We analyzed the waxing and waning patterns (“surges”) of reported SARS-CoV-2 cases from January 1, 2020 through Oct 31, 2021 in all states and provinces (n = 93) in the USA, Mexico, and Canada, and across all counties (N = 3142) in the USA. A correlation matrix of the 576 × 576 daily case incidence rates in the 50 US states generates a distinctive “checkerboard” pattern showing that the epidemic has consisted of seven distinct internally coherent spatiotemporal wave patterns, four in the first year of the epidemic, and three thus far in the second year. Geoclustering of state case rate trajectories reveals three dominant co-varying spatial clusters of similar case rate trajectories, in the northeastern, southeastern and central/western regions of the USA. The spatiotemporal patterns of epidemic year 1 have thus far been repeated (p<.001) in epidemic year 2. The “checkerboard” pattern of the correlation matrix of case trajectories can be closely simulated as three sets of interacting sine waves with annual frequencies of 1:1:2 major cycles per year, corresponding to the northeastern, central/western, and southeastern state clusters. Case incidence patterns in Mexico and Canada have been similar to nearby regions in the southern US and the northern US, respectively. Time lapse videos allow visualization of the wave patterns. These highly structured geographical and temporal patterns, coupled with emerging evidence of annual repetition of these same patterns, show that SARS-CoV-2 case rates are driven at least in part by predictable seasonal factors.Significance StatementLocal COVID-19 rates wax and wane. Often these epidemic changes are attributed to localized human behavioral factors. Our finding of highly structured continental scale spatiotemporal patterns that cross state and national boundaries, coupled with emerging evidence of annual repetition of these same patterns, shows that COVID-19 transmission is driven at least in part by seasonal factors. Other epidemic factors such as vaccine coverage rates, or emergence of new strains like the Delta variant of SARS-CoV-2 appear to modify, but not totally eclipse, these underlying seasonal patterns. COVID-19 seasonal transmission patterns are associated with, and may be driven by, seasonal weather patterns. Predictability of these patterns can provide opportunities for forecasting the epidemic and for guiding public health preparedness and control efforts.