COVID-19 Resources

Using the Methods of the Public Health Disparities Geocoding Project to Monitor COVID-19 Inequities and Guide Action for Health Justice


The COVID-19 pandemic is once again pointing to the need for systematic monitoring and analysis of health inequities – especially in a context of health data lacking social and economic information – to guide both understanding and action. In our latest publications, we have been using the methods of the Public Health Disparities Geocoding Project to document inequities in the population distribution of COVID-19 cases, hospitalizations, and deaths in the United States. In this update to our website, we provide the following resources, to assist others in carrying out this vital work – to clarify who, in what communities, are being hit hardest by COVID-19, and hence where:

(a) resources for testing, screening, and prevention (including adequate provision of personal protective equipment, especially for essential workers at their jobs and for use in transportation to & from these jobs) are urgently needed;

(b) locales to assist self-isolation of people who are positive should be based (e.g., if it is not possible for people to self-isolate at home, given household crowding); and

(c) support is needed to assist people with COVID-19 & their families, especially if they are in communities and social groups already burdened inequitably by premature morbidity and mortality from chronic diseases which exacerbate the severity of COVID-19.

We provide below our relevant conceptual and empirical publications.

We also provide an ACS/ABSM variable table that lists the relevant area-based socioeconomic measures we constructed using 5-year (2014-2018) US Census American Community Survey data which we supply here at the county, ZCTA (ZIPcode tabulation area), and census tract levels (for the entire United States). We request that if you use these data, please cite this webpage.

Lastly, we provide code in R to:

— Prepared by Nancy Krieger, Jarvis T. Chen, Pamela D. Waterman (May 15, 2020)

Definitions and Source Variables from the American Community Survey

Total Population B01003_001E
White Non-Hispanic Population B01001H_001E
% of persons below poverty* B17001_002E / B17001_001E
Index of Concentration at the Extremes (high income white households versus low income black households)* ((B19001A_014E + B19001A_015E + B19001A_016E + B19001A_017E) – (B19001B_002E + B19001B_003E + B19001B_004E + B19001B_005E)) / B19001_001E
Index of Concentration at the Extremes (high income white non-Hispanic households versus  low income people of color households)** (B19001H_014E + B19001H_015E + B19001H_016E + B19001H_017E) – [(B19001_002E + B19001_003E + B19001_004E + B19001_005E) – (B19001H_002E + B19001H_003E + B19001H_004E + B19001H_005E)]/ B19001_001E
% crowding (>1 person per room) (B25014_005E + B25014_006E + B25014_007E + B25014_011E + B25014_012E + B25014_013E) / B25014_001E
% population of color (not White Non-Hispanic) B01003_001E -B01001H_001E) / B01003_001E

* To see more about US census tract poverty data and the cut-point for poverty areas defined by the US census as >=20% below poverty, see the US Census Bureau Changes in Poverty Rates and Poverty Areas Over Time: 2005-2019.

**High-income refers to the top quintile for US household income and low-income refers to the bottom quintile for US household income, during the years specified.




COVID-19 Publications

Publications re: Use of Index of Concentration at the Extremes (ICE) Measures:

Please cite as:
Krieger N, Chen JT, Waterman PD. Using the methods of the Public Health Disparities Geocoding Project to monitor COVID-19 inequities and guide action for social justice. Available as of May 15, 2020 at: