How societal inequalities manifested in COVID outcomes
Newswise – Racial minorities make up about a quarter of Utah’s population, but make up a third of COVID-19 cases in the state. A similar story unfolded across the country. Why have racial minorities been unevenly affected by the COVID-19 pandemic?
Researchers are still working on the answer to this question, but a new study by University of Utah researchers, including Daniel Mendoza and Tabitha Benney, explores the hypothesis that variation in income and employment status, on a neighborhood-by-neighborhood scale, could be the reason. During the 2020 shutdowns, residents of wealthy areas in Salt Lake County, Utah, were able to stay home more than residents of less affluent zip codes, suggesting that the areas ‘essential worker’ occupations the less wealthy, who are also the largest minority populations, have put them at increased risk of contracting COVID-19. Subsequently, poorer postal codes experienced nearly ten times the COVID incidence rate of wealthy areas.
“We were shocked at the nearly ten-fold difference in the increase in the rate of contagion when comparing the groups we had defined,” says Mendoza. “I think it was a very dark moment when we realized how deep the disparities really were in our own backyard.”
The study is published in the journal COVID.
The disparities of Salt Lake County
Two factors make Salt Lake County a great site to explore the link between inequality and COVID-19 infection. First, says Benney, associate professor of political science, a dense network of traffic sensors produces extremely detailed traffic and mobility data, organized by postcode. Pair that with a similar level of COVID-19 incidence rate and demographics, work, and income, and a high-resolution picture emerges.
Second, according to Mendoza, assistant research professor in the Department of Atmospheric Sciences and visiting assistant professor in the Department of Urban and Metropolitan Planning, Salt Lake County exhibits “stark socio-economic disparities. The substantial differences in race, income and occupation are very clear and provide a solid basis for the analysis of inequalities.
The division in Salt Lake County roughly follows the I-15 freeway, which separates the county into east and west sides. The east side has a higher per capita income and percentage of white collar workers. However, the division is not strictly racial, with a more diverse northeast quadrant and a less diverse southwest quadrant in the valley.
But with COVID-19 superimposed on this socio-economic landscape, a pattern has emerged.
“The first time our team calculated the numbers,” Benney says, “we were all appalled at how much income and occupation were linked to COVID incidence rates. “
What is structural inequality?
How are income and occupation related to race? Researchers have explored this question through the prism of structural inequality, which is a system of privilege in institutions and policies that place people on an unequal basis in society. This inequality, write the researchers, “creates[s] relational models that effectively socialize and dictate how people see the world and their place in it. Inequality is seen as structural when the policies produced by the system prevent certain groups from moving forward, regardless of their actions.
In the early months of the COVID-19 pandemic, as white-collar office workers and others stayed at home, workers deemed “essential” were still on the move to run hospitals, grocery store shelves stocked and parcels moving across the country. In this case, structural inequalities at work would be those that would place racial minorities disproportionately in low-income occupations, and therefore disproportionately in the category of blue collar workers least likely to be able to stay at home during the initial lockdown. .
“The real front-line workers were a lot more diverse than expected,” Benney says. “Medical workers are the heroes for sure, but janitors, repairers and the people who have kept our homes and families healthy throughout the pandemic were, and may still, face greater risks. because of their starting point in life and the occupation they have today. . “
Evidence of the uneven effect of lockdowns on different professions and incomes comes from traffic data collected between February and June 2020 – before, during and after the main containment phase of the pandemic. Traffic has declined in zip codes with high percentages of high income, white collar and white collar residents up to 50%. But in poorer postal codes, traffic only declined by about 15%.
Statistical correlations have linked these trafficking patterns to income, occupation, and possibly COVID-19 outcomes.
“Income and occupation go hand in hand much more than race and either variable,” says Mendoza, who also holds adjunct assistant professor positions in the pulmonary division of the Faculty of Medicine and Science. principal at the NEXUS Institute. . In a place like Salt Lake City County, structural inequalities can lead to lower incomes and racially-based professional divisions.
Benney says policies such as lockdowns, which put certain populations at higher disease risk, need to be better designed and implemented in future waves of the current pandemic and beyond. “In this case, because the wealthier communities were more likely to stay at home under the Stay-Home-Stay-Safe directive in Utah, this behavior appears to have kept the risk of illness away from the more workers. wealthy, whitest, and white collar workers. , which were already more likely to bounce back from a crisis, ”she said. While the Utahns have generally benefited from the directive, she adds, designing this policy with essential low-income workers in mind can help prevent the spread of disease, improve outcomes for vulnerable populations and build a society. more resilient overall.
Faced with successive waves
Since the end of the study period in June 2020, the COVID-19 pandemic has continued with a sharp increase in the winter of 2020-21, the deployment of vaccines and the growing impact of the Delta variant. Mendoza and Benney both stress the need for policymakers to consider vulnerable populations, including those in low-income postcodes, when developing a response to the pandemic.
“Frankly, we should show our support for these people by hiding in public, getting vaccinated and looking out for our community in any way we can,” Benney said.
“Our hope is that our research provides insight into the most vulnerable and affected groups and that we can pay attention to their specific needs and care for them like they take care of the rest of us,” adds Mendoza.
Find the full study here.
Find this version here.