Q: Why do all the models tell us something different about what to expect from the #PandemicCovid19?
A: It is complicated, but can be summed up well in this article by 538.
A: It is complicated, but can be summed up well in this article by 538.
TL; DR there are three primary factors:
1) Exponential growth makes models have great variation (think the estimates of 200,000 deaths vs. 2 million deaths);
2) There are many unknown factors (such as regarding the true rates of infected persons); and
1) Exponential growth makes models have great variation (think the estimates of 200,000 deaths vs. 2 million deaths);
2) There are many unknown factors (such as regarding the true rates of infected persons); and
3) Societies are adaptive (so we are constantly measuring in a society that is changing based on the trajectory of the pandemic).
In sum, it is difficult to make a model and all models have uncertainty. We just want the least uncertain model we can get...
In sum, it is difficult to make a model and all models have uncertainty. We just want the least uncertain model we can get...
”Think of it like making a pie. If you have a normal recipe, you can do it pretty easily and expect a predictable result that makes sense. But if the recipe contains instructions like “add three to 15 chopped apples, or steaks, or brussels sprouts, depending
on what you have on hand” … well, that’s going to affect how tasty this pie is, isn’t it? You can make assumptions about the correct ingredients and their quantity. But those are assumptions — not absolute facts.
And if you make too many assumptions in your pie-baking process, you might very well end up with something entirely different than what you were meant to be making. And you wouldn’t necessarily know you got it wrong.”
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