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I'm interested to see how we can use this data (Specially from the first source) to compare outcome from predicted vs actual and how to identify if there are any countries or states in US that are close to 'flattening the curve'.
Hello everybody, and thanks to @Ken_Black and @Ned for sharing the posts - legends on the case !
I wonder if anyone has used Alteryx to connect to the https://closedloop.ai/c19index/ open source model for identifying "At Risk" patients based on customer static data ? ( we won't have the Medicare claims data being outside US)
Python isn't my strong point, but I'm all over Alteryx 😃
Wow, what a tremendous wealth of curated links here - thank you, @LeahK! Inspired by@Ned's work, I created a viz that shows spread over time where the coloration (by county) is based on percentage of population of said county. I wanted to do that since all the charts I ever see just draw absolute numbers, not per capita. It's quite rudimentary as I (gratefully) still have the day job keeping me busy, (and my guitars have really been bugging me to be played lately too, haha). If anybody wanted to improve upon it, the code is here: https://github.com/johnjps111/covid19?files=1