Research Article
Modelling and Simulation for Major Incidents
@ARTICLE{10.4108/icst.pervasivehealth.2015.259178, author={Eleonora Pacciani and Alessandro Borri and Paolo Maurizio Soave and Daniele Gui and Sabina Magalini and Simona Panunzi and Claudio Roberto Gaz and Pasquale Gaudio and Andrea Malizia and Andrea De Gaetano}, title={Modelling and Simulation for Major Incidents}, journal={EAI Endorsed Transactions on Pervasive Health and Technology}, volume={1}, number={4}, publisher={EAI}, journal_a={PHAT}, year={2015}, month={8}, keywords={predictive models for adverse outcomes, personalized patient treatment, health monitoring applications}, doi={10.4108/icst.pervasivehealth.2015.259178} }- Eleonora Pacciani
Alessandro Borri
Paolo Maurizio Soave
Daniele Gui
Sabina Magalini
Simona Panunzi
Claudio Roberto Gaz
Pasquale Gaudio
Andrea Malizia
Andrea De Gaetano
Year: 2015
Modelling and Simulation for Major Incidents
PHAT
EAI
DOI: 10.4108/icst.pervasivehealth.2015.259178
Abstract
In recent years, there has been a rise in Major Incidents with big impact on the citizens health and the society. Without the possibility of conducting live experiments when it comes to physical and/or toxic trauma, only an accurate in silico reconstruction allows us to identify organizational solutions with the best possible chance of success, in correlation with the limitations on available resources (e.g. medical team, first responders, treatments, transports, and hospitals availability) and with the variability of the characteristic of event (e.g. type of incident, severity of the event and type of lesions).
Utilizing modelling and simulation techniques, a simplified mathematical model of physiological evolution for patients involved in physical and toxic trauma incident scenarios has been developed and implemented. The model formalizes the dynamics, operating standards and practices of medical response and the main emergency service in the chain of emergency management during a Major Incident.
Copyright © 2015 A. Borri et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.