[tripletao]

I partially agree with the comment above, but I also think it misunderstands how numerical models are often used. At least where I've built them (not epidemiology), the goal wasn't necessarily to gather the most accurate set of inputs and produce the most accurate prediction of the output. The goal was often to help a highly skilled operator explore the parameter space and guide their intuition on the problem, to help that person and simulation together reach some decision.

So code quality mattered less then usual. If there's a significant bug, then the operator will probably notice, and if there's an insignificant bug then no one cares. The large number of input parameters also doesn't matter. The operators are fully aware that they could artificially manipulate the output to wherever they wanted, but to do so would be cheating only themselves.

It feels to me like Ferguson's model was built with similar intent, and probably served that purpose well. The problem came only when the media portrayed the model as a source of authority apart from the people operating it, perhaps to create a feeling of objectivity behind the decisions driven from that. That created an expectation of rigor that either didn't exist (in the software engineering), or fundamentally can't exist given our current knowledge of the science (in the input assumptions).