There's no reason to interpret the serological study to think a higher R0 is implied, which is what you said.

The only way that missing cases affects estimates of R0 from time series is if we're missing a much bigger proportion of cases now than we were in the past. All the evidence I've seen leans the other way-- more testing, better testing, more cases diagnosed by "presumed" criteria.

So, it actually implies the opposite of what you're saying, and argues for lower R0.

I am not interpreting it that way, I believe in the consensus estimates. The parent commenter (articbull) thinks these serological studies (SC, LA, and to a lesser degree NY) prove that the IFR is much lower than we thought because the actual infection numbers are much higher. The NY study, using reasonable assumptions, looks like the IFR might be between 0.5% - 1.0%, but the SC study was claiming 0.1-0.2%. And I am arguing, in the hypothetical case that the SC study is correct (I think it is flawed), then we have under estimated R0.

Considering we have been under lockdown for over a month (which greatly impacts effective transmission), and considering our estimates of latency hasn't changed dramatically, I think my above assumption is fair.

> And I am arguing, in the hypothetical case that the SC study is correct (I think it is flawed), then we have under estimated R0.

I don't necessarily believe the Santa Clara County study, but there are plenty of other alternatives, including a pretty likely one: gross undercounting at the start of the epidemic and/or earlier cryptic spread in communities. This is something that SCC public health officials / Dr. Sara Cody has stated in recent days is her belief-- I am not sure I agree.

At this point we're accumulating a lot of evidence IFR is 0.3-0.5%.