COVID-19 Deaths Linked to Social Determinants of Health Data

COVID-19 death rates in the US are correlated with patients’ age, race, socioeconomic status, and other social determinants of health data, according to a study led by researchers at the MIT Sloan School of Management.

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Researchers analyzed daily county-level COVID-19 death rates from April 4 to May 27 of this year. Like previous studies, the team found that African Americans and older people are more likely to die from the virus compared to Caucasians and individuals under age 65. Notably, they did not find correlations between obesity rates, ICU beds per capita, or poverty rates.

The team noted that these findings have important implications for determining who is most at risk of dying from the virus and for how policymakers respond to the pandemic.

“Identifying these relationships is key to helping leaders understand both what’s causing the correlation and also how to formulate policies that address it,” said Christopher R. Knittel, the George P. Shultz Professor of Applied Economics at MIT Sloan.

“Why, for instance, are African Americans more likely to die from the virus than other races? Our study controls for patients’ income, weight, diabetic status, and whether or not they’re smokers. So, whatever is causing this correlation, it’s none of those things. We must examine other possibilities, such as systemic racism that impacts African Americans’ quality of insurance, hospitals, and healthcare, or other underlying health conditions that are not in the model, and then urge policymakers to look at other ways to solve the problem.”

The study has been released as a Center for Energy and Environmental Policy working paper, and contains additional insights about what does and does not correlate with COVID-19.

The group also found that there was no correlation between exposure to air pollution. This contradicts earlier studies that suggested that coronavirus patients living in areas with high levels of air pollution before the pandemic were more likely to die from the infection than patients in parts of the country with less air pollution.

However, researchers did find that patients who commute via public transportation are more likely to die from the disease relative to those that telecommute. Additionally, a higher share of people not working, and therefore not commuting, have higher death rates.

“The sheer magnitude of the correlation between public transit and mortality is huge, and at this point, we can only speculate on the reasons it increases vulnerability to experiencing the most severe Covid-19 outcomes,” said Knittel.

“But at a time when many U.S. states are reopening and employees are heading back to work, thereby increasing ridership on public transportation, it is critical that public health officials zero in on the reason.”

From state to state, the proportion of Americans who have died from COVID-19 varies drastically. The statistical models created by the researchers show yield estimates of the relative death rates across states after controlling for all of the factors in their model. In the Northeast, death rates are significantly higher than in other states. Across all states, California’s death rate is the lowest.

The study also found that Americans living in counties with higher home values, higher temperature summers, and lower temperature winters are more likely to die from the virus than patients in counties with lower home values, cooler summer weather, and warmer winter weather.

This could imply that social distancing policies will continue to be necessary in places with hotter summers and colder winters.

“Some of these correlations are baffling and deserve further study, but regardless, our findings can help guide policymakers through this challenging time,” said Bora Ozaltun, a Graduate Research Assistant in the Center for Energy and Environmental Policy Research (CEEPR) lab.

“It’s clear that there are important and statistically significant difference in death rates across states. We need to investigate what’s driving those differences and see if we can understand how we might do things differently.”