Summary
Summary: The purpose of this project is to develop multiple indicators that point to probable communities (geographic places defined by the Census Bureau’s Zip Code Tabulation Areas [ZCTA]) and populations at risk in Los Angeles County with high probability of COVID-19 infection and death across different dimensions. To achieve this, authors used data from California Health Interview Survey (CHIS), the U.S. Census Bureau’s American Community Survey, and the California Department of Parks and Recreation to develop a medical vulnerability index of four indicators: preexisting health vulnerability, barriers to accessing services, built environment risk, and social vulnerability.
Findings: The four indicators share commonalities but are not identical. The analyses presented in the previous sections review similarities in terms of the most vulnerable neighborhoods. For instance, the most vulnerable neighborhoods across all indicators tend to be concentrated in areas within South Los Angeles and the San Fernando Valley. These places are marked by low-income racial communities, while neighborhoods that showed up as being the least vulnerable are along the coastal regions of the county marked by less density, higher incomes and higher proportions of non-Hispanic whites.
In addition to mapping the four indicators, authors presented a quantitative analysis of the socioeconomic and demographic profiles of the most and least vulnerable neighborhoods. Consistently across all indicators, the highest vulnerable are disproportionately people of color and low income, relative to communities at the other end of the spectrum.
Authors hope that these indicators will be helpful for policy makers, local jurisdictions, foundations, and community organizations to identify areas with a high need of resources to protect against a potential second wave of COVID-19 infections.
Data from the 2015-2016 AskCHIS Neighborhood Edition were used in this project.
Read the Publication:
- Research Report: Los Angeles Neighborhoods and COVID-19 Medical Vulnerability Indicators: A Local Data Model for Equity in Public Health Decision-Making