Spatiotemporal Characteristics of COVID-19 Epidemic in the United States

Wang, Yun; Liu, Ying; Struthers, James; Lian, Min

BACKGROUND: A range of near-real-time online/mobile mapping dashboards and applications have been used to track the COVID-19 pandemic worldwide. It remains unknown about small area-based spatiotemporal patterns of COVID-19 in the United States. METHODS: We obtained county-based counts of COVID-19 cases confirmed in the United States from January 22 to May 13, 2020 (N=1,386,050). We characterized the dynamics of COVID-19 epidemic through detecting weekly hotspots of newly confirmed cases using Spatial and Space-Time Scan Statistics and quantifying the trends of incidence of COVID-19 by county characteristics using the Joinpoint analysis. RESULTS: Along with the national plateau reached in early April, COVID-19 incidence significantly decreased in the Northeast (estimated weekly percentage changes [EWPC]: -16.6%), but remained increasing in the Midwest, South and West Regions (EWPCs: 13.2%, 5.6%, and 5.7%, respectively). Higher risks of clustering and incidence of COVID-19 were consistently observed in metropolitan vs rural counties, counties closest to core airports, most populous counties, and counties with highest proportion of racial/ethnic minority counties. However, geographic differences in the incidence have shrunk since early April, driven by a significant decrease in the incidence in these counties (EWPC range: -2.0% – -4.2%) and a consistent increase in other areas (EWPC range: 1.5% – 20.3%). CONCLUSIONS: To substantially decrease the nationwide incidence of COVID-19, strict social distancing measures should be continuously implemented, especially in geographic areas with increasing risks, including rural areas. Spatiotemporal characteristics and trends of COVID-19 should be considered in decision-making on the timeline of re-opening for states and localities.