versus 47.6 deaths per 100,000 in the four largest counties.
Indeed, as the population grouping gets smaller, the death rate gets higher — and the same generally holds true for case rates as well.
I should probably emphasize that this analysis is based on a single day’s data — today’s — and that there can be some day-to-day fluctuations. I haven’t had time to string together a long-term day-over-day analysis, but I’ve done enough spot-checking of recent data to say that today’s data isn’t a fluke or an anomaly, it’s part of a trend.