Emergency Response Planning for a Potential Sarin Gas Attack in Manhattan using Agent-based Models

In this paper, we describe the agent-based modeling (ABM), simulation and analysis of a potential Sarin gas attack in the Port Authority Bus Terminal in the island of Manhattan in New York city, USA. The streets and subways of Manhattan have been modeled as a non-planar graph. The people at the terminal are modeled as agents initially moving randomly, but with a resultant drift velocity towards their destinations, e.g., work places. Upon exposure and illness, they choose to head to one of the hospitals they are aware of. A simple variant of the LRTA∗ algorithm for route computation is used to model a person’s panic behavior. Information about hospital locations and current capacities are exchanged between adjacent persons, is broadcast by the hospital to persons within its premises and is also accessible to persons with some form of radio or cellular communication device. The hospital treats all persons reaching its premises and employs a triage policy to determine who deserves medical attention, in a situation of over-crowding or shortage of resources. On-Site Treatment units are assumed to arrive at the scene shortly after the event. In addition, there are several probabilistic parameters describing personality traits, hospital behavior choices, emergency responder actions and Sarin prognosis. The modeling and simulation were carried out in Java RePast 3.1. The result of the interaction of these 1000+ agents is analyzed by repeated simulation and parameter sweeps. Some preliminary analyses are reported here, and lead us to conclude that simulation-based analysis can be successfully combined with other techniques to go hand in hand with traditional table-top exercises (as war-games) and can be used to develop, test, evaluate and refine public health policies governing catastrophe preparedness and emergency response.