While a number of different near-real-time online/mobile mapping dashboards and applications have been used to track COVID-19 globally, it is unknown what the small area-based spatiotemporal pattern of COVID-19 is in the US. They examined county-based counts of COVID-19 cases confirmed in the US from January to May (n = 1,386,050). They We characterised the dynamics of this epidemic by detecting weekly hotspots of newly confirmed cases using Spatial and Space-Time Scan Statistics and quantifying trends of incidence by county characteristics. By the time of publication, the pandemic had reached a plateau stage in early April and then incidence significantly decreased in the Northeast (estimated weekly percentage changes [EWPC] -16.6%), but continued to increase in the Midwest, South and West Regions (EWPCs 13.2%, 5.6% and 5.7%, respectively). There were higher risks of clustering and incidence of COVID-19 in metropolitan vs. rural counties, counties closest to core airports, the most populous counties and counties with the highest proportion of racial/ethnic minorities. The geographic differences in the incidence shrank from early April, driven by the significant decrease in the incidence in those counties (EWPCs -2.0% to -4.2%) and a consistent increase in other areas (EWPCs 1.5%–20.3%). Therefore, in order to substantially reduce the nationwide incidence of COVID-19, strict social distancing measures need to be continuously implemented, especially in geographic areas with increasing risks, including rural areas.
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