Utah’s young population contributes to relatively low COVID-19 death rate

Research from the Kem C. Gardner Policy Institute shows Utah’s relatively young population is contributing to a lower COVID-19 death rate than the nation as a whole. As of July 14, 2020, the CDC COVID Data Tracker reported the Utah and U.S. per-capita death rates as 7.0 and 41.3 per 100,000, respectively, a difference of 34.3. Using various decomposition methods, demographers at the Gardner Institute estimate that about 8 of those deaths per capita are attributable to Utah’s younger population, with the remaining difference being a result of other factors.

“In many ways, this analysis is more exploratory than definitive, since the provisional data are still so fresh,” said Mike Hollingshaus, senior demographer at the Gardner Institute and lead author of the brief. “But, it provides an alternative outlook on the data. This different way of thinking changes how policymakers view per-capita rates and recommends a nuanced approach to the decision-making process.”

The analysis provided instructive, but still preliminary answers to three questions:

1. What would Utah’s COVID-19 death rate be if its population had the same age structure as the U.S. population? 

If Utah had the same age structure as the U.S., its death rate would rise by nearly 50% to 10.1 per 100,000.

2. What would the U.S. rate be if its age structure were identical to Utah’s?

If the U.S.’s age structure were similar to Utah’s, its death rate would drop by nearly one-third to 28.3 per 100,000, and deaths would have numbered under 100,000 instead of over 130,000 as of July 14.

3. How much of Utah’s lower death rate is the result of the state’s younger population?

About one-quarter of Utah’s lower death rate is attributable to its younger population. The majority (three-fourths) is due to other factors.

In addition to Utah’s young population, other socioeconomic, environmental and demographic characteristics likely play a role in explaining some of the remaining differences in the state’s death rate. The state could also have a lower per-capita rate due to better prevention, response, and treatment; but that conclusion is not justified until these other factors have been accounted for in statistical models.

“Utahns should continue to proceed with caution and remember that demographics matter when combating the profound impacts of COVID-19 on our society,” said Pamela Perlich, director of demographic research at the Gardner Institute. “We hope our research can help decision-makers wisely interpret and act upon population-level metrics as they develop effective policies to combat the pandemic.”

The full research brief and methodology are now available online.

COVID-19 and the metropolis

Many have assumed that densely populated areas like city centers are more conducive to the spread of COVID-19. A new study, published in the Journal of the American Planning Association, finds that the opposite may be true. Researchers from the University of Utah and the Johns Hopkins Bloomberg School of Public Health examined both infection and death rates in 913 U.S. metropolitan counties and found that population size, not density, corresponded to mortality rates. One possible explanation could be faster and more widespread adoption of social distancing practices and better quality of health care in areas of denser population.

“Our findings run counter to the recent narrative about escaping compact cities for sprawling suburbs as a way of staying safe from COVID-19,” said co-author Reid Ewing, distinguished professor in the Department of City & Metropolitan Planning at the University of Utah. “This is one more reason for urban planners and public officials to favor compact urban development over suburban sprawl. Compact places seem to promote better adherence to social distancing and provide better acute health care, so those contracting the coronavirus are less likely to die.”

A map of the 913 U.S. metropolitan counties included in the survey.

The three-member team chose to examine county data, not individual cities, between Jan. 20-May 25, 2020. Large cities alone have multiple unknown variables. Counties, on the other hand, have multiple known factors that allowed the team to find the “activity density” of each and make comparisons. Activity density = (population of a county + jobs in the county)/area of the county.

Activity density takes into account both the county residents and workers commuting within a given area. Other factors, such as population size, education levels, and demographic variables, including age and race and health care infrastructure (ICU bed capacity), were also considered.

“Our analysis shows that metropolitan size is more important than density,” said co-author Sadegh Sabouri, doctoral student in the Department of City & Metropolitan Planning at the U. “Take Dutchess County, New York, for example, being surrounded by one of the largest metropolitan areas—New York, Newark and New Jersey City. The activity density is 518.1 and death rate of 4.63 per 10,000. Salt Lake County, by comparison, is located in a metropolitan area that is one-twentieth the population and has a density four times higher at 2060.2 and a death rate of only 0.61.”

