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Related Concept Videos

Applications of GIS: Disaster Management and Emergency Response01:29

Applications of GIS: Disaster Management and Emergency Response

Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Response Surface Methodology01:16

Response Surface Methodology

Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...

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Related Experiment Video

Updated: Jun 22, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

A novel approach to multihazard modeling and simulation.

Silas W Smith1, Ian Portelli, Giuseppe Narzisi

  • 1Department of Emergency Medicine, Bellevue Hospital Center, 462 First Ave, Room A345A, New York, NY 10016, USA. Silas.Smith@nyumc.org

Disaster Medicine and Public Health Preparedness
|June 4, 2009
PubMed
Summary
This summary is machine-generated.

This study developed an agent-based model for disaster planning, simulating sarin release impacts on metropolitan medical services and public health. The model demonstrated that effective disaster plans and resource management significantly reduce mortality and improve outcomes.

Related Experiment Videos

Last Updated: Jun 22, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)
12:26

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling (SAHM)

Published on: October 11, 2016

Area of Science:

  • Disaster medicine
  • Public health preparedness
  • Computational epidemiology

Background:

  • Metropolitan environments face unique challenges during mass casualty incidents.
  • Effective disaster planning requires understanding the complex interplay of medical response, resource allocation, and public behavior.

Purpose of the Study:

  • To develop and apply a novel agent-based simulation model for disaster planning and response.
  • To assess the impact of sarin release scenarios in a metropolitan setting.
  • To evaluate critical factors influencing medical and public health outcomes.

Main Methods:

  • Developed an agent-based disaster simulation model integrating dose-response, surge capacity, and psychosocial factors.
  • Utilized a geographic information system (GIS) architecture for realistic environmental representation.
  • Simulated passive and active sarin releases in metropolitan transportation hubs.

Main Results:

  • Mortality increased nonlinearly with sarin dose, reaching 55.4% in active dispersion scenarios.
  • High emergency department occupancy (80-100%) significantly exacerbated mortality, similar to a queuing phenomenon.
  • Effective hospital disaster plan implementation, reduced response times, and adequate resources decreased mortality.

Conclusions:

  • Agent-based modeling is a valuable tool for assessing complex, system-wide effects during rare, large-scale events.
  • The model provides insights into optimizing medical and public health disaster response strategies.
  • Understanding psychosocial factors is crucial for managing healthcare demands during disasters.