This article reports the outcome of a project to develop and assess a predictive model of vulnerability indicators for COVID-19 infection in Los Angeles County. Multiple data sources were used to construct four indicators for zip code tabulation areas: (1) pre-existing health condition, (2) barriers to accessing health care, (3) built environment risk, and (4) the CDC’s social vulnerability. The assessment of the indicators finds that the most vulnerable neighborhoods are characterized by significant clustering of racial minorities. An overwhelming 73% of Blacks reside in the neighborhoods with the two highest levels of pre-existing health conditions. For the barriers to accessing health care indicator, 40% of Latinx reside in the highest vulnerability places. The built environment indicator finds that selected Asian ethnic groups (63%), Latinx (55%), and Blacks (53%) reside in the neighborhoods designated as high or the highest vulnerability. The social vulnerability indicator finds 42% of Blacks and Latinx and 38% of selected Asian ethnic group residing in neighborhoods of high vulnerability. The vulnerability indicators can be adopted nationally to respond to COVID-19. The metrics can be utilized in data-driven decision making of re-openings or resource distribution such as testing, vaccine distribution and other pandemic-related resources to ensure equity for the most vulnerable.

Objective: To develop indicators of vulnerability for coronavirus disease 2019 (covid-19) infection in Los Angeles County (LAC) by race and neighborhood characteristics. Design: Development of indicators that combines pre-existing medical vulnerabilities with social and built-environment data by zip code tabulation areas (ZTCAs). Setting: Neighborhoods in LAC categorized by race/ethnicity ranked into quintiles by relative vulnerability: Non-Hispanic white; Black; Latinx: Cambodians, Hmong and Laotians combined (CHL); and Other Asians. Data Sources: AskCHIS Neighborhood Edition, American Community Survey 2014-2018, and California Department of Parks and Recreation. Main Outcome Measures: 1) Pre-Existing Health Condition, 2) Barriers to Accessing Healthcare, 3) Built Environment Risk, and 4) CDC's Social Vulnerability. Results: Neighborhoods most vulnerable to covid-19 are characterized by significant clustering of racial minorities, low income households and unmet medical needs. An overwhelming 73% of Blacks reside in the neighborhoods with the two highest quintiles of pre-existing health conditions, followed by Latinx (70%) and CHL (60%), while 60% of whites reside in low or the lowest vulnerable neighborhoods. For the Barriers to Accessing Healthcare indicator, 40% of Latinx reside in the highest vulnerability places followed by Blacks, CHL and other Asians (29%, 22%, and 16% respectively), compared with only 7% of Whites reside in such neighborhoods. The Built Environment Indicator finds CHL (63%) followed by Latinx (55%) and Blacks (53%) reside in the neighborhoods designated as high or the highest vulnerability compared to 32% of Whites residing in these neighborhoods. The Social Vulnerability Indicator finds 42% of Blacks and Latinx and 38% of CHL residing in neighborhoods of high vulnerability compared with only 8% of Whites residing these neighborhoods. Conclusions: Vulnerability to covid-19 infections differs by neighborhood and racial/ethnic groups. Our vulnerability indicators when utilized in decision-making of re-openings or resource distribution such as testing, vaccine distribution, hotel rooms for quarantine and other covid-19-related resources can provide an equity driven data approach for the most vulnerable.

This article uses data from the American Housing Survey to examine Asian American wealth through home equity, which is the most important asset held by many households. We also analyze ethnic variations in housing assets and the impact of the Great Recession on subgroups. Our analysis finds that non-Hispanic whites had greater equity than Asian Americans after adjusting for geographic differences; Chinese-born Asians have the highest and Philippine-born and Southeast Asians have the lowest home equity within ethnic variations; and the recession impacted all Asian subgroups, but affected Philippine-born Asians the most.

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