How bad will this get? It’s a simple enough question…
Why it’s so freaking hard to make a good COVID-19 model – FiveThirtyEight
The number of people who will die is a function of how many people could become infected, how the virus spreads and how many people the virus is capable of killing.
Straightforward enough, but the trouble begins when you try to fill in the numbers. Look at the factors and assumptions within just the fatality rate, for instance.
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.
There are so many factors as play here. This is the model they end up with. It’s one version, at least.
Over the next few months, you are going to see many different predictions about COVID-19 outcomes. They won’t all agree. But just because they’re based on assumptions doesn’t mean they’re worthless.
“All models are wrong, it’s striving to make them less wrong and useful in the moment,” Weir said.
Six unknown factors in coronavirus models and how they could affect predictions – The Conversation
Since the global outbreak of COVID-19, researchers have scrambled to develop and share models which can predict how the virus will spread. This is inherently tricky, as we know so little about the disease, and a model is only ever as good as the information you put into it.