Spatial correlations in geographical spreading of COVID-19 in USA

TL;DR

This study analyzes the spatial correlations of COVID-19 spread in the USA at the county level, revealing how urban travel facilitated long-range transmission and identifying key transition points during the epidemic.

Contribution

It introduces a detailed analysis of spatial correlation lengths over time and identifies percolation transitions linked to epidemic peaks in the USA.

Findings

Correlation length was large even during case declines

Urban centers showed stronger correlations than rural areas

Identified percolation transition in November 2020 and January 2021

Abstract

The global spread of the COVID-19 pandemic has followed complex pathways, largely attributed to the high virus infectivity, human travel patterns, and the implementation of multiple mitigation measures. The resulting geographic patterns describe the evolution of the epidemic and can indicate areas which are at risk of an outbreak. Here, we analyze the spatial correlations of new active cases in USA at the county level and characterize the extent of these correlations at different times. We show that the epidemic did not progress uniformly and we identify various stages which are distinguished by significant differences in the correlation length. Our results indicate that the correlation length may be large even during periods when the number of cases declines. We find that correlations between urban centers were much more significant than between rural areas and this finding indicates that long-range spreading was mainly facilitated by travel between cities, especially at the first months of the epidemic. We also show the existence of a percolation transition in November 2020, when the largest part of the country was connected to a spanning cluster, and a smaller-scale transition in January 2021, with both times corresponding to the peak of the epidemic in the country.