The analysis did not indicate a significant association with infection rates. However, higher activity density did have a significant and unexpected association with death rates. They found that after controlling for factors such as metropolitan size, education, race and age, doubling the activity density was associated with an 11.3% lower death rate.

They also conclude that counties with higher proportions of people ages 60 and older, lower proportions of college-educated people, and higher proportions of African Americans experienced greater infection and mortality rates.

The researchers have been updating the data as the pandemic has progressed and are finding that the associations uncovered in their study are becoming even stronger. The team is also conducting a longitudinal study that tracks the relationships among county density, infection and mortality rates and explanatory factors as they change over time. They have found consistent results regarding the inverse relationship between density and the COVID-19 mortality rate.

Find the full study here.

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The U leads national study of COVID-19 effects on pregnancy

A University of Utah Health researcher is leading a nationwide study of the effects of the COVID-19 pandemic on women during and after pregnancy.

Torri D. Metz, an associate professor of obstetrics and gynecology, is the principal investigator of a multipronged study that will analyze the medical records of up to 21,000 pregnant women. The study, supported by the National Institutes of Health (NIH), seeks to determine if changes to health care delivery implemented in response to the pandemic have resulted in higher rates of pregnancy-related complications and cesarean delivery.

The study, conducted by researchers in the Maternal-Fetal Medicine Units (MFMU) Network, a group of 12 U.S. clinical centers including the University of Utah Hospital, will also try to establish the risk of pregnant women with COVID-19 transmitting the virus to their fetuses. Newborns will be monitored and assessed until they are discharged from the hospital.

In addition, the scientists will track the health of more than 1,500 pregnant women with confirmed cases of COVID-19 for six weeks after childbirth.

“There have been so many changes in maternal health care in the past few months, both for practitioners and expectant women themselves,” Metz says. “Their relative willingness to come in for care during this time is declining. We’re seeing more and more data nationally that women are delaying presentation for care or not coming in for care at all because they fear contracting COVID-19. That decision actually puts them at higher risk of maternal morbidity and mortality.”

Telehealth can replace much of the necessary care provided by physicians, says Metz, who is also vice chair for research at U of U Health. However, there is the potential that some complications could be missed.

Among the risk factors the researchers will track are increased incidence of high blood pressure, postpartum hemorrhage and infections. The team will analyze medical records of women who delivered children on the same randomly chosen days (April 19, for instance) in 2019 and 2020 to determine if new moms in 2020 had an increased risk of adverse outcomes. The study will run through the end of the year.

“The questions we will be addressing in this study are ones that a lot of practitioners and women who are pregnant or are considering getting pregnant are asking themselves,” Metz says. “Hopefully, this study will illuminate some of the answers so that we can better counsel women on what to expect.”

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The study is funded by the Eunice Kennedy Shiver National Institute of Child Health and Human Development (NICHD).

Utah’s spring air quality better than usual during pandemic

As stay-at-home measures went into place in March 2020, many wondered how fewer cars on the road would impact Salt Lake’s air quality. The first preliminary measurements are now in. Air quality along the Wasatch Front in March is usually good, but the reduction in emissions from COVID-19 stay-at-home measures have made air quality even better than usual.

The results here are some of the first to integrate ground-based air quality and greenhouse gas emissions with satellite observations to understand how emissions have changed .

“These measurements, taken together, paint a consistent picture of cleaner air from reduced emissions, especially from reduced traffic,” said Logan Mitchell, research assistant professor in the Department of Atmospheric Sciences at the University of Utah, who conducted the analysis using data from Utah Department of Environmental Quality (DEQ) monitoring stations. “It shows how fast the air quality improves after a reduction in emissions and suggests that as the economy starts to recover and emissions ramp up, we’re going to see our air quality get worse again.”

