Simulating Victim Health State Evolution from Physical and Chemical Injuries in Mass Casualty Incidents

Mehdi Benhassine, Ruben De Rouck, Michel Debacker, Ives Hubloue, Erwin Dhondt, Filip Van Utterbeeck

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Abstract

The field of discrete-event simulation for medical disaster management is relatively new. In such simulations, human victims are generated using pre-determined transitions from one health state to the next, based on a set of triggers that correspond to treatment or the clinical progression of untreated injuries or diseases. However, this approach does not account for subtle differences in clinical progression. We propose a parameter-based model to characterize the evolution of symptoms at first for physical and nerve agent chemical injuries. We used a Gompertz function to predict the time of death in trauma based on forensic data. Then we separately considered the effects of the chemical warfare agent sarin (GB) being the origin of the chemical injuries for the purpose of modelling a GB attack in a metro station. We emphasize that our approach can be extended to other CBRN threats pending knowledge of clinical progressions available in the literature for the purpose of casualty estimations. The intent is to provide an estimate of time to death without any treatment and overlay this model with a treatment model, improving the evolution of the health state. A modification for non-life-threatening injuries is included without losing generality. Improvement functions modelling medical treatment are proposed. We argue that the availability of injury scores vs mortality can greatly enhance the validity of the model.

Original languageEnglish
Pages (from-to) 113–125
Number of pages13
JournalNew Trends in Computer Sciences
Volume1
Issue number2
DOIs
Publication statusPublished - 28 Dec 2023

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