The problem the modelers have is how to account for reduced transmission in a continuous model. If you don’t set it to zero, you can end up with 1⁄10,000th of a person still sick, and then the virus comes back full force a couple months later, despite having literally eradicated it. So yes, setting it to zero is wrong, but not doing so is also wrong. Because all models are wrong.
Perhaps you think they should be using an entirely different and more sophisticated model, and maybe they should, but it turns out that those have other drawbacks, like needing far more data than we have to calibrate and build, or needing you to make up inputs.
With actual numbers very, very large, this isn’t remotely a concern; the domain of a correct continuous model might be “so long as there are at least 100 positive tests per week” or the like. Once we’re there, we obviously need to treat things more discretely.
It’s just not a sufficient reason for the modelers to make this egregious an optimistic error in setting R as a function of social distancing measures.
those have other drawbacks, like needing far more data than we have to calibrate and build, or needing you to make up inputs
Those are exactly the drawbacks Zvi is pointing to! And they’re not even putting distributions on the parameter values the pulled from their asses!
The problem the modelers have is how to account for reduced transmission in a continuous model. If you don’t set it to zero, you can end up with 1⁄10,000th of a person still sick, and then the virus comes back full force a couple months later, despite having literally eradicated it. So yes, setting it to zero is wrong, but not doing so is also wrong. Because all models are wrong.
Perhaps you think they should be using an entirely different and more sophisticated model, and maybe they should, but it turns out that those have other drawbacks, like needing far more data than we have to calibrate and build, or needing you to make up inputs.
With actual numbers very, very large, this isn’t remotely a concern; the domain of a correct continuous model might be “so long as there are at least 100 positive tests per week” or the like. Once we’re there, we obviously need to treat things more discretely.
It’s just not a sufficient reason for the modelers to make this egregious an optimistic error in setting R as a function of social distancing measures.
Those are exactly the drawbacks Zvi is pointing to! And they’re not even putting distributions on the parameter values the pulled from their asses!