Patterns of exposure to SARS-CoV-2 carriers manifest multiscale association between urban landscape morphology and human activity

The outbreak of the Coronavirus disease 2019 (COVID-19), and the drastic measures taken to mitigate its spread through imposed social distancing, have brought forward the need to better understand the underlying factors controlling spatial distribution of human activities promoting disease transmission. Focusing on results from 17,250 epidemiological investigations performed during early stages of the pandemic outbreak in Israel, we show that the distribution of carriers of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes COVID-19, is spatially correlated with two satellite-derived surface metrics: night light intensity and landscape patchiness, the latter being a measure to the urban landscape's scale-dependent spatial heterogeneity. We find that exposure to SARS-CoV-2 carriers was significantly more likely to occur in patchy parts of the city, where the urban landscape is characterized by high levels of spatial heterogeneity at relatively small, tens of meters scales. We suggest that this spatial association reflects a scale-dependent constraint imposed by the city's morphology on the cumulative behavior of the people inhabiting it. The presented results shed light on the complex interrelationships between humans and the urban landscape in which they live and interact, and open new avenues for implementation of multi-satellite data in large scale modeling of phenomena centered in urban environments.

Automated summary

The distribution of COVID-19 carriers in Israel during the early stages of the pandemic outbreak was found to be closely correlated with satellite-derived surface metrics, including night light intensity and landscape patchiness. Risk of exposure to the virus carriers was significantly higher in patchy parts of the city characterized by high spatial heterogeneity, reflecting a scale-dependent constraint imposed by the city's morphology on people's behavior. These results highlight the complex interrelationships between humans and the urban landscape, and suggest new avenues for utilizing multi-satellite data in large scale modeling of urban phenomena.