Which part(s) of the discussion do you expect would be most illuminating for non-quantitatively-inclined readers?
I think the discussion on what uncertainty means was the most illuminating. The analogy and comparisons between lying on a couch and Russian Roulette helped make the "risks" of uncertainty very clear; we can be highly certain, but that doesn't tell us too much about the risk of the result. Thus, in order to better express predictions, it's critical that different scenarios are given when summarizing results. Although the best method would to directly display a distribution, this is obviously difficult because it probably carries too much data. Thus, including something like the 2.5%, median, and 97.5% result is probably succinct yet expressive enough.
Suggest another framing of the issues discussed that would be more effective.
A good reframing of these issues could focus on how the public interprets data and information given to them. This could be discussing the challenges in communicating uncertainty effectively, especially in a context where information is constantly evolving (like in the COVID case). By highlighting the uncertainty in presenting data, acknowledging uncertainties, and explaining the process of scientific inquiry, the public can gain a deeper understanding of information and make better informed decisions.