Assessment of Population-Level Disadvantage Indices to Inform Equitable Health Policy.

Policy Points The rapid uptake of disadvantage indices during the pandemic highlights investment in implementing tools that address health equity to inform policy. Existing indices differ in their design, including data elements, social determinants of health domains, and geographic unit of analysis. These differences can lead to stark discrepancies in place-based social risk scores depending on the index utilized. Disadvantage indices are useful tools for identifying geographic patterns of social risk; however, indiscriminate use of indices can have varied policy implications and unintentionally worsen equity. Implementers should consider which indices are suitable for specific communities, objectives, potential interventions, and outcomes of interest. CONTEXT: There has been unprecedented uptake of disadvantage indices such as the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to identify place-based patterns of social risk and guide equitable health policy during the COVID-19 pandemic. However, limited evidence around data elements, interoperability, and implementation leaves unanswered questions regarding the utility of indices to prioritize health equity. METHODS: We identified disadvantage indices that were (a) used three or more times from 2018 to 2021, (b) designed using national-level data, and (c) available at the census-tract or block-group level. We used a network visualization to compare social determinants of health (SDOH) domains across indices. We then used geospatial analyses to compare disadvantage profiles across indices and geographic areas. FINDINGS: We identified 14 indices. All incorporated data from public sources, with half using only American Community Survey data (n = 7) and the other half combining multiple sources (n = 7). Indices differed in geographic granularity, with county level (n = 5) and census-tract level (n = 5) being the most common. Most states used the SVI during the pandemic. The SVI, the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Child Opportunity Index (COI) met criteria for further analysis. Selected indices shared five indicators (income, poverty, English proficiency, no high school diploma, unemployment) but varied in other metrics and construction method. While mapping of social risk scores in Durham County, North Carolina; Cook County, Illinois; and Orleans Parish, Louisiana, showed differing patterns within the same locations depending on choice of disadvantage index, risk scores across indices showed moderate to high correlation (rs 0.7-1). However, spatial autocorrelation analyses revealed clustering, with discrepant distributions of social risk scores between different indices. CONCLUSIONS: Existing disadvantage indices use varied metrics to represent place-based social risk. Within the same geographic area, different indices can provide differences in social risk values and interpretations, potentially leading to varied public health or policy responses.

COVID-19 Response Strategies at Large Institutes of Higher Education in the United States: A Landscape Analysis, Fall 2020.

PURPOSE: To examine the pandemic response plans of institutes of higher education (i.e., colleges and universities), including COVID-19 prevention, enforcement, and testing strategies. METHOD: Data from the largest public (n = 50) and private (n = 50) US institutes of higher education were collected from October 30 to November 20, 2020. RESULTS: Most institutes of higher education (n = 93) offered some in-person teaching in the Fall 2020 semester; most adopted masking (100%) and physical distancing (99%) mandates. Other preventive strategies included on-campus housing de-densification (58%), classroom de-densification (61%), mandated COVID-19-related training (39%), and behavioral compacts (43%). Testing strategies included entry testing (65%), testing at regular intervals (32%), population sample testing (46%), and exit testing (15%). More private than public institutes implemented intercollegiate athletics bans, behavioral compacts, and suspension clauses for noncompliance. CONCLUSIONS: Variability in COVID-19 prevention and testing strategies highlights the need for national recommendations and the equitable distribution of sufficient pandemic response resources to institutes of higher education.

The Health of Children in Immigrant Families: Key Drivers and Research Gaps Through an Equity Lens.

OBJECTIVE: The United States benefits economically and socially from the diverse skill-set and innovative contributions of immigrants. By applying a socioecological framework with an equity lens, we aim to provide an overview of the health of children in immigrant families (CIF) in the United States, identify gaps in related research, and suggest future areas of focus to advance health equity. METHODS: The literature review consisted of identifying academic and gray literature using a MeSH Database, Clinical Queries, and relevant keywords in 3 electronic databases (PubMed, Web of Science, and BrowZine). Search terms were selected with goals of: 1) conceptualizing a model of key drivers of health for CIF; 2) describing and classifying key drivers of health for CIF; and 3) identifying knowledge gaps. RESULTS: The initial search produced 1120 results which were screened for relevance using a meta-narrative approach. Of these, 224 papers were selected, categorized by topic, and reviewed in collaboration with the authors. Key topic areas included patient and family outcomes, institutional and community environments, the impact of public policy, and opportunities for research. Key inequities were identified in health outcomes; access to quality health care, housing, education, employment opportunities; immigration policies; and inclusion in and funding for research. Important resiliency factors for CIF included strong family connections and social networks. CONCLUSIONS: Broad structural inequities contribute to poor health outcomes among immigrant families. While resiliency factors exist, research on the impact of certain important drivers of health, such as structural and cultural racism, is missing regarding this population. More work is needed to inform the development and optimization of programs and policies aimed at improving outcomes for CIF. However, research should incorporate expertise from within immigrant communities. Finally, interventions to improve outcomes for CIF should be considered in the context of the socioecological model which informs the upstream and downstream drivers of health outcomes.