Quantum-Energy Epidemic Dynamics: A Probabilistic Framework for Modeling Infectious Disease Spread Under Uncertainty
Abstract
Abstract Infectious disease modeling has traditionally relied on deterministic frameworks such as SIR, which often fail to capture uncertainty and heterogeneity in real-world outbreaks. This study introduces Quantum-Energy Epidemic Dynamics (QEED), a probabilistic framework that integrates epidemic energy concepts with uncertainty modeling. Beyond its theoretical formulation, QEED is applied to a case study in Al-Hodeidah, Yemen (2020–2025), using climate anomalies, cholera surveillance data, and health service indicators. The results demonstrate QEED’s ability to capture multi-wave epidemic behavior, threshold effects, and climate-driven variability more effectively than classical models. This dual contribution—conceptual innovation and empirical validation—highlights QEED’s potential as both a theoretical paradigm and a practical tool for early warning and climate-sensitive epidemic planning. Epidemic intensity is modeled as: where represents the probabilistic distribution of infection states. The framework captures uncertainty, mobility effects, and environmental drivers, providing improved predictive capability over classical models.
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