“For environmental scientists, this was a once-in-a-lifetime opportunity to study the air quality impacts of fewer cars on the road,” said Bryce Bird, director of the Utah DEQ’s Division of Air Quality. “We are looking forward to further analyzing the data our monitors collected during this period when residents were teleworking and driving less. Dr. Mitchell’s initial analysis shows a lot of promise and hopefully, the final results will help inform behavior and policy in the coming years.”

March air quality by the numbers

Measurements of all air pollutants come from a monitoring station at Hawthorne Elementary in Salt Lake City and additional measurements of carbon dioxide come from monitoring stations in Sugarhouse, at the U, and in the southwest Salt Lake Valley. The measurement period reported here is the last half of March since many of Utah’s stay-at-home measures were in effect by March 15.

  • NOx (oxides of nitrogen) levels were lower due to traffic reductions, especially during rush hour peaks. Nitric oxide (NO) levels were 57% lower than the average March, and nitrogen dioxide (NO2) was 36% lower than average.
  • O3 (ozone) is about the same as usual at midday but slightly elevated at night.  This is characteristic evidence of less NOxin the air and less reaction between NOx and ozone at night. It’s consistent with what scientists think urban air would look like with decreased NOemissions.
  • PM2.5 (particulate matter) is down by 41%, particularly at night. It’s not clear yet whether that’s due to reduced overall particulate matter emissions or reduced formation of particulate matter through atmospheric chemistry.
  • CO2 (carbon dioxide) levels are at 19% and 33% lower than average at the Sugarhouse and U stations, respectively.
  • SO2 (sulfur dioxide) is around typical levels. Mitchell says this isn’t surprising, as there aren’t many SO2 sources in the Salt Lake valley.

PHOTO CREDIT: Logan Mitchell

Pollutant concentrations by hour of day observed at the Utah DAQ Hawthorne site.

More analyses are forthcoming, and the data have not yet been peer-reviewed, Mitchell says. Also, analyzing the weather conditions from March 2020 will provide a more complete picture of how emissions compare to previous years.

“These results give me a lot of optimism about the future,” Mitchell said. “It shows that as we recover from the pandemic if we invest in clean energy and electric vehicles, it’s really possible to clean up the air.”

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Read the full report of preliminary results, including images, here.

Find current air quality conditions from the Utah DEQ here and measurements from stationary and mobile air quality monitors through the University of Utah here.

University of Utah invests $1.3 million in COVID-19 research

As the COVID-19 pandemic continues to spread across the globe, University of Utah scientists are at the forefront of efforts to learn more about how to lasso the virus that causes it and understand its potential long-term social, economic and psychological effects.

In a stride toward those goals, the Office of the Vice President for Research in partnership with the Immunology, Inflammation and Infectious Disease (3i) Initiative at the University of Utah has awarded $1.3 million in seed grants to 56 cross-campus projects that will examine a host of issues arising out of the pandemic.

“In just a matter of months, COVID-19 has killed more than 100,000 people worldwide, making this one of the most devastating events in recent history,” says Ryan O’Connell, Ph.D., co-director of the 3i initiative at University of Utah Health. “This bleak reality has prompted us to quickly identify and support COVID-19 focused research projects being proposed by our outstanding faculty here at the University of Utah in an effort to understand and defeat this deadly virus using a variety of innovative strategies.”

These multidisciplinary projects will not only address ways to prevent and treat the disease, but will also explore how to design better personal protective equipment as well as dampen the long-term effects of physical isolation on domestic violence and mental health. The projects are divided into six broad categories (number of grants).

Data Science and Genomic Medicine (9)

Projects that aim to make better predictions of COVID-19, and engage cutting-edge methods across artificial intelligence, genetics and mathematical modeling.

Environmental Impact and Minimizing Exposure (6)

Projects that aim to understand how our actions are impacting the environment, and how to minimize exposure to COVID-19 across settings.

