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Modeling Human Response to Threats and Disasters

Explore the intricate process of warning response research spanning different disasters and human behaviors. Understand the factors influencing warning response, from message characteristics to receiver traits. Delve into the realm of intelligent consequence management, utilizing advanced modeling techniques for effective decision-making in disaster scenarios. Discover the major questions guiding research in this field.

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Modeling Human Response to Threats and Disasters

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  1. Modeling Human Response to Threats and Disasters John H. Sorensen Oak Ridge National Laboratory May 29-30, 2003

  2. Major Modeling Thrusts in Disaster Research • Warning Response • Warning Diffusion • Evacuation Behavior • Protective Action Effectiveness • Psycho-Social Impacts • Intelligent Consequence Management

  3. Warning Response Research • Started in the 1950’s • Driven by the shadow of nuclear war • If we sound the sirens, what will people do? • Series of studies - tornado, hurricane, flood, explosion, air raid sirens, alien invasions • Major findings • People seek more information • People converge on event

  4. Warning Response Process Hear Understand Believe Personalize Confirm Respond

  5. Receiver Characteristics Visual and other cues Family and network Female Younger Majority High SES Non-fatalistic Sender Characteristic Message source Message channel Message style Clear Specific Accuracy Certain Consistency Message Content Factors Increasing Response

  6. Alternative Responses to Natural and Technological Hazards • Do nothing/ denial • Confirm warning/ seek information • Evacuate/ temporary relocation • Seek protective shelter/ stay home/ isolation • Respiratory protection • Decontaminate • Seek medical attention • Help others

  7. Modeling Diffusion of Warning

  8. Intelligent Consequence Management • New sensor networks or links to existing sensor networks designed to detect and monitor the threats of concern • High-speed communications and data exchange • Real-time simulation models running on high-speed machines • Faster than real-time predictive capabilities • Advanced decision support tools that can process data and simulation outputs into a format useful to decision-makers

  9. ORNL LDRD • Dynamic evacuation modeling • Utilize deployable road sensor tape or existing monitors • First evacuation model with dynamic traffic assignment • Can update simulations using real time data • Linked to GIS

  10. Intelligent Consequence Management Architecture for Rad/Chemical Incident Alerting Sensor Sound Preparedness Alert Protective Action Library Protection Action ES Notify Emergency Response Team Damage Assessment Activate Monitors Choose Protection Plan Evacuate Go To Safe Room Dispersion Scenario Library Run Economic Model Data Archive Generate Evacuation Plan Generate Evacuation To Safe Room Plan Run Evacuation and Shelter Models Outdoor Dispersion Model Classify Event Distribute Plans (Electronically) Activate Warning With Evacuation Instructions Accident Library Data Archive Send Data Distribute to Emergency Response Team RT Traffic Counters Activate Field Monitoring Send in Response Team Generate Emergency Response Plan Initiate Search & Response Initiate Sampling Initiate Decontamination Generate Sampling Plans System components to be tested are in red Generate Search & Rescue Plan

  11. Major Questions • How will warnings be issued to publics once a bio event is identified? • To what degree will human behavior in a bio event be similar to other hazards? • Will bio events elicit a different types of human response than observed for other hazards? • What are the relevant parameters to model in a bio event?

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