Community Boosts Immunity? Exploring the Relationship Between Social Capital and COVID-19 Social Distancing

被引:3
作者
Gibbons, Joseph [1 ,2 ]
Yang, Tse-Chuan [2 ]
Oren, Eyal [1 ]
机构
[1] San Diego State Univ, 5500 Campanile Dr, San Diego, CA 92182 USA
[2] SUNY Albany, Albany, NY 12222 USA
关键词
COVID-19; Social capital; Social distancing; Big data; Geographically weighted regression; SELF-RATED HEALTH; MULTILEVEL ANALYSIS; TRUST; INTERVENTION; DISADVANTAGE; MODEL;
D O I
10.1007/s40980-021-00096-5
中图分类号
C921 [人口统计学];
学科分类号
摘要
The early stages of the COVID-19 pandemic required a dramatic change in social practices, including distancing from social settings, to limit its spread. While social capital has considerable potential in facilitating the adoption of these norms, it also comes with considerable limitations that potentially undermine its effectiveness. We draw upon recently released mobility data from Google, network data from Facebook, and demographic data from the 2018 American Community Survey to determine how both organizational and networked measures of social capital relate to different forms of distancing. In addition, we employ geographically weighted regression to identify how these relationships vary across the nation. Findings indicate that while both forms of social capital can positively relate to distancing, the impacts are spatially inconsistent and, in some locations, social capital can discourage distancing. In sum, more policy efforts are needed to address not only low-social capital, but also unhelpful social capital.
引用
收藏
页码:75 / 105
页数:31
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