Health Impacts Across Populations (12)

Projects investigating the different ways that COVID-19 impacts people from different communities.

Mental Health and the Brain (7)

Projects that explore how people are psychologically adjusting to the disruptions in everyday life.

Social Impact and Policy (5)

Projects seeking to understand how to better protect and prepare people from the unintended consequences of efforts to reduce exposure to COVID-19.

Testing and Treating COVID-19 (17)

Projects that aim to find better tests, treatment, and a cure for COVID-19.

Among the U’s schools and colleges receiving seed grants are the School of Medicine and the colleges of nursing, pharmacy, engineering, humanities, science, architecture and planning, social and behavioral sciences and mines and Earth sciences.

“We’re very excited to partner with the Immunology, Inflammation, & Infectious Disease Initiative to fund high-priority pilot projects that respond to the COVID-19 crisis,” says Diane Pataki, associate vice president for research and a professor of biological sciences at the U. “Our goal is to help researchers across campus form competitive interdisciplinary teams that will quickly respond to national funding opportunities.

The seed grants fund pilot projects that promote collaborations among research groups at the U. Seed grants provide initial support to develop preliminary data that will allow competitive applications for funding by the National Institutes of Health or other agencies and foundations.

3i was created to improve diagnosis and treatment for this diverse array of disorders. A major goal of this initiative is to integrate basic, translational and clinical research in these areas by strengthening the 3i community and fostering collaborations. The Neuroscience Initiative also contributed funding for COVID-19 seed grant projects.

For the full list of projects, go here.

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Mucus and the coronavirus

As the lethal COVID-19 coronavirus propagates around the globe, we know a sneeze, a cough or simply touching a surface with the virus can spread the infection.

What researchers don’t know is exactly the role different compositions of mucus, the slimy substance on human tissue, play in the transmission and infection of coronaviruses. Nor do they know why some people known as “super-spreaders” will spread the disease more than others. But University of Utah biomedical engineering assistant professor Jessica R. Kramer is now researching how mucus plays a part in transferring coronaviruses from person to person.

“Not everyone spreads the disease equally. The quality of their mucus may be part of the explanation,” Kramer says. “One person may sneeze and transmit it to another person, and another may not, and that is not well understood.”

She has received a one-year, $200,000 Rapid Response Research (RAPID) grant from the National Science Foundation for the research.

PHOTO CREDIT: Dan Hixson/University of Utah College of Engineering

University of Utah biomedical engineering assistant professor Jessica R. Kramer has received a new grant to research how mucins, the slimy substance in human tissue, plays a role in spreading coronaviruses such as COVID-19.

Understanding how different compositions of the proteins that make up mucus spread coronaviruses could help identify those who are “super-spreaders” as well as those who could be more vulnerable to becoming infected, says Kramer. That could lead to faster, more accurate data on who will spread the virus or more effective quarantine measures for high-risk populations. The nation’s epidemiologists have said since the arrival of COVID-19 that accurate testing to know where the infection is growing is a key factor to containing its spread.

Kramer and her team will create different forms of synthetic mucins, the proteins that make up mucus, and test them with non-hazardous versions of coronaviruses. COVID-19, which is the cause of the worldwide pandemic, is a novel coronavirus that by the end of March has so far killed more than 37,000 people since it was first discovered late last year. But it is only one of many forms of coronaviruses.

Kramer will use special aerosols in a closed environment to simulate coughing to help determine how different mucins carry the virus through the air. She will also test the viability of the virus when it lands on a surface based on the mucins that carry it. Her lab will also examine how mucin composition on the next victim’s mouth, eyes or lungs affects whether the virus makes it through the mucus into their cells to replicate.

The composition of mucus changes from person to person based on their genetics, environmental factors, or their lifestyle such as whether the person smokes or what their diet is. “It’s important that people understand that it’s not only the amount of mucus that is a factor but how the molecular composition is different,” she says.

Kramer’s lab at the University of Utah has been creating synthetic mucins and more recently studying how mucins and bacteria interact with each other. She says researching how mucins interact with viruses is a natural extension of this work.

