JUE Insight: The geographic spread of COVID-19 correlates with the structure of social networks as measured by Facebook

We use aggregated data from Facebook to show that COVID-19 is more likely to spread between regions with stronger social network connections. Areas with more social ties to two early COVID-19 hotspots(Westchester County, NY, in the U.S. and Lodi province in Italy) generally had more confirmed COVID-19 cases by the end of March. These relationships hold after controlling for geographic distance to the hotspots as well as the population density and demographics of the regions. As the pandemic progressed in the U.S., a county's social proximity to recent COVID-19 cases and deaths predicts future outbreaks over and above physical proximity and demographics. In part due to its broad coverage, social connectedness data provides additional predictive power to measures based on smartphone location or online search data. These results suggest that data from online social networks can be useful to epidemiologists and others hoping to forecast the spread of communicable diseases such as COVID-19.

Automated summary

The use of aggregated data from Facebook shows that COVID-19 tends to spread more easily in regions with stronger social network connections. Areas that have more social ties to early COVID-19 hotspots in the U.S. and Italy had a higher number of confirmed cases by the end of March. These relationships remain significant even after taking into account geographic distance, population density, and demographics. The study suggests that social connectedness data from online platforms can be valuable for epidemiologists and others in predicting the spread of communicable diseases like COVID-19.