I would imagine that, given a detailed surveillance mechanism that’s strictly adhered to, you could calculate the maximum “time to detection” of how soon after hitting that threshold you’d know about it.
Post those 4 things: R_0 threshold, surveillance mechanism, time-to-detection, and shutdown plan then people can choose if they want to sign up for that risk.
Of course in the education case specifically, the real crux of the issue is the differential between the educators’ (generally older) risk tolerance and those of the students/the needs of students families (in the pre-university case).
That's exactly what's driven me batty about governments' responses.
After the initial lockdown, that's precisely what they should have done.
Instead, we got a schizophrenic "Everything is fine" and then "Everything is danger! Surprise second lockdown!"
No wonder people are pissed. It'd be better and more effective policy to just lay out the methods, criteria, and current status.
(PS: Technically, you're talking about R_t, or current, rather than R_0, or initial)
Lots of things broken with public response unfortunately.
Btw (because I also peeked at other links), if another UX discovery data point re: pharma research would help, flip me an email (in profile). My father just retired from T10 drug discovery R&D (pathology), and would probably be willing to talk your ear off re: process issues.