Democrat and Chronicle: Report Ties Redlining in Rochester City Neighbourhoods to Susceptibility to COVID

Democrat and Chronicle, October 1, Report Ties Redlining in Rochester City Neighbourhoods to Susceptibility to COVID 

Historically redlined neighborhoods are almost three times more likely to suffer from life threatening illnesses, which now includes COVID-19.

The report uses the Centers for Disease Control and Prevention’s social vulnerability index to measure public susceptibility to various diseases and dangers, not least of all a pandemic. It correlates that index with redlining status in an attempt to measure the enduring impact of state-sanctioned discrimination in 140 American cities including racial covenants in property deeds.

As an example, one census tract in the Upper Falls neighborhood was redlined and today has higher social vulnerability than 99% of the country. Residents there are two or three times more likely to experience mental illness, obesity, diabetes or other maladies compared to those in green-coded neighborhoods.

The social vulnerability scores do not capture COVID-19 contraction directly, but zip code-level data from Monroe County shows the same pattern. Four of the five ZIP codes with the most COVID-19 cases per 100,000 residents were redlined.

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Redlining and Neighborhood Health

Before the pandemic devastated minority communities, banks and government officials starved them of capital.

Lower-income and minority neighborhoods that were intentionally cut off from lending and investment decades ago today suffer not only from reduced wealth and greater poverty, but from lower life expectancy and higher prevalence of chronic diseases that are risk factors for poor outcomes from COVID-19, a new study shows.

The new study, from the National Community Reinvestment Coalition (NCRC) with researchers from the University of Wisconsin–Milwaukee Joseph J. Zilber School of Public Health and the University of Richmond’s Digital Scholarship Lab, compared 1930’s maps of government-sanctioned lending discrimination zones with current census and public health data.

Table of Content

  • Executive Summary
  • Introduction
  • Redlining, the HOLC Maps and Segregation
  • Segregation, Public Health and COVID-19
  • Methods
  • Results
  • Discussion
  • Conclusion and Policy Recommendations
  • Citations
  • Appendix

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