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Given the uncertainty around every component of #COVID19 forecasts, how can *anyone* do any useful modeling at all? The more research we did, the more confused I became. But our conversation with @drake_lab helped.https://fivethirtyeight.com/features/why-its-so-freaking-hard-to-make-a-good-covid-19-model/ …
Because there are huge ranges around most, if not all, of the parameters in the models, propagating the uncertainty through all of them (i.e. multiplying them all out) would result in a uselessly huge final range of outcomes. So how can we say anything meaningful?
Basically, many of the uncertainties are correlated; not all combinations of parameters are equally plausible or even possible. The thing is, it's hard to estimate those correlations from the data. But it's not just unhelpful to assume they're uncorrelated -- it's also wrong.
So if you think, like I feared, that the uncertainty means we can't say anything useful at all, that's not true. But this is where domain expertise and experience come in -- that's what helps modelers make informed decisions about how to narrow the range of outcomes.
Of course, even experts can disagree! Which explains why different research groups have come up with different forecasts. But that's what makes this topic a particularly iffy one for non-experts to weigh in on, as this excellent @W_R_Chase piece outlines:https://www.williamrchase.com/post/why-i-m-not-making-covid19-visualizations-and-why-you-probably-shouldn-t-either/ …
The modeling is still important, in that it gives information about the shape of the trajectory curve, even if you don’t know the units. For instance, using a standard SIR model with an open population, you can see the appearance of echo outbreaks in the months ahead...
...and you can surmise roughly when they might happen, even if you don’t know how big they might get. You can also make inferences about whether or not to relax international or regional travel restrictions when we look to restart the economy.
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