Coping Equilibrium and Stability Margins: A Predictive Stability Control Architecture for Critical Biological Systems Demonstrated in Hantavirus Pulmonary Syndrome (HPS)

Abstract

Abstract Critical biological diseases frequently exhibit abrupt transitions from compensated physiological states to irreversible systemic collapse. Despite substantial advances in intensive care medicine, current clinical decision-making remains predominantly reactive, relying on threshold-based interpretation of isolated physiological variables after significant deterioration has already occurred. Consequently, many catastrophic clinical events are detected only after the underlying biological system has crossed a critical stability boundary. This work introduces the Ruin Horizon Framework (RHF), a conceptual systems-theoretic architecture designed to characterize complex biological diseases as nonlinear adaptive networks approaching critical state transitions. Rather than interpreting disease progression as a sequence of independent pathological events, RHF models host physiology as a dynamically coupled regulatory system possessing finite resilience, adaptive capacity, and stability margins. The central hypothesis of RHF is that the primary organizing principle of complex adaptive biological systems is not continuous optimization, but the maintenance of sufficient distance from a dynamically evolving Ruin Horizon. RHF defines the resulting adaptive operating regime as Coping Equilibrium, in which regulatory resources are dynamically redistributed to preserve an adequate Stability Margin. The framework proposes that catastrophic deterioration emerges when adaptive regulation progressively loses the ability to compensate for accumulating physiological stress, ultimately driving the system toward a critical boundary referred to as the Ruin Horizon. In contrast to conventional biomarker-centered monitoring, RHF evaluates disease evolution through continuous estimation of system-wide stability, resilience, and network coordination. To demonstrate the conceptual applicability of the framework, Hantavirus Pulmonary Syndrome (HPS) is presented as a representative example of a rapidly destabilizing biological system characterized by endothelial dysfunction, capillary leak syndrome, respiratory failure, and nonlinear host-pathogen interactions. Within this context, RHF introduces the concept of Dual-Horizon Dynamics, describing the simultaneous interaction between viral expansion and host physiological resilience. The proposed framework integrates concepts from nonlinear dynamics, network physiology, critical slowing down, resilience theory, and predictive systems control into a unified supervisory architecture intended to support anticipatory clinical decision-making. Importantly, the present manuscript does not disclose the proprietary mathematical implementation underlying RHF. Instead, it presents a secrecy-safe conceptual abstraction intended to stimulate scientific discussion and guide future experimental validation. If validated prospectively, RHF may provide a generalizable systems-level foundation for predictive stability monitoring across a broad spectrum of rapidly deteriorating critical illnesses.