The data hub publishes a broad set of measures across pertinent topics such as public health, government spending, personal finances, and employment to assess the longer-term economic impact of the pandemic and the efficacy of recovery efforts. It includes indicators on health (COVID-19 cases, deaths), economy (unemployment claims, retail sales, air travel passengers, etc), standard of living (household spending, personal income, food scarcity, housing insecurity, etc), and government (federal government spending, federal reserve assets, state tax revenue, federal deficit).

Safe, reliable, and equitable water access is critical to human health and livelihoods. In this study, we present the first longitudinal analysis of household access to running water—a vital social infrastructure—in the 50 largest US cities since 1970. In the accompanying paper published in Nature Cities, results of the analysis indicate that water access has worsened in an increasing number and typology of US cities since the 2008 global financial crash, disproportionately affecting households of color. We provide evidence to suggest that a ‘reproductive squeeze’—systemic, compounding pressures on households’ capacity to reproduce themselves on a daily and societal basis—is forcing urban households into more precarious living arrangements, including housing without running water, with few signs of abating.This file—which is the supplementary data that underpins the paper—contains the microdata dataset for the manuscript "Urban Inequality, the Housing Crisis and Deteriorating Water Access in US Cities" (Nature Cities). Here, we present customized and improved Public Use Microdata Sample (PUMS) definitions used in our study that enable researchers to compare US Metropolitan Statistical Area (MSA) over time, while minimizing spatial error. The dataset also includes accompanying R code for statistical analysis of census microdata and the creation of static and dynamic spatial visualizations.Parties interested in collaborating on use of the full script may contact the corresponding author (K. Meehan).If you use this dataset or code, please cite as follows: Meehan, Katie, Jason R. Jurjevich, Lucy Everitt, Nicholas M.J.W. Chun, and Justin Sherrill. (2024). Metropolitan Geographic Definitions and Code for "Urban Inequality, the Housing Crisis and Deteriorating Water Access in US Cities.” Tucson, AZ: University of Arizona Research Data Repository. DOI: 10.25422/azu.data.25724286FUNDINGThis research and dataset were supported by a grant selected by the European Research Council and funded by UKRI Horizon Europe Guarantee (Grant No. EP/Y024265/1)For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu

Safe, reliable, and equitable water access is critical to human health and livelihoods. In this study, we undertake the first systematic and comprehensive analysis of household piped water access in the United States, with the aim of explaining drivers of infrastructural inequality in the 50 largest metropolitan areas. Drawing on statistical analysis and regression modeling of U.S. census microdata at the household scale, our analysis reveals spatial and sociodemographic patterns of racialized, class-based, and housing disparities that characterize plumbing poverty across metropolitan areas.This dataset includes relevant supplemental data for our manuscript titled, "Geographies of Insecure Water Access and the Housing-Water Nexus in U.S. Cities" (forthcoming, PNAS). Here, we present customized Public Use Microdata Sample (PUMS) definitions used in our study that make U.S. Metropolitan Statistical Area (MSA) geographies comparable over time, as well as the accompanying R code for statistical analysis of census microdata and the creation of spatial visualizations. Parties interested in collaborating on use of the full script may contact the corresponding author (K. Meehan).If you use this dataset or code, please cite as follows:Meehan, Katie; Jason R. Jurjevich; Nicholas M.J.W. Chun, and Justin Sherrill (2020): Metropolitan Geographic Definitions and Code for "Geographies of Insecure Water Access and the Housing-Water Nexus in U.S. Cities." Tucson, AZ: University of Arizona Research Data Repository. https://doi.org/10.25422/azu.data.12456536For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data-management@arizona.edu

This table contains data on the living wage and the percent of families with incomes below the living wage for California, its counties, regions and cities/towns. Living wage is the wage needed to cover basic family expenses (basic needs budget) plus all relevant taxes; it does not include publicly provided income or housing assistance. The percent of families below the living wage was calculated using data from the Living Wage Calculator and the U.S. Census Bureau, American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. The living wage is the wage or annual income that covers the cost of the bare necessities of life for a worker and his/her family. These necessities include housing, transportation, food, childcare, health care, and payment of taxes. Low income populations and non-white race/ethnic have disproportionately lower wages, poorer housing, and higher levels of food insecurity. More information about the data table and a data dictionary can be found in the About/Attachments section.