We all seem to be talking about guesstimates and data we can't be sure of, but I see little talk of what we can do.
If this were a tech problem - a big problem that seemed insurmountable - I would break it down into chunks as best I could, look at all the parts of the chain, and ask myself which I could be most effective in tackling first. Treat it like a sprint. Which part of the chain would that be?
With the caveat I'm not a domain expert, obviously, I'd go for the lack of testing kits - what makes testing for something like this so hard and so hard at scale?
Maybe it isn't and it's the supply of kits. Is this not something that is also "fixable"? There's a lot of intelligent and capable people on this forum, why not throw some pasta at the wall?
Well, as far as throwing pasta at the wall - it sounds a little bit like Engineer's disease to think that we can come up with a solution by thinking hard on the problem https://news.ycombinator.com/item?id=10812975
Obviously I'm as arrogant as the the next guy, but I think that arrogant next guy is probably already working on this issue and has a bunch of background in domain expertise and specific knowledge of the logistics I won't manage in a side project while commenting in between fixing bugs on the Equity/Credit analysis app I'm working on right now.
Just my 2 cents, and 2 cents is not worth much in this economy.
Throwing pasta at a wall implies that the idea of coming up with an idea is unlikely, thus not being arrogant, but also points out that it is possible, which it is.
As it is, I'd prefer the focus moved to solutions from speculation, at least it's an attitude I'm more comfortable with.
I don't think testing for this is actually that hard or that hard to scale - we had the full virus sequenced and its genome up on the internet within a couple weeks. Initially we do pcr based tests (easiest to "develop" - you just find the right primers which takes a couple more nites and then maybe a week or two to make sure it works). And there's already talk of people using new tools like SHERLOCK (CRISPR based diagnostics tool, and other tools like LAMP could be used as well (it's a special type of very fast, very sensitive pcr) since I recall some work done with LAMP in previous coronavirus outbreaks. One thing potentially making it hard is just getting equipment/kits into shut down cities (see article discussing Roche's diagnostics effort linked below). There are definitely challenges, but in diagnostics, the technology has come a long way to allow cheap, rapid, scalable testing.
If true, it's mainly because nCov can spread before showing any symptoms. And if true, that testing before 1 week after infection showing negative sign makes it worse.
Now imagine how to prevent a net virus from spreading, where it doesn't show any symptom and scanning it before 1 week shows negative result, while during that time it can easily infect other.
Testing in real people isn't cheap, and currently there is no proven cure either (afaik).
Vaccine is the best solution but it hasn't been found yet.
If this were a tech problem - a big problem that seemed insurmountable - I would break it down into chunks as best I could, look at all the parts of the chain, and ask myself which I could be most effective in tackling first. Treat it like a sprint. Which part of the chain would that be?
With the caveat I'm not a domain expert, obviously, I'd go for the lack of testing kits - what makes testing for something like this so hard and so hard at scale?
Maybe it isn't and it's the supply of kits. Is this not something that is also "fixable"? There's a lot of intelligent and capable people on this forum, why not throw some pasta at the wall?