社会资本对地方层面 COVID-19 结果的影响。
Social capital's impact on COVID-19 outcomes at local levels.
机构信息
Political Science Department, Northeastern University, Boston, MA, 02115, USA.
Security and Emergency Services Department, Embry-Riddle Aeronautical University, Daytona Beach, FL, 32114, USA.
出版信息
Sci Rep. 2022 Apr 21;12(1):6566. doi: 10.1038/s41598-022-10275-z.
Over the past thirty years, disaster scholars have highlighted that communities with stronger social infrastructure-including social ties that enable trust, mutual aid, and collective action-tend to respond to and recover better from crises. However, comprehensive measurements of social capital across communities have been rare. This study adapts Kyne and Aldrich's (Risk Hazards Crisis Public Policy 11, 61-86, 2020) county-level social capital index to the census-tract level, generating social capital indices from 2011 to 2018 at the census-tract, zipcode, and county subdivision levels. To demonstrate their usefulness to disaster planners, public health experts, and local officials, we paired these with the CDC's Social Vulnerability Index to predict the incidence of COVID-19 in case studies in Massachusetts, Wisconsin, Illinois, and New York City. We found that social capital predicted 41-49% of the variation in COVID-19 outbreaks, and up to 90% with controls in specific cases, highlighting its power as diagnostic and predictive tools for combating the spread of COVID.
在过去的三十年中，灾害学者强调，具有更强社会基础设施的社区——包括能够建立信任、互助和集体行动的社会关系——往往能够更好地应对和从危机中恢复。然而，对社区的社会资本进行全面衡量的情况却很少见。本研究将 Kyne 和 Aldrich（风险、危害、危机和公共政策，第 11 卷，第 61-86 页，2020 年）的县级社会资本指数应用于普查区层面，从 2011 年到 2018 年，在普查区、邮政编码和县级细分层面生成社会资本指数。为了向灾害规划者、公共卫生专家和地方官员展示其有用性，我们将这些指数与疾病预防控制中心的社会脆弱性指数相结合，以预测马萨诸塞州、威斯康星州、伊利诺伊州和纽约市的 COVID-19 病例研究中的 COVID-19 发病率。我们发现，社会资本预测了 COVID-19 爆发的 41-49%的变化，在特定情况下，通过控制变量，最高可预测 90%，这凸显了其作为诊断和预测工具在抗击 COVID 传播方面的强大作用。
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