Disclaimer: I'm an Epidemiologist, not an Economist, so it was a reading from someone outside the field.
The idea that fields have certain "ways of knowing" something was interesting to me - that for economics, its about the analytic solution of an equilibrium.
My own field has something similar - generally speaking, the "hierarchy of evidence" starts with single case reports at the bottom, and then way up at the top are meta-analyses of large randomized clinical trials. As a modeler, I was once asked by a clinician where models (be they analytical or simulation) fit in that framework, and the only answer I could give was "along side it". Analytic results are Capital-T True in a way that even RCTs aren't, but are only true in the universe laid out by the model itself, for example.
It was also just an interesting read as models in my field have been migrating from analytic (or numerical) solutions to equilibrium problems toward more simulation and agent based models, and that same "Yes, but how do you know it's right" type questions are coming up.
This is slightly off-topic but I've recently read the book "Growing Artificial Societies: Social Science From the Bottom Up" and in my spare time I've been slowly implementing something very similar to the sort of "Maximally-Minimalist" simulation they describe.
This simulation includes the concept propagation of disease, again in a sort of "Maximally-Minimalist" way. While it's suitable in the sense that it fits with the rest of simulation, I've identified it as something that I am going to have to learn about before I extend that part of the simulation beyond what's already been described.
So I was wondering if you might know of a resource which presents various minimalist models of disease propagation that you could recommend. I'm not epidemiologist, I'm actually retired and studying economics as they pertain to environmental systems, so I'm not actually looking for anything that extremely complex or compute intensive... I'm just looking for something slightly more detailed that what I've got now and perhaps describes a step-by-step method towards modeling that's actually realistic.
It's a textbook on agent-based models written by an ecologist (where an awful lot of disease modeling is done). I believe there's a cheaper paperback version on Amazon, and they use NetLogo, which is pretty gentle computationally.
The idea that fields have certain "ways of knowing" something was interesting to me - that for economics, its about the analytic solution of an equilibrium.
My own field has something similar - generally speaking, the "hierarchy of evidence" starts with single case reports at the bottom, and then way up at the top are meta-analyses of large randomized clinical trials. As a modeler, I was once asked by a clinician where models (be they analytical or simulation) fit in that framework, and the only answer I could give was "along side it". Analytic results are Capital-T True in a way that even RCTs aren't, but are only true in the universe laid out by the model itself, for example.
It was also just an interesting read as models in my field have been migrating from analytic (or numerical) solutions to equilibrium problems toward more simulation and agent based models, and that same "Yes, but how do you know it's right" type questions are coming up.