Open AccessGeographical patterns of social cohesion drive disparities in early COVID infection hazard
Author(s) -
Loring J. Thomas,
Peng Huang,
Fan Yin,
Junlan Xu,
Zack W. Almquist,
John R. Hipp,
Carter T. Butts
Publication year - 2022
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2121675119
Subject(s) - cohesion (chemistry) , covid-19 , geography , demography , sociology , biology , virology , medicine , outbreak , infectious disease (medical specialty) , disease , chemistry , organic chemistry , pathology
The uneven spread of COVID-19 has resulted in disparate experiences for marginalized populations in urban centers. Using computational models, we examine the effects of local cohesion on COVID-19 spread in social contact networks for the city of San Francisco, finding that more early COVID-19 infections occur in areas with strong local cohesion. This spatially correlated process tends to affect Black and Hispanic communities more than their non-Hispanic White counterparts. Local social cohesion thus acts as a potential source of hidden risk for COVID-19 infection.