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Emergent Dynamical Spatial Boundaries in Emergency Medical Services: A Navier-Stokes Framework from First Principles

Applications 2025-11-03 v1 Econometrics Methodology

Abstract

Emergency medical services (EMS) response times are critical determinants of patient survival, yet existing approaches to spatial coverage analysis rely on discrete distance buffers or ad-hoc geographic information system (GIS) isochrones without theoretical foundation. This paper derives continuous spatial boundaries for emergency response from first principles using fluid dynamics (Navier-Stokes equations), demonstrating that response effectiveness decays exponentially with time: τ(t)=τ0exp(κt)\tau(t) = \tau_0 \exp(-\kappa t), where τ0\tau_0 is baseline effectiveness and κ\kappa is the temporal decay rate. Using 10,000 simulated emergency incidents from the National Emergency Medical Services Information System (NEMSIS), I estimate decay parameters and calculate critical boundaries dd^* where response effectiveness falls below policy-relevant thresholds. The framework reveals substantial demographic heterogeneity: elderly populations (85+) experience 8.40-minute average response times versus 7.83 minutes for younger adults (18-44), with 33.6\% of poor-access incidents affecting elderly populations despite representing 5.2\% of the sample. Non-parametric kernel regression validation confirms exponential decay is appropriate (mean squared error 8-12 times smaller than parametric), while traditional difference-in-differences analysis validates treatment effect existence (DiD coefficient = -1.35 minutes, p<0.001p < 0.001). The analysis identifies vulnerable populations--elderly, rural, and low-income communities--facing systematically longer response times, informing optimal EMS station placement and resource allocation to reduce health disparities.

Keywords

Cite

@article{arxiv.2510.26810,
  title  = {Emergent Dynamical Spatial Boundaries in Emergency Medical Services: A Navier-Stokes Framework from First Principles},
  author = {Tatsuru Kikuchi},
  journal= {arXiv preprint arXiv:2510.26810},
  year   = {2025}
}

Comments

110 pages, 11 figures

R2 v1 2026-07-01T07:14:24.882Z