County level sociodemographic risk factors associated with COVID-19 frequency and mortality

In just one year, COVID-19 has killed more than 400,000 Americans, and captured more than 24 million others. But a new study shows just how unfair these deaths and cases have played out across the country.

He finds that the population of the county was the worst before the epidemic, with the highest numbers of coronavirus in spring and summer.

That level of disadvantage, measured at a standard scale called the Social Vulnerability Index (SVI), closely followed the number of cases and deaths per 100,000 residents in each county, according to a new University of Michigan study.

The ten-point SVI score combines many measures of county population social disadvantage, with higher scores implying greater disadvantage. For every higher point on the ten-point SVI scale, counties had a 14% higher case of COVID-19 cases, and a 14% higher number of deaths per 100,000 people, the team reports. Open JAMA Network.

That translates to 87 additional COVID-19 cases per 100,000 people, and 3 additional COVID-19 deaths per 100,000 people, for each step up the SVI scale.

Cases also rose faster in higher-SVI counties than in lower SVI ones in the months the researchers analyzed, from late March to the end of July 2020.

With half of all COVID-19 cases coming from a virus transmitted by people who have no symptoms, the findings have a significant impact on Americans as a whole, say the researchers from the UM Institute for Policy and Healthcare Innovation.

These findings highlight that inequality and social inequality, and its role in stimulating the spread of coronavirus, is a problem that affects us all, though no matter where we live. This evidence contradicts the notion that COVID-19 mainly affects just one set of people in one type of area. “

Renuka Tipirneni, MD, M.Sc., lead author of the study

She said, “While the first increase was largely in urban areas with high percentages of Black and Latinx residents, as time went on there were some of the highest rates of cases and deaths in rural areas with predominantly white populations. But across the board, we found that the areas most affected by the disease were associated with higher levels of social disadvantage. “

The SVI, which is reflected in everything from income, language and education to housing, race and disability, is measured by the Centers for Disease Control and Prevention based on data from the National census.

Higher incidence and mortality rates were also observed in areas with higher levels of measures not included in the standard SVI, such as obesity, high mobility, food insecurity and uninsured adults. Cheers.

Tipirneni, a primary care physician in the Department of Medicine within the UM School of Medicine and a health services researcher who has worked in a variety of health care settings, worked with the first author and senior statistician Monita Karmakar, Ph.D., MS for data analysis. Coauthor Paula Lantz, Ph.D., associate professor and dean at UM’s UM School of Public Policy, helped evaluate the policy impact of the decisions.

“Our findings show that pockets of inequality are ubiquitous in America, and play a major role in the pandemic that affects us. all while interacting with each other, “Karmakar said.

Most factors associated with higher effects

The team looked at how SVI and other social measures related to 4.3 million cases and 147,074 deaths were reported in the first 6 months of the pandemic in the US. They reported a difference in population density and COVID test levels.

The team then analyzed the SVI for each county. The ten-point score, expressed in terms of scores from 0.1 to 1.0, melts measures that include poverty rate, income and level of education, type of housing, English ability , lone parent families, percentage of people over 65 or younger. , access to a personal vehicle, percentage of ethnic and minority ethnic population, and disability.

Digging down into the individual factors that made up the social vulnerability index, the researchers found that the percentage of racial and ethnic minorities was highest in the county population, and as the higher the percentage of people with limited English skills, the higher the COVID-19 case and mortality rates. The counties that measured the highest on these factors had a 22% increase in case rate for all points up their overall SVI score, and a 17% increase in death rate.

The percentage of the population living in overcrowded or lone parent households was also associated with higher incidence and mortality rates.

Looking at factors not included in the official SVI, the researchers found many links with COVID-19. Interestingly, the collection of health care facilities available in the county did not seem to make much of a difference, although Tipirneni warns, as more hospitals are overcrowded. COVID-19 patients in the fall and early winter levels, that may have changed.

However, with higher levels of obesity among county residents, the more adults who did not have health insurance, the more adults rely on public transport to get to and from work, and the more people with an unstable food supply, the higher the levels of COVID-19 Cases and deaths.

Most affected counties

Of the 3,137 counties surveyed, Trousdale County, Tennessee came in as the county with the highest incidence of COVID-19 cases during the study period, with 16,348 cases per 100,000 people by the end of July 2020. This was linked mostly to a COVID- 19 spring uprising that sickened more than 1,300 residents at a correctional center located there. This helped explain his high case despite having an SVI score of 0.52, near the middle of the scale.

But the next four counties with the highest COVID-19 case rates since January through July were all significantly higher on the SVI scale, including Lake County, TN and Lee County, Arkansas with scores SVI over 0.9. Dakota County, Nebraska (0.86) and Buena Vista County, Iowa (0.74), came fourth and fifth. The latter two are also rural counties with small numbers that are home to a prison that was the center of a major revolution.

The county with the highest death rate, Hancock County, Georgia, received an overall SVI score of 0.80, with a population of 8,000 people seeing a high number of foster home deaths. The top four counties – three in Georgia, and one in New Mexico – scored SVI above 0.9.

The survey team intends to make a complete list of the SVI scores and COVID-19 frequency and mortality rates for each county in the study available online.

The study did not include data from for U.S. districts, or for New York City because at the time of the analysis, the city did not release county-level data for the five counties that make it up. However, the authors analyzed what looked at New York City data as if it were a single county, and found that it did not alter their results.

Policy implications

The authors note that the new findings support the broader importance of “health social decisions” – above factors about a person’s life situation that cause differences in the his risk in terms of health conditions. Such decisions are known to put someone at a higher risk of the conditions that would put them at higher risk of developing a severe case of COVID-19 if they get the disease, including diabetes, high blood pressure and lung disease.

Countries with high SVI scores are likely to have higher percentages of critical workers in frontline jobs. They are also likely to increase the number of people living in households and commuting to work in situations that make it difficult for the social distance and isolation of the sick.

“The long-term inequality caused by the social vulnerability scores is likely to increase in the hardest counties due to the pandemic,” says Lantz. “The fascinating Catch-22 of the COVID-19 pandemic is that its economic and social consequences are going to exacerbate social inequality and social vulnerability at the community level. Equality education and health insurance to reduce the social inequalities that drive all forms of health inequalities, including COVID-19. “

As policymakers address key causes, immediate effects and downstream impacts of the identified inequalities, the researchers hope the new findings will help them to focus their efforts.

Immediate efforts could include public outreach initiatives aimed at people with lower English language ability, focused efforts to expand COVID-19 testing, treatment and vaccination in the most severe areas , and coordinated housing and food assistance among government and non-profit service organizations.

The team previously measured COVID-19 frequency and mortality rates with SVI for Michigan counties, and provided the data to the state. It was shared with the state action group targeting COVID-19 test sites and other services.

In the meantime, the team hopes that future research could look at even smaller geographical areas, down to the community, ZIP code or Census trail level, as well as data on the types jobs that people work in a particular area. New efforts by the Agency for Healthcare Research and Quality, and the local social vulnerability resources from the University of Wisconsin and the Robert Wood Johnson Foundation, may help further efforts to study and implement benefit disparities.