“I tend to listen to people, who, from the beginning, acknowledge the uncertainty and live in the humility of ‘this is what we think we know to the best of our knowledge, but our the data are flawed, and it will change as we improve our understanding—we are trying our best.’ It’s hard to get a good tweet to go viral with that though (although some manage to do so!).
“The problem Etzioni says, isn’t the modeling team—which she believes is doing it’s best to ‘deliver results that match the data and produce ever-more-complex predictions about the future.’ Rather, it’s the way the information is communicated. Including ‘acknowledging your model’s limitations and uncertainties.’ Which she says ‘is never front and center in the IHME’s updates.’” - The Bulwark
Over the last several weeks I’ve encountered a range of negative views toward the models epidemiologists have been using in the struggle against COVID-19. Skepticism is a healthy thing. But rejecting models entirely isn’t skepticism. Latching onto fringe theories isn’t skepticism. Rejecting the flattening-the-curve strategy because it’s allegedly model-based isn’t skepticism either.
These responses are mostly misunderstandings of what models are and of how flattening-the-curve came to be.
