Evidence for complex fixed points in pandemic data

TL;DR

This paper presents evidence that complex fixed points explain the quasi-linear growth phase in epidemic data, offering a new symmetry-based paradigm for modeling pandemic dynamics.

Contribution

It introduces a novel epidemic Renormalisation Group approach revealing complex fixed points, advancing understanding of multi-wave epidemic behavior.

Findings

Identification of quasi-linear growth as evidence of complex fixed points

Calibration of the model with COVID-19 data

A paradigm shift in epidemiological data modeling

Abstract

Epidemic data show the existence of a region of quasi-linear growth (strolling period) of infected cases extending in between waves. We demonstrate that this constitutes evidence for the existence of near time-scale invariance that is neatly encoded via complex fixed points in the epidemic Renormalisation Group approach. As a result we achieve a deeper understanding of multiple wave dynamics and its inter-wave strolling regime. Our results are tested and calibrated against the COVID-19 pandemic data. Because of the simplicity of our approach that is organised around symmetry principles our discovery amounts to a paradigm shift in the way epidemiological data are mathematically modelled.