Geometric characterization of SARS-CoV-2 pandemic events

TL;DR

This paper introduces a geometric framework to analyze and compare SARS-CoV-2 pandemic trajectories across countries, enabling classification and early warning of epidemic events through low-dimensional geometric observables.

Contribution

The study presents a novel geometric approach to characterize epidemic trajectories, providing a unified, low-dimensional system for classification and potential early warning of outbreaks.

Findings

Defined geometric observables for epidemic event classification

Applied framework to SARS-CoV-2 data across countries

Proposed a system for epidemic alert and early warning

Abstract

While the SARS-CoV-2 keeps spreading world-wide, comparing its evolution across different nations is a timely challenge of both theoretical and practical importance. The large variety of dissimilar and country-dependent epidemiological factors, in fact, makes extremely difficult to understand their influence on the epidemic trends within a unique and coherent framework. We present a geometric framework to characterize, in an integrated and low-dimensional fashion, the epidemic plume-like trajectories traced by the infection rate, $I$, and the fatality rate, $D$, in the $(I,D)$ plane. Our analysis enables the definition of an epidemiometric system based on three geometric observables rating the SARS-CoV-2 pandemic events via scales analogous to those for the magnitude and the intensity of seismic events. Being exquisitely geometric, our framework can be applied to classify other epidemic data and secondary waves, raising the possibility of designing epidemic alerts or early warning systems to enhance public and governmental responses to a rapidly emerging outbreak.