Comments (2)
Hi Mike thanks for opening this.
This is a known issue for countries/regions with few cases. The low sample size (which is a good thing as it means not many cases) leads to lots of uncertainty in the RT estimate (as the prior has more of an impact) and onset imputation. This uncertainty is then magnified in the forecasts beyond what is plausible.
I think the best step is to not forecasts for places with a low number of cases as we are unlikely to be able to make a reasonable prediction without a much stronger prior on R. I have made this change in the backend but due to the time it takes to compute these forecasts the changes won't show up until tomorrow.
Hopefully, that clarifies the issue. Will continue to monitor this to see if there is a.) a better solution or b.) implemented fix doesn't help.
from covid.
Updated the master to not forecast regions with very low case counts. Let me know if this doesn't fix.
from covid.
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from covid.