Optimising a public policy decision

Public policy decision-making often involves choosing between policy options that are each subject to uncertainty. Individual uncertainties might be relatively well understood but it can be difficult to assess the combined effect of multiple uncertainties affecting both costs and benefits.

This case study describes the use of Monte Carlo simulation to model the aggregate effect of multiple uncertainties associated with policy options for dealing with a potential animal health pandemic. The purpose was to assist policy makers to optimise their decisions in the context of tight political deadlines.

Read the full case here.