Tactical Medical Evacuation in a Hyper-Transparent Combat Environment: Operational Conclusions from the 2022-2025...

The contemporary battlefield-defined by the mass employment of first-person view drones, multispectral sensor suites, integrated Intelligence, Surveillance and Reconnaissance systems, and precision-guided munitions-has produced an unprecedented level of informational transparency in which tactical medical evacuation no longer conforms to classical doctrinal assumptions. Drawing on field observations from Ukrainian units (2022-2025) and analytical modelling conducted in MATLAB, this study introduces a new conceptual framework that treats battlefield transparency as a probabilistic process dynamically updated through a Bayesian mechanism.

A connectivity parameter (C) is proposed to quantify the degree of coordination among friendly measures aimed at reducing sensor exposure (electronic warfare, smoke and thermal screens, maneuver, deception), thereby determining a unit's ability to generate short-lived "windows of reduced transparency."

Modelling demonstrated that under conditions of persistent aerial surveillance and dense sensor saturation, evacuation risk becomes sharply nonlinear, although Bayesian updates consistently shift the expected transparency toward higher values, rendering most traditional evacuation scenarios operationally infeasible. Only at sufficiently high levels of connectivity (C  ≥  0.6-0.7) do tactical conditions emerge that are compatible with relatively safe evacuation.

Based on this framework, FIRE-FORM v1.0 is introduced as a universal field tool for rapid "evacuate/do not evacuate" decision-making, integrating transparency, connectivity, and Bayesian likelihood into a single composite risk index. This approach establishes a new analytical paradigm for medical support in hyper-transparent battlespaces and offers a foundation for the development of adaptive doctrines and decision-making algorithms suited to technologically advanced modern warfare.