This is interesting. I was just looking at the dataset that you linked to. What other variables did you look at? I thought adult obesity would likely produce a strong correlation. Could you create a composite figure that incorporated a number of these stats (smoking, obesity, age)?
I noted while looking at data from California that the CFR for the Asian population was lower than average and I see that the data looks similar in my home state of MN. I thought perhaps there might be some inherited immunity within that pop but may be just a function of age.
I'll post an update above that lists some of the other factors I explored & what factor gave the best fit for each region. As you'll see, % of Smokers was most common. A composite factor would be tricky because the factors have so much correlation between each other (e.g. heavy smoking areas are also likely heavy drinking areas). It's been awhile since I tackled complicate multi-variate regression, but I'll give it some thought.
This is interesting. I was just looking at the dataset that you linked to. What other variables did you look at? I thought adult obesity would likely produce a strong correlation. Could you create a composite figure that incorporated a number of these stats (smoking, obesity, age)?
I noted while looking at data from California that the CFR for the Asian population was lower than average and I see that the data looks similar in my home state of MN. I thought perhaps there might be some inherited immunity within that pop but may be just a function of age.
I'll post an update above that lists some of the other factors I explored & what factor gave the best fit for each region. As you'll see, % of Smokers was most common. A composite factor would be tricky because the factors have so much correlation between each other (e.g. heavy smoking areas are also likely heavy drinking areas). It's been awhile since I tackled complicate multi-variate regression, but I'll give it some thought.