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Predicting Emergency Evacuation and Sheltering Behavior: A Structured Analytical Approach

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  • Matt Dombroski
  • Baruch Fischhoff
  • Paul Fischbeck

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.

Suggested Citation

  • Matt Dombroski & Baruch Fischhoff & Paul Fischbeck, 2006. "Predicting Emergency Evacuation and Sheltering Behavior: A Structured Analytical Approach," Risk Analysis, John Wiley & Sons, vol. 26(6), pages 1675-1688, December.
  • Handle: RePEc:wly:riskan:v:26:y:2006:i:6:p:1675-1688
    DOI: 10.1111/j.1539-6924.2006.00833.x
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    1. Matthew J. Dombroski & Paul S. Fischbeck, 2006. "An Integrated Physical Dispersion and Behavioral Response Model for Risk Assessment of Radiological Dispersion Device (RDD) Events," Risk Analysis, John Wiley & Sons, vol. 26(2), pages 501-514, April.
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    Cited by:

    1. Joost R. Santos & Lucia Castro Herrera & Krista Danielle S. Yu & Sheree Ann T. Pagsuyoin & Raymond R. Tan, 2014. "State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1056-1068, June.
    2. Jinghong Wang & Siuming Lo & Qingsong Wang & Jinhua Sun & Honglin Mu, 2013. "Risk of Large‐Scale Evacuation Based on the Effectiveness of Rescue Strategies Under Different Crowd Densities," Risk Analysis, John Wiley & Sons, vol. 33(8), pages 1553-1563, August.
    3. Xuewei Ji & Wenguo Weng & Weicheng Fan, 2008. "Cellular Automata‐Based Systematic Risk Analysis Approach for Emergency Response," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1247-1260, October.
    4. Ben Krishna & Anindita Paul, 2020. "Collaborative information behaviour during epidemics: The case of Nipah outbreak in Southern India," Working papers 367, Indian Institute of Management Kozhikode.
    5. Matthew S. VanDyke & Andy J. King, 2018. "Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1378-1389, July.
    6. C. Natalie van der Wal & Daniel Formolo & Mark A. Robinson & Steven Gwynne, 2021. "Examining Evacuee Response to Emergency Communications with Agent-Based Simulations," Sustainability, MDPI, vol. 13(9), pages 1-24, April.
    7. Robin L. Dillon & Catherine H. Tinsley & William J. Burns, 2014. "Near‐Misses and Future Disaster Preparedness," Risk Analysis, John Wiley & Sons, vol. 34(10), pages 1907-1922, October.
    8. Margaret L. Brandeau & Jessica H. McCoy & Nathaniel Hupert & Jon-Erik Holty & Dena M. Bravata, 2009. "Recommendations for Modeling Disaster Responses in Public Health and Medicine: A Position Paper of the Society for Medical Decision Making," Medical Decision Making, , vol. 29(4), pages 438-460, July.
    9. Sammy Zahran & Daniele Tavani & Stephan Weiler, 2013. "Daily Variation in Natural Disaster Casualties: Information Flows, Safety, and Opportunity Costs in Tornado Versus Hurricane Strikes," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1265-1280, July.

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