As a more general point, it’s not entirely satisfactory to say that you made an observation and got Rt approximately one, so that’s just what it is.
I suspect we agree. That is, there’s both a general obligation to consider other causal models that would generate your observations (“do we only observe this because of a selection effect?”), and a specific obligation that R0=1 in particular has a compelling alternate generator (“fixed testing capacity would also look like this”).
Where I think we disagree is that in this case, it looks to me like we can retire those alternative models by looking at other data (like deaths), and be mildly confident that the current R0 is approximately 1, and then there’s not a ‘puzzle’ left. It’s still surprising that it’s 0.85 (or whatever) in particular, but in the boring way that any specific number would be shocking in its specificity; to the extent that many countries have a R0 of approximately 1, it’s because they’re behaving in sufficiently similar ways that they get sufficiently similar results.
I suspect we agree. That is, there’s both a general obligation to consider other causal models that would generate your observations (“do we only observe this because of a selection effect?”), and a specific obligation that R0=1 in particular has a compelling alternate generator (“fixed testing capacity would also look like this”).
Where I think we disagree is that in this case, it looks to me like we can retire those alternative models by looking at other data (like deaths), and be mildly confident that the current R0 is approximately 1, and then there’s not a ‘puzzle’ left. It’s still surprising that it’s 0.85 (or whatever) in particular, but in the boring way that any specific number would be shocking in its specificity; to the extent that many countries have a R0 of approximately 1, it’s because they’re behaving in sufficiently similar ways that they get sufficiently similar results.