I’m confused why you assume that 36-68% of the population in the UK is infected. I thought, based on comments here, that those numbers were the output of a model that made highly optimistic assumptions about IFR, not an attempt at estimating the actual proportion of infections.
Do you think this is a realistic range for the proportion already infected in the UK?
I’m not impressed by the comment about this paper here on LW or the twitter link in it.
This paper was written by an international team of highly cited disease modellers who know about the Diamond Princess and have put their reputation on the line to make the case that this the hypothesis of high infections rate and low infection fatality might be true.
I think it is a realistic range that this many people are already infected and are asymptomatic. Above I’ve tried to summarize and review the relevant evidence that fits with this hypothesis.
But I’m not ruling out the more common theory (that we have maybe only 10x the 500k confirmed cases). I just find it less likely.
This paper was written by an international team of highly cited disease modellers who know about the Diamond Princess and have put their reputation on the line to make the case that this the hypothesis of high infections rate and low infection fatality might be true.
Yes, but when you actually read the paper (I read some parts), it says that their model is based on an assumption of low IFR, and in itself did not argue for low IFR (feel free to prove me wrong here).
That’s true and that’s what they were criticized for.
They argued that the current data we observe can be also be explained by low IFR and widespread infection. They called for widespread serological testing to see which hypothesis is correct.
If in the next few weeks we see high percentage of people with antibodies then it’s true.
In the meantime, I thought it might be interesting to see what other evidence there is for infection being widespread, which would suggest that IFR is low.
I really appreciate your attempt to summarize this literature. But it seems you still believe that the Oxford paper provides evidence in favor of very low IFR, when in fact others are claiming that this is merely an assumption of their model, and that this assumption was made not because the authors believe it is plausible but simply for exploratory purposes. If this is correct (I haven’t myself read the paper, so I can only defer to others), then the reputation or expertise of the authors is evidentially irrelevant, and shouldn’t cause you to update in the direction of the very low IFR. (Of course, there may be independent reasons for such an update.)
Thanks Pablo for your comment and helping to clarify this point. I’m sorry if I was being unclear.
I understand what you’re saying. However:
I realize that the Oxford study did not collect any new empirical data that in itself should cause us to update our views.
The authors make the assumption that the IFR is low and the virus is widespread and find that it fits the present data just as well as high IFR and low spread. But it does not mean that the model is merely theoretical: the authors do fit the data on the current epidemic.
This is not different from what the Imperial study does: the Imperial authors do not know the true IFR but just assuming a high one and see whether it fits the present data well.
But indeed, on a meta-level the Oxford study (not the modelling itself) is evidence in favor of low IFR. When experts believe something to be plausible then this too is evidence of a theory to be more likely to be true and we should update. An infinite number of models can explain any dataset and the authors only find these two plausible.
By coming out and suggesting that this is a plausible theory, especially by going to the media, the authors have gotten a lot of flag for this (“Irresponsible”—see twitter etc.). So they have indeed put their reputation on the line. This is despite the fact that the authors are prudent and saying that high IFR is also plausible and also fits the data.
I’m confused why you assume that 36-68% of the population in the UK is infected. I thought, based on comments here, that those numbers were the output of a model that made highly optimistic assumptions about IFR, not an attempt at estimating the actual proportion of infections.
Do you think this is a realistic range for the proportion already infected in the UK?
I’m not impressed by the comment about this paper here on LW or the twitter link in it.
This paper was written by an international team of highly cited disease modellers who know about the Diamond Princess and have put their reputation on the line to make the case that this the hypothesis of high infections rate and low infection fatality might be true.
I think it is a realistic range that this many people are already infected and are asymptomatic. Above I’ve tried to summarize and review the relevant evidence that fits with this hypothesis.
But I’m not ruling out the more common theory (that we have maybe only 10x the 500k confirmed cases). I just find it less likely.
Yes, but when you actually read the paper (I read some parts), it says that their model is based on an assumption of low IFR, and in itself did not argue for low IFR (feel free to prove me wrong here).
That’s true and that’s what they were criticized for.
They argued that the current data we observe can be also be explained by low IFR and widespread infection. They called for widespread serological testing to see which hypothesis is correct.
If in the next few weeks we see high percentage of people with antibodies then it’s true.
In the meantime, I thought it might be interesting to see what other evidence there is for infection being widespread, which would suggest that IFR is low.
I really appreciate your attempt to summarize this literature. But it seems you still believe that the Oxford paper provides evidence in favor of very low IFR, when in fact others are claiming that this is merely an assumption of their model, and that this assumption was made not because the authors believe it is plausible but simply for exploratory purposes. If this is correct (I haven’t myself read the paper, so I can only defer to others), then the reputation or expertise of the authors is evidentially irrelevant, and shouldn’t cause you to update in the direction of the very low IFR. (Of course, there may be independent reasons for such an update.)
Thanks Pablo for your comment and helping to clarify this point. I’m sorry if I was being unclear.
I understand what you’re saying. However:
I realize that the Oxford study did not collect any new empirical data that in itself should cause us to update our views.
The authors make the assumption that the IFR is low and the virus is widespread and find that it fits the present data just as well as high IFR and low spread. But it does not mean that the model is merely theoretical: the authors do fit the data on the current epidemic.
This is not different from what the Imperial study does: the Imperial authors do not know the true IFR but just assuming a high one and see whether it fits the present data well.
But indeed, on a meta-level the Oxford study (not the modelling itself) is evidence in favor of low IFR. When experts believe something to be plausible then this too is evidence of a theory to be more likely to be true and we should update. An infinite number of models can explain any dataset and the authors only find these two plausible.
By coming out and suggesting that this is a plausible theory, especially by going to the media, the authors have gotten a lot of flag for this (“Irresponsible”—see twitter etc.). So they have indeed put their reputation on the line. This is despite the fact that the authors are prudent and saying that high IFR is also plausible and also fits the data.