Effectively identifying communities in need of public health resources is critical for addressing health disparities. However, clear strategies for doing so and prioritizing resources are not well established. As area-based socioeconomic measures (ABSMs), which include indices that capture determinants of health for a specific geographical unit, increasingly gain traction for guiding policy and resource allocation, it is essential to understand how different ABSMs perform in relation to health outcomes of interest. This proof-of-concept study illustrates an approach to compare how different ABSMs as place-based indicators are associated with disease outcomes. Using monthly COVID-19 public health surveillance data for 2020-2021 at the census tract level in California, we qualitatively and quantitatively compare five prominent ABSMs: California Healthy Places Index, Area Deprivation Index, Social Vulnerability Index, Index of Concentration at the Extremes, and Home Owners’ Loan Corporation (HOLC) “redlining” grades. Our findings demonstrate that no single ABSM consistently aligned with COVID-19 case and mortality rates across geographies or time, highlighting the importance of selecting measures based on context, data availability, data quality, and the specific health outcome of interest. Moreover, our analysis revealed that associations between poor health outcomes and proxy measures for historical disinvestment and racial discrimination suggest these patterns are important to identify when developing equitable public health strategies. This work underscores the potential for public health decision-makers and implementers to use both qualitative and quantitative approaches to select among ABSMs for targeting interventions more effectively.

The authors acknowledge funding from the National Foundation for the Centers for Disease Control and Prevention and the California Equitable Recovery Initiative (CERI). ATK acknowledges funding from the UCSF Division of Pulmonary and Critical Care Medicine T32 Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The authors acknowledge funding from the National Foundation for the Centers for Disease Control and Prevention and the California Equitable Recovery Initiative (CERI). ATK acknowledges funding from the UCSF Division of Pulmonary and Critical Care Medicine T32 Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The findings and conclusions in this article are those of the authors and do not necessarily represent the views or opinions of the California Department of Public Health (CDPH) or the California Health and Human Services Agency.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Analyses conducted were considered exempt from the State of California Health and Human Services Agency's Committee for the Protection of Human Subjects (Project #2023-193), as data and results were considered essential components of California Department of Public Health public health surveillance.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

ABSM data utilized in in these analyses are available with analytic code at: https://github.com/Cesariddle/Index-Comparison-Analysis. Monthly time-series data of COVID-19 outcomes at the census tract level are considered protected public health data. Investigators interested in accessing this data should contact the corresponding author to discuss the process for developing a data use agreement and accessing the data.

https://github.com/Cesariddle/Index-Comparison-Analysis