Predicting emergency evacuation and sheltering behavior: a structured analytical approach.

Abstract

We offer a general approach to predicting public compliance with emergency recommendations. It begins with a formal risk assessment of an anticipated emergency, whose parameters include factors potentially affecting and affected by behavior, as identified by social science research. Standard procedures are used to elicit scientific experts' judgments regarding these behaviors and dependencies, in the context of an emergency scenario. Their judgments are used to refine the model and scenario, enabling local emergency coordinators to predict the behavior of citizens in their area. The approach is illustrated with a case study involving a radiological dispersion device (RDD) exploded in downtown Pittsburgh, PA. Both groups of experts (national and local) predicted approximately 80-90% compliance with an order to evacuate workplaces and 60-70% compliance with an order to shelter in place at home. They predicted 10% lower compliance for people asked to shelter at the office or to evacuate their homes. They predicted 10% lower compliance should the media be skeptical, rather than supportive. They also identified preparatory policies that could improve public compliance by 20-30%. We consider the implications of these results for improving emergency risk assessment models and for anticipating and improving preparedness for disasters, using Hurricane Katrina as a further case in point.