In Poverty During a Pandemic

This project will investigate the relationship between poverty and COVID-19 using statistical and spatial analysis. The goal of this project will be to assess whether poverty increases the risk for catching COVID-19 and dying from COVID-19.

"Yet some public health experts contend that social and economic conditions ― long overlooked by government leaders, policymakers and the public ― are even more powerful indicators of who will survive the pandemic. A toxic mix of racial, financial and geographic disadvantage can prove deadly." - USA Today

Policy makers knew that areas where people already live sicker and die younger than affluent communities were more likely to suffer during a pandemic (USA Today). As of yet, little has been done to help those who need it most. Low-income Individuals are less likely to seek out care until they are dealing with severe symptoms and need to be seen. This is in addition to being more likely to have pre-existing conditions that put them at higher risk for death due to COVID-19 including heart disease, diabetes, and hypertension (Washington Post).

Many low-income jobs do not offer paid sick leave or health insurance and, as a result, the poor have to choose between missing a paycheck or risking their lives.

With no immediate federal relief like rental assistance and suspensions of debt collection and evictions, the poor will be disproportionately affected by coronavirus (United Nations).

• Are U.S. counties with higher poverty rates more at risk of COVID-19 spread than countries with lower poverty rates?

• Are counties with higher poverty rates experiencing more deaths due to COVID-19?

• COVID-19 cases and deaths will be directly correlated with poverty rates by county.

We started off by collecting data on total COVID-19 cases and deaths by county from the CDC and USAFact Sheets. These data tables were input into ArcGIS Pro for initial analysis. We created new attribute fields for calculating percentage COVID-19 cases/deaths per county and for COVID-19 cases/deaths per 100,000 per county.

We did a table join with a U.S. county shapefile after creating a unique identifier for combining states and counties correctly.

Two choropleth maps were created in order to visualize the spatial distribution of COVID-19 cases/deaths per 100,000 by county (see below).

We conducted a statistical analysis in Excel using the same tables from the CDC and USAFact Sheets. To test for a relationship between poverty and COVID-19 cases/deaths, we did a Pearson's Correlation Test.

To visually analyze the relationship between COVID-19 cases/deaths and poverty, we created a linear regression model and calculated the R-squared value.

Lastly, we created two bivariate choropleth maps, one for COVID-19 cases and poverty and another for COVID-19 deaths and poverty.

Our analysis indicates that there is a positive correlation between poverty and COVID-19 cases and deaths at the county level within the US. This correlation is low as indicated by the results from the Pearson's Correlation Test. A low correlation coefficient is likely due to the variety of risk factors that influence contracting and dying from COVID-19. However, we can use the bivariate choropleth maps to identify specific areas where poverty and COVID-19 cases/deaths are high and compare them to areas where poverty is high, but COVID-19 cases/deaths are low. This information can aid politicians, city planners, and healthcare professionals in creating policy and programs that are targeted to the specific needs of the community.

There is no doubt that this pandemic has exacerbated the vulnerabilities of resource-strapped minorities, making it critical to remember that while studies have shown COVID-19 transmission is high in poor communities, poverty does not affect all demographics equally.

The highest poverty rate by race is with Native American (25.4%), Black (20.8%), and Hispanic (17.6%). These percentages mirror the statistics of deaths due to COVID-19 seen in each racial group.

“COVID-19 Deaths Analyzed by Race and Ethnicity.” APM Research Lab, www.apmresearchlab.org/covid/deaths-by-race.

Smialek, Jeanna. “Poor Americans Hit Hardest by Job Losses Amid Lockdowns, Fed Says.” The New York Times, The New York Times, 14 May 2020, www.nytimes.com/2020/05/14/business/economy/coronavirus-jobless-unemployment.html.

Szabo, Liz, and Hannah Recht. “The Other COVID-19 Risk Factors: How Race, Income, ZIP Code Can Influence Life and Death.” USA Today, Gannett Satellite Information Network, 25 Apr. 2020, www.usatoday.com/story/news/health/2020/04/22/how-coronavirus-impacts-certain-races-income-brackets-neighborhoods/3004136001/.

“The Population of Poverty USA.” Poverty Facts | Poverty USA, www.povertyusa.org/facts.

Thebault, Reis, et al. “The Coronavirus Is Infecting and Killing Black Americans at an Alarmingly High Rate.” The Washington Post, WP Company, 7 Apr. 2020, www.washingtonpost.com/nation/2020/04/07/coronavirus-is-infecting-killing-black-americans-an-alarmingly-high-rate-post-analysis-shows/?arc404=true.

Theoharis, Liz. “Inequality and Poverty Were Destroying America Well Before Covid-19.” The Nation, 22 Apr. 2020, www.thenation.com/article/society/inequality-and-poverty-were-destroying-america-well-before-covid-19/.

US Census Bureau. “About.” The United States Census Bureau, 12 May 2016, www.census.gov/topics/income-poverty/poverty/about.html.

“US COVID-19 Strategy Failing the Poor, Says UN Expert.” OHCHR, www.ohchr.org/EN/NewsEvents/Pages/DisplayNews.aspx?NewsID=25798&LangID=E.

USAFacts. “Coronavirus Live Map: US Coronavirus Cases by County.” USAFacts, USAFacts, 7 June 2020, usafacts.org/visualizations/coronavirus-covid-19-spread-map/.