ArXiv TLDR

Macroscopic Signatures of Gauge-Mediated Contagion: Deriving Behavioral Shielding from Stochastic Field Theory

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2604.00153

Jose de Jesus Bernal-Alvarado, David Delepine

q-bio.PEstat.AP

TLDR

This paper uses stochastic field theory to model epidemics, showing how behavioral shielding emerges from gauge-mediated contagion and dynamically suppresses R_eff.

Key contributions

  • Unified model links microscopic epidemic dynamics to macroscopic population behavior via stochastic field theory.
  • Introduces a Reactive Immunity Field, showing radiative corrections create a dynamic herd immunity threshold.
  • Derives macroscopic reaction-diffusion equations, revealing "Fear Drift" and a cubic shielding penalty in R_eff.
  • Maps field-theoretic concepts (Debye screening, vacuum polarization) to specific terms in behavioral equations.

Why it matters

This paper offers a novel field-theoretic framework to understand how behavioral responses impact epidemics. It provides a mechanistic explanation for phenomena like "Fear Drift" and dynamic herd immunity, validated with COVID-19 data. This approach could improve epidemic modeling and public health interventions.

Original Abstract

We present a unified theoretical model relating stochastic microscopic epidemic dynamics with macroscopic non-linear population behavior. Utilizing the Doi-Peliti formalism, we model the pathogen as a gauge mediator field coupled to susceptible and infected host populations, and introduce a Reactive Immunity Field capable of spontaneous symmetry breaking. We demonstrate that the naive epidemic vacuum is destabilized by radiative loop corrections via the Coleman-Weinberg mechanism, generating a dynamic herd immunity threshold. By extracting the classical saddle-point limit of the Effective Action, we derive the macroscopic reaction-diffusion equations governing the host population. We show that integrating out the gauge mediator inherently generates a thermodynamic Free Energy dependent on the square of the susceptible density. This non-linearity produces a macroscopic spatial ``Fear Drift'' proportional to the magnitude of the immunity field, and a cubic shielding penalty in the effective reproductive number ($R_{eff}$). In this work, we establish a mapping between fundamental field-theoretic mechanisms and specific terms in the macroscopic behavioral equations. We demonstrate that Debye screening is physically executed by the spatial cross-diffusion fluxes driving host evacuation. Simultaneously, vacuum polarization manifests as a non-linear cubic penalty ($-S^3 I$) in the dressed reaction rate that dynamically suppresses the effective reproductive number. As a validation of our model, we apply the formalism to high-resolution spatiotemporal COVID-19 data from Germany.

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