Press Releases | Health of the population | social sciences
May 23, 2022
A study by the University of California, Irvine and the University of Washington focused on social cohesion as a factor in COVID-19 infection rates in San Francisco neighborhoods.
Social cohesion, which is normally associated with positive physical and mental health outcomes, can be a drain during a pandemic, according to new research from the University of California, Irvine, and the University of Washington.
That’s because social connections — which generally provide access to support, information, and resources — can also provide avenues of infection, particularly for vulnerable individuals.
The study, recently published in the Proceedings of the National Academy of Sciences, points to a hidden factor behind inequalities in the COVID-19 pandemic, particularly among marginalized communities living in dense urban areas.
“With this study, we aimed to better understand factors that led to differences in contagion early in the pandemic,” says lead author Loring Thomas, Ph.D. candidate in sociology at UC Irvine. “Our computational models found that communities whose members belonged to groups that were, on average, slightly more cohesive were at much higher risk of infection, especially before non-pharmaceutical interventions such as masking became widespread.”
The researchers focused on San Francisco and combined demographic and housing data from the US Census with observed cases of infection among Black, Hispanic, Asian and White racial and ethnic groups. They then used computer models to understand 1,225 trajectories – or pandemic trajectories – of individual infections that occurred before March 24, 2020.
“This paper demonstrates the power of computational modeling to advance our understanding of how small racial/ethnic differences can lead to large real-world outcomes such as we have seen in the timing of this pandemic and exposure to COVID-19,” said Co- Author Zack Almquist, assistant professor of sociology at UW.
A previous paper by this research team, published in the first year of the pandemic, used census-area demographics, simulation techniques, and COVID-19 case data to examine where and how quickly the coronavirus could spread in Seattle and 18 other major cities. The team created a new model of virus spread that shows how infection can peak faster in some neighborhoods than others, based in part on social and geographic connections.
Examining San Francisco for the latest study, the researchers found that differences in social cohesion between demographic groups — the strength of ties and a sense of solidarity among members of a community — along with other factors such as housing conditions, influenced infection rates in the first months of the pandemic.
“A key risk factor for early contagion early in the pandemic was not just having numerous contacts, but being embedded in locally coherent parts of the contact network — that is, having many contacts in a community that themselves have many contacts within it community,” said co-author Carter Butts, a professor of sociology at UC Irvine.
When the data was further broken down by race and location, the researchers found that black and Hispanic populations housed in the city center had the highest rates of infection, followed by Asian and white populations.
Butts added that these findings can also help those preparing for future emergencies to prioritize alerts or interventions for high-risk groups when outbreaks of a potentially serious disease are first detected.
Other co-authors included Peng Huang, Fan Yin, Junlan Xu, and John Hipp, all from UC Irvine. The study was funded by the National Science Foundation, the National Institutes of Health and a grant from the UCI Council on Research, Computing and Libraries.
For more information, contact Almquist at [email protected]
Adapted from a UC Irvine press release.
Keyword(s): College of Arts and Sciences • Institute of Sociology • Zack Almquist
