The uncertainty in every aspect of life in the Spring of 2020 made modeling relevant to everyone.
Pork supply chains were front page news. Randomized control trials were
driving major stock market swing. This ubiquitous focus on forecasting helped us
all appreciate the quote attributed to George Box that, "all models are wrong, but some are useful."
While the underlying mechanics of epidemiological models are highly complex;
understanding and sense checking model outputs is fairly straight forward.
For example, in the Spring of 2020, modeling teams assumed that there were 4-5 times as
many infected individuals as the declared case count. Does this seem correct to you?
Uncertainty is a constant and models are not perfect.
That said, public sector and corporate leaders must incorporate existing analytics tools
to ensure we are at least making the best decisions possible under adverse conditions.