In the Fall of 2020, my colleague, Prof. Immaculata De Vivo of the Harvard School of Public Health, and I wrote an essay about the public perception of risk and uncertainty, especially with regard to COVID-19. In this post, we are gathering comments from students in the Spring 2021 edition of "GenEd 1112: The Past and Present of the Future," an undergraduate course I teach at Harvard. Students were asked to read the essay, and then comment here on which part(s) of the discussion they expect would be most illuminating for non-quantitatively-inclined readers --and/or to suggest another framing of the issues discussed that would be more effective.
As a non-quantitatively inclined reader, I found the paragraph that contains the most numbers, in which you discuss the current uncertainty in the risk of dying from COVID-19, most interesting and helpful. In this paragraph, you describe different projections for COVID-19 related deaths and what that means for the uncertainty in the risk. Ultimately, this kind of reasoning relies on very simple, straightforward math that I find easy to follow. I haven't come across a clear description of what uncertainty means in terms of risk of dying from COVID-19, even with all of the articles I've read since the pandemic started. I think news outlets might shy away from this type of mathematical reasoning about risk because it could scare off readers. This essay shows that the math involved in calculating uncertainty in risk can be quite simple to explain and understand.