Preparing a regional public health system for emergency situations is difficult because one has to find vulnerable points without prior experience of similar situations. By creating a fairly realistic simulator, NYU researchers modeled New York City’s public health response to a sarin gas attack and identified a few cracks in the system. The computer program, called Plan C, may serve as a tool for other cities to stress test their own hospital systems for various potential disasters.
The article, “A Novel Approach to Multihazard Modeling and Simulation,” is based on the authors’ test of the NYU computerized disaster simulation framework known as “Plan C” with a hypothetical malicious sarin release in several Manhattan locations. With the input of city demographic information, hospital resource and public transit data, the results showed that under certain circumstances, up to 22,000 individuals might become exposed, leading to 178 intensive care unit admissions.
Plan C is an innovative tool for emergency managers, urban planners, and public health officials to prepare and evaluate optimal plans for response to an array of hypothetical urban catastrophic situations. It was developed as part of the Large Scale Emergency Readiness (LaSER) Project at NYU’s Center for Catastrophe Preparedness and Response (CCPR).
Plan C uses a powerful, large-scale computational, multi-agent based disaster simulation framework involving as many as thousands of variables or agents – from existing hospital beds and emergency department services to hospital surge capacity and behavioral and psychosocial characteristics to anticipate public response to an attack. It has been able to simulate the complex dynamics of emergency responses in such scenarios as a chemical release, food poisoning, and smallpox.
According to the article, implementing disaster plans within 30 minutes compared to two hours of an incident diminished mortality and waiting times and reduced the number of patients who were severely affected. GIS portability to other urban locations was demonstrated.
Full story: Simulating a Public Health Disaster Using Multiple Variables Can Assist Hospitals and Cities in Preparing for Worst-Case Scenarios, NYU Researchers Find…
Abstract in Disaster Medicine and Public Health Preparedness: A Novel Approach to Multihazard Modeling and Simulation