ygolo
My termites win
- Joined
- Aug 6, 2007
- Messages
- 6,732
It seems petty to compare the handling of OCVID-19 right now since we are still in the middle of this crisis. It is also a complex issue where local leaders play more important roles than can be captured by readily available data. There are also many factors environmental, and sociological that made susceptibility very different.
However, people seem to be discussing making comparisons anyway, and it difficult to rule out motivated reasoning behind the analysis.
So, I am wondering if there is a way to blind the data and have people do the comparison without really knowing who they're analyzing.
What factors should be involved? Obviously, feeding raw numbers would make raw numbers of cases or deaths easily identify which nation, state, or locality is referenced (though deaths would be less directly identifying). Even per capita numbers, can be fairly easily be reversed to identify specific case. The amount of testing that happens is a relevant factor. So is, I'd assume, typical temperatures, humidity levels, the level of development of the infrastructure(e.g. LPI score), population density, and level of regular foreign travel before the crisis.
Maybe what is the best handling of the situation is fundamentally subjective?
One thought I had was to have people rate how well things were handled, and feed in normalized versions of all the above features along with political leanings of the regions rated to see which factors most influenced the rating of which region did well (perhaps it'll the political leaning)
Any thoughts on how you may proceed?
However, people seem to be discussing making comparisons anyway, and it difficult to rule out motivated reasoning behind the analysis.
So, I am wondering if there is a way to blind the data and have people do the comparison without really knowing who they're analyzing.
What factors should be involved? Obviously, feeding raw numbers would make raw numbers of cases or deaths easily identify which nation, state, or locality is referenced (though deaths would be less directly identifying). Even per capita numbers, can be fairly easily be reversed to identify specific case. The amount of testing that happens is a relevant factor. So is, I'd assume, typical temperatures, humidity levels, the level of development of the infrastructure(e.g. LPI score), population density, and level of regular foreign travel before the crisis.
Maybe what is the best handling of the situation is fundamentally subjective?
One thought I had was to have people rate how well things were handled, and feed in normalized versions of all the above features along with political leanings of the regions rated to see which factors most influenced the rating of which region did well (perhaps it'll the political leaning)
Any thoughts on how you may proceed?
