If they are anywhere nearly as sensitive to 'bayesian priors', aka parameters made up of full cloth, as the covid19 models, then I take a hard pass.
Edit: Perhaps that was a bit too much of an 'in jest' reply. I'm frustrated at the whole mathematical rituals schtick, when in reality the whole thing is at best an unfalsifiable qualitative guess. The parameter space is immense, and we only have 1 measurable trajectory through it for validation.
I've seen claims that the number of parameters in the Imperial College agent-based model was c.a. 400. Perhaps it was 40.
Compare to a quadratic or quartic fit to some log-lin data. If you have to represent your ratio of poorly-constrained model parameters (40 or 400) to apparently necessary parameters (say 4) _using Big-O notation_, then science has arguably left the premises.
Edit: Perhaps that was a bit too much of an 'in jest' reply. I'm frustrated at the whole mathematical rituals schtick, when in reality the whole thing is at best an unfalsifiable qualitative guess. The parameter space is immense, and we only have 1 measurable trajectory through it for validation.