A National Neighborhood Data Resource to Understand Inequities in the Health and Socioeconomic Impacts of COVID-19 in the United States

COVID-19大流行导致美国社区发生了重大变化， 开始被阐明。永久关闭的企业过多，特别是 最容易受到社会距离影响的小型社区企业，如当地的理发店和美甲店， 院. 2021年9月下旬爆发的COVID-19疫情导致2，000所社区学校关闭， 在39个州平均为6天。一个迅速发展的研究机构试图了解 这些趋势，侧重于个人层面的传染病传播或 业务水平。没有考虑的是这些变化发生的背景。根据上下文，我们 指的是一个拥有机会、限制、风险和灵活性的邻里社区环境 大流行后的增长，包括对社交距离保持强劲的商业部门的就业机会; 全面的宽带互联网接入，以促进远程医疗、在线教育、远程工作和在线 杂货店购物;公园和步行街道，以促进社交距离的身体活动和社交 互动，以减轻大流行病造成的社会孤立;以及通过 替代医疗保健提供者和药房的可用性。获得这些社区资源是 在美国各地分布不均，加剧了包括老年人在内的弱势群体的风险， 儿童和青少年、少数民族和农村地区的儿童和青少年。然而，由于缺乏国家、 当地邻里环境的标准化、纵向指标阻碍了识别 哪些社区最容易受到大流行病的直接和长期后果的影响， 一系列行为、心理、社会和经济结果。为了解决这个限制，在国家的 数据基础设施，我们将增加，策划和传播我们的国家邻里数据的数据 档案（NaNDA），其中包括丰富的物理，社会和经济特点的地方 美国各地的社区（例如，种族隔离，商业密度，环境危害， 宽带互联网接入和医疗保健可用性）。我们 将与COVID-19社会、行为和经济研究联盟合作， 共享和分析空间参考邻域数据，这些数据可轻松链接到现有测量数据， 队列研究或不同地理水平的电子健康记录。我们将与新冠肺炎 联盟协调中心，以确定和创建作为研究优先事项的关键邻里指标 联盟中的团队，包括一组关于社会，行为和 社区层面的COVID-19疫情经济指标。我们还将制定新的衡量标准， 大流行前几十年的纵向邻里变化，这可以告知社区风险 和复原力。

The COVID-19 pandemic has resulted in substantial changes to American neighborhoods in ways that are only beginning to be elucidated. There has been an excess of permanent business closures, particularly among small neighborhood businesses most vulnerable to social distancing, such as local barber shops and nail salons. COVID-19 outbreaks in late September 2021 caused 2,000 neighborhood schools to close for an average of six days in 39 states. A burgeoning body of research has tried to understand the forces driving these trends, focusing on infectious disease transmission at the individual level or economic models at the business level. What is not considered is the context in which these changes are taking place. By context, we mean the neighborhood community environment that holds the opportunities, restrictions, risks, and flexibility for post-pandemic growth, including job opportunities in business sectors robust to social distancing; comprehensive broadband internet access to facilitate telemedicine, online schooling, remote work, and online grocery shopping; parks and walkable streets to facilitate socially distanced physical activity and social interaction to mitigate social isolation brought on by the pandemic; and the provision of medical care through the availability of alternate health care providers and pharmacies. Access to these neighborhood resources is not equally distributed across America, reinforcing risk for vulnerable populations, including older adults, children and adolescents, racial/ethnic minorities, and those in rural areas. However, a lack of national, standardized, longitudinal metrics of the local neighborhood environment has hindered the ability to identify which communities are most vulnerable to the immediate and longer-term consequences of the pandemic for a host of behavioral, psychological, social, and economic outcomes. To address this limitation in the nation's data infrastructure, we will augment, curate and disseminate data from our National Neighborhood Data Archive (NaNDA), which includes a wealth of physical, social and economic characteristics of the local neighborhood across the United States (e.g., racial segregation, business density, environmental hazards, broadband internet access, and healthcare availability), in the years both before and since the pandemic. We will participate with the Consortium on Social, Behavioral, and Economic Research on COVID-19 to integrate, share, and analyze spatially referenced neighborhood data that can be readily linked to existing survey data, cohort studies, or electronic health records at various levels of geography. We will work with the COVID-19 Consortium Coordination Center to identify and create key neighborhood metrics that are priorities for research teams in the Consortium, including a set of common data elements (CDEs) on the social, behavioral and economic indicators of the COVID-19 pandemic at the neighborhood level. We will also develop new metrics of longitudinal neighborhood change in the decades preceding the pandemic, which can inform community risk and resilience since the pandemic.