Computer simulation analysis of prehospital nerve agent mass casualty incident care: Is Belgian antidote administration too slow?

Introduction
Computer simulation is an established but underused tool for policy analysis
and supporting decision makers. Current geopolitical developments have reignited the need for preparedness against civil chemical warfare agent
exposures. To examine the effectiveness of current CBRNe mass casualty
incident (MCI) response we implemented a small-scale sarin nerve agent
subway chemical scenario in a Belgian subway station with 986 victims,
analogous to the 1995 Tokyo Sarin attack. In this work. In this abstract we
present the work on the analysis of the arrival time of a Hazardous Materials
(HAZMAT) specific response mobile medical team (MMT). Currently there
is only one such Belgian MMT, stationed in Neder-Over-Heembeek. We
hypothesize that their arrival time would be too slow to salvage the most
critical victims.
Methods
The medical monodisciplinary intervention plans (MIP) and Brussels
Firefighters CBRNe policy were implemented in the SimJulia based simulator.
Chemical exposure thresholds are estimated based on a Gaussian Plume
model incorporating experimental wind-speed measurements and results
of a Computational Fluid Dynamics model. Chemical victims were modeled based on exposure and extrapolated data from military chemical victim
profiles. Victim health follows a Gompertz model of a compound score
based on routinely used clinical parameters. A subset of victims sustains
traumatic injuries on evacuation, which hastens the deterioration of their
clinical state. Chemical victims self-evacuate following a Social Force model
if able and are evacuated by the firefighter teams in protective clothing if
unable. After evacuation, victims receive antidotes and oxygen in the hot
zone from the HAZMAT MMT, as well as anticonvulsants and/or respiratory
support if required. After decontamination victims receive further stabilizing
treatment in the forward medical post (FMP). After FMP stabilization victims
are transported to local hospitals. The primary measured outcome parameter
is averaged all-cause mortality over 30 simulation replications.

Results
As expected, mortality increases with HAZMAT MMT arrival time after Sarin
release. This result follows a sigmoidal curve with a floor and ceiling which
correspond to the number of savable victims.
Conclusion
Our results imply that in an urban nerve agent MCI, antidote administration
has a critical time-window of 20-30 minutes. The HAZMAT MMT will most-
likely not be available quickly enough to be relied upon as the sole source of
antidotes. This suggests that antidote stockpiles and similar MMTs should be
prepared in other major cities. Another solution could be HAZMAT trained
paramedic intervention teams with standing orders to administer antidotes in
specific situations.

Methods
The medical monodisciplinary intervention plans (MIP) and Brussels
Firefighters CBRNe policy were implemented in the SimJulia based simulator.
Chemical exposure thresholds are estimated based on a Gaussian Plume
model incorporating experimental wind-speed measurements and results
of a Computational Fluid Dynamics model. Chemical victims were modeled