Quantitative Editor, @FiveThirtyEight | PhD, @LSEGovernment | 
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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/ …
Any chances, in epidemiology, that creating a multimodel ensemble could give more insights of the uncertainty and provide more information for decision-makers. In hydrological forecasting, it is done to observe uncertainties related to the model representation of the phenomena.
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