Evidence for Complex Fixed Points in Pandemic Data

Mathematical models used in epidemiology to describe the diffusion of infectious diseases often fail reproduce recurrent appearance exponential growth number infections (waves). This feature requires a time-modulation some parameters model. Moreover, epidemic data show existence region quasi-linear (strolling period) infected cases extending between waves. We demonstrate that this constitutes evidence for near time-scale invariance is neatly encoded via complex fixed points Renormalization Group approach. As result, we obtain first consistent mathematical description multiple wave dynamics and its inter-wave strolling regime. Our results are tested calibrated against COVID-19 pandemic data. Because simplicity our approach organized around symmetry principles, discovery amounts paradigm shift way epidemiological mathematically modelled. period crucial controlling emergence next wave, thus encouraging maintenance (non)pharmaceutical measures during following wave.