Some problems with the model US policymakers are using to forecast coronavirus outbreak


Posted on 2 mins read

A letter published in the Annals of Internal Medicine urges caution for policy makers relying on IHME’s model.

The TL;DR is captured by a statistician

You have probably seen this model before, it’s the one that gives graphs such as this

And even if you haven’t, you’ve certainly heard about it. It’s the model that has been quoted by US policymakers for an initial worst case of 1 to 2 million and then a best case of 100-200 thousand.

Here are some problems with the model

First,

The model rests on the likely incorrect assumption that effects of social distancing policies are the same everywhere and that suppression policies will be implemented in all regions and will remain effective throughout.

Second, he model is overly reliant on the reported outcomes in Hubei and South Korea which took very different approaches than places for which the model is being used to make predictions.

Third, is that it is based mostly on reported death counts

death counts can be unreliable and reporting differences occur even within regions. Although Hubei province data represent the most complete mortality curve available, these numbers are suspect

Fourth, the model also has had to shift its predictions wildly in the past and isn’t very transparent about why this is

updated projections already reveal substantial volatility. For New York, the model predicted 10 243 deaths (range, 5167 to 26 444) on 27 March and 15 546 (range, 8016 to 22 255) on 30 March. Given the opaqueness of the model and underlying source data, it is challenging to understand why other regions’ projections also change dramatically. The alignment of past predictions with reality and current predictions should also be reported transparently.

And finally, the model is being quoted in the media without awareness or communication of any of the caveats above.



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