Kramer’s award is the second NSF RAPID grant to be given to U researchers related to the spread of the COVID-19 coronavirus. Michael Vershinin and Saveez Saffarian of the U’s Department of Physics & Astronomy will study how the structure of the coronavirus withstands changes in humidity and temperature and under what conditions the virus falls apart.

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COVID-19 antibody tests can guide public health, policy decisions

It’s too soon to use COVID-19 antibody testing to issue “immunity passports,” antibody tests that are available today. But they are good enough to inform public health decisions about relaxing social distancing interventions, says an international group of infectious disease and public health experts in Science Immunology today.

“We don’t need to wait for the perfect test to monitor populations,” says University of Utah Health infectious disease physician-researcher Daniel Leung. “We can use what we have if we go in with our eyes open.” Leung is the corresponding author on the editorial together with specialists from seven different countries and leading public health institutions in the U.S., including Johns Hopkins Bloomberg School of Public Health, Harvard School of Public Health, University of California, San Francisco and Pennsylvania State University.

Today’s tests are ready for populations, not people

Some have suggested that detecting antibodies to SARS-CoV-2—the coronavirus that causes COVID-19—become the basis of “immunity passports” that enable people to return to work, school, or travel. Yet facts indicate that it is premature to take that step. Scientists have yet to determine whether the antibodies or perhaps a threshold level of antibodies, protect a person from being re-infected. In addition, there are multiple antibody tests, none with the levels of specificity needed to declare someone immune.

In short, we are far from being at a place where a positive antibody test guarantees that a person cannot get COVID-19 nor spread it to someone else, say Leung and colleagues. And the stakes are too high to risk getting it wrong.

Regardless, these same tests are good enough to monitor the spread of COVID-19 in populations. “There is no need to throw out the baby with the bathwater,” Leung says. “We can use serological testing at the population level to get valuable information about transmission and the impact of interventions—and we don’t need a perfect serology test to do it.”

Understanding trends such as where outbreaks are occurring and which regions are quiet, along with the characteristics of who is getting ill and who is protected, can provide information to guide policy. Is a specific state or county ready to ease restrictions? Are students safe to go back to school? Do certain populations need extra protection?

Fine-tuning existing tests to meet different needs

One reason many of today’s tests can work for public-level decisions is that they do not just provide black and white answers. Instead, their parameters can be adjusted to fit different needs. One of these characteristics is specificity—how well a test detects antibodies to SARS-CoV-2 and not to antibodies against other coronaviruses. The other is sensitivity—the minimum level of antibodies someone must have in their blood in order to test positive.

In general, there is a tradeoff between the two. Adjusting a test to prioritize sensitivity makes it not as specific, and making a test more specific makes it less sensitive. But, according to the editorial, it’s OK to sacrifice one for the other in order to answer certain questions.

Take the situation in a rural countryside where relatively few people per capita have had COVID-19. In that setting, a test with high sensitivity and low specificity would not be optimal. These characteristics could easily result in the same number of people testing positive who never had COVID-19 as the number of people who really are positive. In this situation, the results would be practically meaningless.

However, the same test can be used if it is tuned for that situation. This can be done by designating a higher cutoff and saying that a test does not count as positive unless it has a stronger signal. Doing so lowers the false positive rate by increasing specificity. In this scenario, positive tests are more likely to be truly positive—and that data can be safely used to monitor that population.

On the other hand, an urban setting where higher proportions of the population have been infected would do better with a test prioritized for higher sensitivity. That would provide a better snapshot of the spread of COVID-19 by capturing a greater segment of the population.

“While we should certainly collect these data, we need to make sure the right studies are put in place so we can meaningfully interpret these data for individuals and for populations,” says Andrew Azman, assistant scientist at Johns Hopkins Bloomberg School of Public Health.

