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If we are testing everyone, regularly, I'd be on board with that.

I would be interested in splitting up the positivity numbers, to see what it is for people who were tested due to symptoms, vs. people who were tested vs. contact tracing.  In that event, then yes, add another category under people who were tested mandatorily for work/procedures/travel, etc.

But the combined data of people who could possibly have it due to being symptomatic and/or contact tracing, is not aided by also throwing in the arbitrary group of people who were having elective surgery.

I know there's so much emphasis put on %positive results, and to an extent I get it... Generally you have to assume that if the %positive out of total tests is high, that there are a bunch of people not getting tested. If the %positive out of total is low, it suggests you're testing regime is widespread enough to catch most of the actual cases.

But it seems like a statistic that would be WAY too easy to throw false or misleading information. It's a data machete when you need a data scalpel.

Which IMHO is why the %positive metric should be important for epidemiologists, but when used as the basis for a whole bunch of things like what portions of the economy are open or on lockdown, it's not the right tool for the job.

If we are testing everyone, regularly, I'd be on board with that.

I would be interested in splitting up the positivity numbers, to see what it is for people who were tested due to symptoms, vs. people who were tested vs. contact tracing.  In that event, then yes, add another category under people who were tested mandatorily for work/procedures/travel, etc.

But the combined data of people who could possibly have it due to being symptomatic and/or contact tracing, is not aided by also throwing in the arbitrary group of people who were having elective surgery.

Yes, this I agree with, but the problem is that it is.

As long as that's the case, then we need to set a defined parameter that makes sense, AND determine what is acceptable rate within that.  There is value in contact tracing and helping researchers understand the virus in arbitrary testing for admission to certain things, but for public policy decisions it doesn't.

The reason 8% or 10% or whatever is the threshold for what is concerning is because we are only testing a specific group.  If you widen who is getting tested, then that gets a whole lot lower.  That's why the metrics the sports, doing mandatory testing, are using, are much, much lower.  If you were simply testing everyone, for no reason, at all, and were still getting 8% positivity rate, that would be horrifying.