Article ID: | iaor20081191 |
Country: | United States |
Volume: | 36 |
Issue: | 6 |
Start Page Number: | 486 |
End Page Number: | 501 |
Publication Date: | Nov 2006 |
Journal: | Interfaces |
Authors: | Larson Richard C., Metzger Michael D., Cahn Michael F. |
Keywords: | government |
Large-scale emergency incidents, such as acts of terrorism, human-caused accidents, and acts of nature, often overwhelm local first-responder resources. A historical review of five recent major emergencies – the Oklahoma City bombing (1995), the crash of United Airlines Flight 232 (1989), the sarin attack in the Tokyo subway (1995), Hurricane Floyd (1999), and Hurricane Charlie (2004) – shows the need for additional research to develop decision-oriented, operations research models to improve preparation for and response to major emergencies. Local emergency managers need decision guidance regarding evacuation directives, management of near-the-scene logistics, triage on the scene and at hospitals, use of volunteers and off-duty personnel, reducing telephone traffic congestion, and integration of response with second- and third-level responders from other jurisdictions. Especially promising is the potential use of data mining and statistical inference to glean more real-time information from 911 calls that may be reporting a coordinated attack at multiple locations.