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The new coronavirus tears through areas where residents generally keep to their own small, close-knit communities. But the virus takes its time spreading in crowded cities where residents of different neighbourhoods tend to intermingle, ultimately infecting more people than in the relatively isolated areas. Moritz Kraemer at the University of Oxford, UK, and his colleagues modelled the spread of SARS-CoV-2 through communities of various sizes and population densities(B. Rader et al. Nature Med. https://doi.org/fcjk; 2020).
The researchers validated their model by comparing its output with known data on individual movements and infection rates in crowded Chinese cities such as Wuhan and less densely packed provinces in Italy. The team’s model predicts relatively short, intense spikes in COVID-19 cases in relatively uncrowded cities where residents stick to their own neighbourhoods rather than mingling freely. In crowded cities, however, people are more likely to have to cope with outbreaks that last longer than do those in the countryside. The researchers applied their model to 310 cities worldwide, and predict that those with relatively even population distributions, such as Ulaanbaatar in Mongolia, could expect a short-term explosion in cases. But more densely settled urban centres, such as Madrid, can expect more protracted outbreaks.
Published in Nature Medicine (October 5, 2020):
