A Research Note on Community Resilience Estimates: New U.S. Census Bureau Data With an Application to Excess Deaths...

Area of Science:

• Public Health
• Sociology
• Demography

Background:

• The U.S. Census Bureau developed the Community Resilience Estimates (CRE) to measure tract-level vulnerability.
• Existing vulnerability indices include the Social Vulnerability Index (SVI) and National Risk Index (NRI).
• Validation of the CRE's predictive power for public health crises is needed.

Purpose of the Study:

• To validate the U.S. Census Bureau's Community Resilience Estimates (CRE) using COVID-19 excess death data.
• To compare the predictive accuracy of CRE with demographic factors, SVI, NRI, and socioeconomic predictors.
• To assess the association between CRE risk measures and neighborhood-level mortality during the COVID-19 pandemic.

Main Methods:

• Linked Social Security Administration mortality records to CRE using administrative microdata.
• Employed machine learning techniques to analyze predictive power.
• Compared CRE quartiles against single demographic categorizations (race, age), SVI, NRI, and socioeconomic variables (poverty, unemployment).

Main Results:

• CRE quartiles demonstrated more stable predictions of COVID-19 excess deaths than race or age.
• CRE showed greater predictive power for COVID-19 excess deaths compared to SVI, NRI, poverty, and unemployment.
• A 10-percentage-point increase in a CRE risk measure correlated with one additional neighborhood death during the initial COVID-19 outbreak.

Conclusions:

• The Community Resilience Estimates (CRE) offer a more accurate predictor of community vulnerability to disasters like pandemics.
• CRE provides a more robust measure of vulnerability than traditional demographic factors or existing indices (SVI, NRI).
• The findings support the utility of CRE for public health preparedness and response planning.