Not only are black Americans disproportionately affected by Covid-19, but they also started to succumb to it earlier than other groups. New research by Graziella Bertocchi and Arcangelo Dimico finds that the first and more harshly hit by the pandemic were black women employed as frontline workers who commute on public transport from historically ‘redlined’ blocks – areas systematically discriminated against.
Their study of race-disaggregated and geo-referenced data provided by the medical examiner’s office of Cook County, Illinois, the second most-populated county in the United States and which includes Chicago, shows that the higher vulnerability of black women is not determined by physical and demographic factors such as underlying health conditions and age. Rather is it determined by socio-economic factors, because they are overrepresented in low-pay, high-risk jobs in two key essential sectors, healthcare and transport. Black women are also more likely to reach the workplace by public transport.
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In most countries of the world, minorities are overrepresented among Covid-19 fatalities, while women are underrepresented. By looking at the intersection between race and gender, this study uncovers instead a bias against black women: while black men are affected as much as white men, black women are more affected than white women, and this is due to their lower socio-economic status. The first and more harshly hit by the pandemic are black women employed as frontline workers who commute on public transport from historically ‘redlined’ blocks – areas systematically discriminated against.
Individual-level data that link Covid-19 outcomes to socio-economic status are rare. But this study makes use of an extraordinarily detailed source of race-disaggregated and geo-referenced data provided by the medical examiner’s office of Cook County, Illinois.
The researchers combine the medical examiner’s data with US Census data on occupation by sector, public transport use, household crowding and access to health insurance – down to the block group level of disaggregation. The resulting unique dataset makes it possible to investigate jointly the racial and gendered impact of Covid-19, its timing, its determinants and its geography.
Since Cook County is the second most-populated county in the United States and includes Chicago, the third largest metropolitan area in the country, the analysis carries nationwide relevance.
Main findings:
By mid-September 2020, black individuals had died at a rate approximately 1.2 times higher than their population share. As of early April 2020, however, this rate was as high as 2.2, which implies that black individuals were the first to be hit by the virus.
Thus, not only are black Americans disproportionately affected by Covid-19, but they also started to succumb to it earlier than other groups. What the epidemiological curve discloses is an extraordinary degree of racial segregation, with different groups displaying distinct patterns even in the timing of their exposure to the epidemic.
The data uncover a bias against black women in mortality that is at odds with the well-established evidence that rather points to a male bias. This happens because black women are as vulnerable as black men, while white and Latino women are more shielded than white and Latino men respectively. To quantify, in the critical second week of April 2020, the black-white differential in excess deaths was 3 percentage points and was entirely explained by Black women.
The higher vulnerability of black women is not determined by physical and demographic factors such as underlying health conditions and age, but rather by socio-economic factors, because they are overrepresented in low-pay, high-risk jobs in two key essential sectors, healthcare and transport. Furthermore, black women are more likely to reach the workplace by public transport. No effect is found for household crowding and access to health insurance.
The researchers also show that the black woman bias is spatially concentrated in historically redlined blocks. This reveals a persistent influence of the residential racial segregation policies of the 1930s.
These findings underline the need for granular data combining Covid-19 outcomes with socio-economic information. It is only through such data that scientists can produce evidence capable of guiding effective policy responses, including priority strategies for vaccination campaigns even after the emergency will be over.
