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 ǣhotspotsǥ (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.

我们使用 Facebook 的汇总数据表明，COVID-19 更有可能在社交网络联系较强的地区之间传播。到 3 月底，与两个早期 COVID-19 热点地区（美国纽约州韦斯特切斯特县和意大利洛迪省）社会联系较多的地区通常有更多确诊的 COVID-19 病例。在控制了与热点的地理距离以及该地区的人口密度和人口统计数据后，这些关系仍然成立。随着疫情在美国的蔓延，一个县与最近的 COVID-19 病例和死亡人数的社会距离比物理距离和人口统计数据更能预测未来的疫情爆发。部分由于其广泛的覆盖范围，社交联系数据为基于智能手机位置或在线搜索数据的测量提供了额外的预测能力。