New York’s Inequality Meets COVID-19

Dayeon Kim, Jiweon Kim, Namhee Kim

Project Objective

With more than 1,000 deaths within the first month of the outbreak, New York became the epicenter of America’s coronavirus crisis. It is widely known that COVID-19 is affecting the poor more than the wealthy, and people of color more than the Whites, and this polarity has been especially severe in New York.

This project aims to explore if the pandemic is an example of the health-inequity side of income and racial inequality in the city. We will visualize COVID-19 positive cases per capita at zipcode level on a map, and the correlation between the severity of COVID-19 cases and demographic features of the zipcode area, such as race, income level, and educational attainment.

Data

For this project, we combined two datasets.
1. Dataset that provides the cumulative count of New York City residents by Zipcode who tested positive for COVID-19. The cumulative counts are as of date of extraction from the NYC Health Department’s disease surveillance database. For this project, the data used takes the cumulative count as of April 17th.
2. Demographics data at zipcode level attained through the “uszipcode” database in python. This API provides demographics data including total population, racial composition of the residents, median income, and educational attainment at zipcode level.

Black and Hispanic New Yorkers Are Dying at Highest Rates from COVID-19

The above graph shows COVID19 cases by four different races over three different categories. For all three categories, which are “Non-Hospitalized”, “Non-fatal Hospitalized”, and “Deaths”, African American seems to show the highest COVID19 cases among four ethnic groups. On the other hand, Asian has significantly lower COVID19 cases among the four ethnicities especially for “Non-Hospitalized” category.

## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/sunghwapark/Desktop/DataVisFinalProj/ZIP_CODE_040114", layer: "ZIP_CODE_040114"
## with 263 features
## It has 12 fields

The Least Advantaged Zipcodes in New York City Are Suffering the Most

Hover over the zipcodes on this New York City map to find COVID-19 positive cases and demographics information at zipcode level. This interactive map shows the number of COVID-19 positive cases per 100,000 residents for each zipcode. When hovered over, it also shows information about the percentage of Black residents, percentage of residents with less than $25,000 income, and percentage of residents with less than high school diplomas. This map clearly shows that the darkest colored zipcodes tend to have significantly higher percentage of Black residents and residents who are less privileged. In areas like 11368, with the highest number of positive cases per capita, almost 40% of its residents have less than high school degrees, whereas in wealthier zipcodes like 10282 that are less infected by COVID-19, only 1.8% of its residents have less than high school degrees, and only 2% of its residents are Black.

Correlation Between COVID-19 and Income

The above graphs show that there is a negative correlation between COVID-10 cases and median income. It seems to be that for neighborhoods without space to self-isolate, a private car and a job that can be performed remotely, the chances of infection necessarily increase. The graph also shows that the neighborhood’s education level and percentage of Black residents are correlated with the impact of the corona virus. Less privileged corners of New York with more Black residents and people with less educational backgrounds had higher rates of COVID-19 cases. In order to better understand this idea, our group came up with the following visualization of a map over the series of time.

Change in COVID-19 Positive Cases in relation to Black Residents and Household Income

## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/sunghwapark/Desktop/DataVisFinalProj/ZIP_CODE_040114", layer: "ZIP_CODE_040114"
## with 263 features
## It has 12 fields

## OGR data source with driver: ESRI Shapefile 
## Source: "/Users/sunghwapark/Desktop/DataVisFinalProj/ZIP_CODE_040114", layer: "ZIP_CODE_040114"
## with 263 features
## It has 12 fields

The left map (log1) represents the log difference of positive cases in New York City through April 2nd and April 15th. The right map (log2) represents the log difference of positive cases in New York City through April 15th and May 2nd. As seen in the above visualization, there was a huge increase in Corona cases during April 2nd and April 15th. However, Since April 15th, there was a huge decline in increase in Corona cases in most areas. This can indicate that the New York City’s government’s recommendation on social distancing and wearing masks might play a role in such a decline.

Additionally, in many areas where there was a significant decline in log difference over the two periods seem to correlate with percentage of African American residing in that area and also with income. For example, areas where there was initially low log difference such as Manhattan has low percentage of African Americans and also low percentage of people who earn less than 25,000 dollars of household income. This applies similarly to the areas where there was significant drop in log difference over the two periods such as Staten Island.

Although further testing should be conducted in more precise manners and confounding variables should be controlled, it seems plausible to project an idea that neighborhoods with more Black residents, less-educated, and with less-income were hit the hardest by COVID-19.

Link to Process Book
Link to Code