Demographics alone don’t explain COVID-19 death rates

(ORDO NEWS) — A new study from the Spatial Data Center has found associations between COVID-19 deaths and social aspects of life.

“We hope to show how geographic location affects COVID-19 outcomes,” says Susan Paykin, study author. “These outcomes are not determined by the people themselves, but rather by the conditions that determine the places in which they live.”

In a study by the Spatial Data Center, county-level data reveals the vulnerability of communities

During the pandemic, many Americans became amateur scientists, tracking local rates of disease or vaccination to decide which activities might or might not be safe. Researchers at the University of Chicago saw an opportunity to dig deeper: Using county-level data, they found that different demographics are vulnerable in different ways – often depending on their geographic location.

They found that not all members of a particular race or ethnic group in the US are affected by the same factors or experience the same effects of COVID-19. By identifying associations between COVID deaths and social determinants of health, the research team uncovered specific ways in which place shapes how people experience a pandemic.

“We know it’s not just about different demographics,” says Susan Paykin, senior research director at the University of Chicago’s Spatial Data Center. “It is the structural, economic and social factors that define these places that drive the higher rates of death and disease.”

The results of the study, published in JAMA Network Open, were derived from a cross-sectional study of 3,142 counties in the 50 US states and the District of Columbia, with a focus on black or African American, Hispanic or Hispanic, and non-Hispanic whites. The group examined these different groups and their different social backgrounds and whether they are different or similar in urban, rural and suburban areas.

According to the study, black or African American populations with high mortality rates – especially in the Southeast – were more vulnerable due to low socioeconomic status, high income inequality, limited access to quality health care, and severe housing problems.

The white populations that have experienced the highest mortality rates – most commonly in the rural Midwest – are located primarily in counties with a high percentage of the elderly who have limited access to quality health care.

The team was made up of spatial data scientists and public health researchers who are part of the Healthy Regions and Policies Lab at the University of Chicago’s Spatial Data Center. This group is working on the US COVID Atlas, a free and open source data visualization tool that integrates COVID data and community metrics.

The team observed that mortality among various minority groups was disproportionately high during the pandemic, however, available data from the Centers for Disease Control and Prevention (CDC) does not provide detailed information on race and ethnicity below the state level.

“Different groups are vulnerable in different ways,” says Qingyun Lin, a postdoctoral fellow at the center and first author of the study. “In Hispanic populations, we found that many of them have a high mortality rate in urban areas. We found that those who live in areas with a high percentage of working-age people, low insurance rates and severe housing problems are most vulnerable.”

“Our study looks at COVID mortality rates, specifically the highest death rates in the first year of the pandemic,” Peikin said. “Then we look at how this compares to where different racial and ethnic groups live and try to understand where high mortality rates disproportionately affected different groups. And what social structural factors are associated with these results?”

The researchers relied in particular on two data sources. One was county-level COVID mortality data provided by the Centers for Disease Control and Prevention, focused on the first year of the pandemic. They used county-level data from the US Census Bureau’s American Public Survey and County Health Ranking and Roadmaps, which included demographics and community contextual factors.

They examined community-level variables such as income inequality, the ratio of population to primary care physicians, avoidable hospital admissions, percentage of serious housing problems, percentage of internet access, and age distribution.

These data were then compared with previous literature data on variables that have been shown to be associated with COVID-19 mortality. The team also spoke to their colleagues working on county health rankings for more information.

The researchers hope that their work will serve as an incentive to collect and share information at a more detailed level, not only in the context of the COVID-19 pandemic, but also in the event of future pandemics or other natural disasters.

“We hope to show how location affects COVID-19 outcomes,” Peikin said. “These outcomes are not determined by people themselves, but rather by the conditions that define the places they live in.

And this has really important implications for policy and structural change, and how we frame and start preparing for the future and building a culture of equality.” health in general, for various populations in various communities in the United States”.

As a next step, the researchers intend to expand their datasets to include members of various ethnic groups. The only reason they were not included in this study is that the level of data available was not large enough to produce statistically significant results.

The current study is primarily exploratory and looks at associations. Researchers are also interested in looking more deeply into different urban, rural and suburban settings to better understand the structural factors and drivers associated with higher mortality and death rates from COVID.

The team also hopes to take a closer look at the structural and social factors that characterize very low death rates from COVID-19 in order to build a more complete picture of what makes a society resilient – ​​at least in the context of the impact of COVID.

In addition to Lin and Paykin, Dylan Halpern, Aresha Martinez-Cardoso, and Marynia Kolak, all from the University of Chicago, participated in the study.


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