Thread by @jonlevyBU

1. I’ve been thinking a lot about our tendency for “bright line” decision making and what that means for how we approach school reopening decisions this fall...a little wonky, but indulge me, since I think it matters...

THREAD

2. Epidemiologists are quite familiar with this phenomenon, as p = 0.05 is treated as the magical bright line by some. If p = 0.049, it is significant and “real”. If p = 0.051, it is insignificant and “not real”. Many have written on this topic ⬇️

amstat.tandfonline.com/doi/full/10.10…

3. How does this connect to #COVID19? One place is the 6-foot “rule”. It is treated (by some) as a magical bright line. 5’11” - deep trouble. 6’1” - no risk, all is well.

The reality, of course, is that there is a continuum of exposure risk.

4. Before I go too far, let me just say that we need “bright lines” for guidance. We wrote about this in our @JExpSciEnvEpi article - a probabilistic function of risk vs. distance does not provide clear communication to people. A 6 foot guideline does.

nature.com/articles/s4137…

5. But I worry that it can be used too rigidly. Suppose you can set up a classroom in an educationally ideal way, but kids will be 5’11” apart. Should we nix it? Or, if we move desks 2 inches further apart, should we now be fine opening the school, regardless of anything else?

6. We need to be sensible and keep remembering that more distance is better than less distance; that just because people are precisely 6 feet apart does not eliminate risk; and that being 5’11” apart does not drastically increase risk versus 6 feet.

7. I also worry about this with numeric thresholds for reopening. The Harvard report below is outstanding, with categories to help guide decision-making, and clear language about the need to use multiple metrics, look at rate of change, etc.

globalepidemics.org/wp-content/upl…

8. But we have a tendency to ignore the details and just use the numbers. What can be counted, counts. I could see school districts grabbing the “bright lines”, shutting everything down at 25 cases per 100,000 and opening at 24.9.

9. Where does that leave us? Especially with a novel and uncertain risk, we crave certainty. We also don’t want to make the wrong decision, and relying on “bright lines” helps us to avoid blame if things don’t go well. But the hard decisions ultimately require judgment.

10. I am writing this as a quantitative person, who models exposure and risk for a living. I would love for there to be a simple formula on how to get to zero risk (other than staying in the basement forever). But we live in a world with a continuum of risk and shades of grey.

11. We also live in a heterogeneous world, where risk tolerance varies, as does the consequence of getting sick and the consequence of not being physically in school. Hopefully we can blend the hard numbers with a bit of judgment and compassion.

END