Interplay of social distancing and border restrictions for pandemics (COVID-19) via the epidemic Renormalisation Group framework

TL;DR

This paper introduces an epidemic renormalisation group framework to analyze and project the effects of social distancing and border restrictions on global COVID-19 spread, revealing the greater effectiveness of social distancing in delaying peaks.

Contribution

It presents a novel, simplified approach using renormalisation group techniques to model pandemic dynamics and assess intervention impacts across multiple regions.

Findings

Social distancing delays epidemic peaks more effectively than border restrictions.

The framework accurately reproduces observed delays in infection peaks among regions.

It offers a scalable alternative to large-scale simulations for global epidemic modeling.

Abstract

We demonstrate that the epidemic renormalisation group approach to pandemics provides an effective and simple way to investigate the dynamics of disease transmission and spreading across different regions of the world. The framework also allows for reliable projections on the impact of travel limitations and social distancing measures on global epidemic spread. We test and calibrate it on reported cases while unveiling the mechanism that governs the delay in the relative peaks of newly infected cases among different regions of the globe. We discover that social distancing measures are more effective than travel limitations across borders in delaying the epidemic peak. We further provide the link to compartmental models such as the simplistic and time-honoured SIR-like models. We also show how to generalise the framework to account for the interactions across several regions of the world, replacing or complementing large scale simulations.