The article by Brandeau et al. in the same issue presents recommendations for mathematical and simulation models:
1. Include stakeholder input to effectively address the spectrum of relevant real-world planning and response problems.
2. Include a user-friendly interface, the ability to customize model inputs to suit local needs, the ability to quickly and easily perform sensitivity analysis, and provide ongoing user support.
3. Build models that balance simplicity and complexity so that our models both adequately represent real-world scenarios and can be used and interpreted by the intended end users.
4. Include in our models the relevant outcomes, including outcomes that extend beyond those typically considered in cost-effectiveness analyses; these may include timeliness and efficiency of response, resource utilization, evacuation timing, and/or measures related to behavior of responders and the public.
5. Build models that address the fundamental uncertainties in disaster scenarios, including the likelihood and magnitude of an event, operational response capabilities, supply chain capacity and robustness, behavior of responders and the public, and countermeasure effectiveness.
6. In our reports, address the motivation for the study, define critical assumptions, explain the modeling methodology, discuss key sensitivity analyses, make available public-use versions of the model, and identify
all relevant partners in model creation.