  In this study, we construct a series of evolving epidemic networks by
measuring the correlations of daily COVID-19 cases time series among 3,105
counties in the United States. Remarkably, through quantitative analysis of the
spatial distribution of these entities in different networks, we identify four
typical patterns of COVID-19 transmission in the United States from March 2020
to February 2023. The onsets and wanes of these patterns are closely associated
with significant events in the COVID-19 timeline. Furthermore, we conduct
in-depth qualitative and quantitative research on the spread of the epidemic at
the county and state levels, tracing and analyzing the evolution and
characteristics of specific propagation pathways. Overall, our research breaks
away from traditional infectious disease models and provides a macroscopic
perspective on the evolution in epidemic transmission patterns. This highlights
the remarkable potential of utilizing complex network methods for macroscopic
studies of infectious diseases.
