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There’s several factors involved. One is weather. Another is population density. Others, of course include vaccination rates and efficacy, public use of PPE, and how contagious the particular viral strains circulating in that area at that time actually are.
Basically, every viral transmission is a function of physics and biology. If you take the covid virus, for example, you have a dose dependent relationship. I like to think of it as the 3 D’s: Dosage = Droplets + Duration. We’d say that the probability that a given person would get infected on the basis of a given interaction with an infected person would be a function of virus containing droplet density (ie how many tiny, virus containing spit particles are floating around you, which would decrease as a cubic function of (another D) Distance from that person. Any given virus like that would have a dosage threshold - a number of viruses necessary to cause an infection), which will itself depend on the individual strain and the target’s immunity level vs that variant. The duration part is just to make sure we write it as a function of time - so the cumulative number of viruses you inhale, for instance.
So conditions that tend to increase duration and decrease distance would tend to push infection rates up, but that’s in turn going to be bounded by things like PPE, which work by reducing droplets. And the number of droplets necessary to cause an infection will increase based on the target’s immunity profile.
All of which is to say it’s going to shift around, and the areas with higher (recent) vaccination rates and higher PPE usage will have lower values than they otherwise would have, but because things like population density vary so much between states, it’s going to throw off your analysis if you don’t account for that.