COVID-19 Resources (2020)

The COVID-19 Resources (2020) are part of the Public Health Disparities Geocoding Project, which provides free, accessible resources to use geocoding and area-based social metrics (ABSMs) to improve monitoring of and action to address health inequities.

This page provides guidance on how to use the methods of the Public Health Disparities Geocoding Project to monitor COVID-19 Inequities and guide action for health justice.

Introduction

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.

Resources for using our methods to monitor and act on COVID-19 inequities

We provide 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:

• extract ABSMs from the US Census American Community Survey
• replicate the analyses we conducted in our empirical papers using these variables
• replicate excess mortality analyses by ZIPcode social metrics

Definitions and source variables from the American Community Survey

Description	Source variable
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

COVID-19 publications

Conceptual

• Krieger N, Gonsalves G, Bassett MT, Hanage W, Krumholz HM. The fierce urgency of now: closing glaring gaps in US surveillance data on COVID-19. Health Affairs Blog, April 14, 2020.
• Krieger N. COVID-19, data, and health justice. To the Point(blog), Commonwealth Fund, Apr. 16, 2020.
• Chotiner I. The interwoven threads of inequality and health. (Interview with Nancy Krieger). The New Yorker, April 14, 2020.
• Krieger N. Measures of Racism, Sexism, Heterosexism, and Gender Binarism for Health Equity Research: From Structural Injustice to Embodied Harm-An Ecosocial Analysis. Annu Rev Public Health. 2020 Apr 2;41:37-62. doi: 10.1146/annurev-publhealth-040119-094017.
• Krieger N. Living and dying at the crossroads: racism, embodiment, and why theory is essential for a public health of consequence. Am J Public Health 2016; 106:832-833.

Empirical

• Chen JT, Krieger N. Revealing the unequal burden of COVID-19 by income, race/ethnicity, and household crowding: US county vs ZIP code analyses. Harvard Center for Population and Development Studies Working Paper Series, Volume 19, Number 1. April 21, 2020.
• Chen JT, Waterman PD, Krieger N. COVID-19 and the unequal surge in mortality rates in Massachusetts, by city/town and ZIP Code measures of poverty, household crowding, race/ethnicity, and racialized economic segregation. Harvard Center for Population and Development Studies Working Paper Series, Volume 19, Number 2. May 9, 2020.
• with data used in: Ryan A, Lazar K. Disparities push coronavirus death rates higher. Harvard analysis finds mortality surged higher in communities with more poverty, people of color, and crowded housing. Boston Globe, May 9, 2020.
• Chin T, Kahn R, Li R, Chen JT, Krieger N, Buckee CO, Balsari S, Kiang SV. U.S. county-level factors relevant to COVID-19 burden and response. MedRxiv, posted April 11, 2020.

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

• Krieger N, Waterman PD, Spasojevic J, Li W, Maduro G, Van Wye G. Public Health monitoring of privilege and deprivation using the Index of Concentration at the Extremes (ICE). Am J Public Health 2016; 106: 256-253. doi: 10.2105/AJPH.2015/302955.
• Krieger N, Kim R, Feldman J, Waterman PD. Using the Index of Concentration at the Extremes at multiple geographic levels to monitor health inequities in an era of growing spatial social polarization: Massachusetts, USA (2010-2014). Int J Epidemiol 2018; 47:788-819.
• Krieger N, Waterman PD, Gryparis A, Coull BA. Black carbon exposure, socioeconomic and racial/ethnic spatial polarization, and the Index of Concentration at the Extremes (ICE). Health & Place 2015; 34:215-228.
• Krieger N, Feldman JM, Waterman PD, Chen JT, Coull BA, Hemenway D. Local residential segregation matters: stronger association of census tract compared to conventional city-level measures with fatal and non-fatal assaults (total and firearm related), using the Index of Concentration at the Extremes (ICE) for racial, economic, and racialized economic segregation, Massachusetts (US), 1995-2010. J Urban Health 2017; 94:244-258.