Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity

Standard epidemiological models for COVID-19 employ variants of compartment (SIR or susceptible–infectious–recovered) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion.

Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity
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