Additional studies will only make the results of antibody testing more informative. The editorial stipulates that we still need to understand whether antibodies remain in the body for months or years, what levels of antibodies provide immunity, and how responses might differ in people who had various severities of infection or who have other medical conditions.

Equally as important as leveraging the technologies at hand, the authors say, is building an infrastructure that allows states and countries to share protocols, standardize methods, share results, and coordinate activities. This would not only improve the response to the current pandemic but could build a foundation for monitoring other infectious diseases, including influenza, cholera, malaria, and future pandemics.

The knowledge gained now may help re-frame the future, they say. “The current crisis presents an opportunity to rethink how health systems generate and use surveillance data and how to harness the power of serological tests and seroepidemiology.”

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In addition to Leung, co-authors are Juliet Bryant, Andrew Azman, Matthew Ferrari, Benjamin Arnold, Maciej Boni, Yap Boum, Kyla Hayford, Francisco Luquero, Michael Mina, Isabel Rodriguez-Barraquer, Joseph Wu, Djibril Wade and Guy Vernet. In addition to the institutions mentioned, collaborators come from Fondation Mérieux, Médecins Sans Frontières, Epicentre in Yaounde and Paris, University of Hong Kong, IRESSEF, Dakar and Institut Pasteur de Bangui.

The editorial was published as “Serology for SARS-CoV-2: apprehensions, opportunities, and the path forward.”

People who live together may not get COVID-19 together

If anyone I live with were to get COVID-19, I would be resigned to the idea that I would get it too. After all, my family breathes the same air without wearing masks and touches the same doorknobs, day in and day out. And yet, it’s not necessarily a foregone conclusion that members of a shared household will share the virus.

Once one person becomes infected, there is a 12% likelihood that someone they are living with will become infected too, according to the University of Utah’s Utah HERO phase one study. Reports from China (also here) indicate that what we’re seeing in Utah is similar to what’s happening elsewhere in the world.

Scientists arrived at the number by performing antibody tests on more than 8,000 Utahns in randomly chosen households across four counties in the state. A positive test indicates that a person has had COVID-19 sometime in the past. Among households where at least one person tested positive, the scientists calculated the proportion of remaining members who also had antibodies.

It’s thought that, typically, when two or more people in a household test positive, one passed the virus to the other. But in some cases, they each may have been infected by someone outside the household. Either way, the frequency that two or more people in a household test positive is lower than one might expect considering how quickly COVID-19 is spreading all around us.

“You might think, ‘Wow if I’m in a household with an infected person, I’m a goner,’” says U of U Health epidemiologist Matthew Samore. “But that’s just not true. The interesting thing is, what are the implications?”

Superspreader or super unlucky?

Close examination of COVID-19 cases worldwide has already taught us that new coronavirus infection spreads more readily when people are close to one another indoors for long periods of time. That characterizes the living condition of many homes—and yet spread from one person in a household to another fails to happen about 88% of the time. What, then, could make the difference between who is likely to spread the virus and who is not?

Perhaps you’ve heard of the term “superspreaders”? One explanation, says Samore and his colleague Damon Toth, is that there is a large variability in infectiousness, and certain conditions are conducive to spreading the virus to large numbers of people. There is support for the idea that a relatively small proportion of people could be responsible for much of the spread of the disease. Research suggests that 10% to 20% of infected people were responsible for 80% of the cases examined.

“If we can understand the factors that make people superspreaders, or that make people minimally infectious, then we can create better policies that better control spread,” Samore says. What could those factors be? Scientists are trying to answer the question, but several possibilities exist.

Biological differences that lead infected people to shed more virus—and for longer periods of time—could boost their infectivity. Characteristics like these could come from being in a certain age group, from changes in the immune system and from other reasons scientists have yet to uncover.

The surrounding environment presents another set of conditions that could make a big difference. Imagine that households with a large number of people in tight quarters, multigenerational families or poor ventilation could be particularly conducive to spreading the disease.

Whether superspreading conditions are the main culprit or transmission mainly comes from many mild spreading events, chances are spreading happens more frequently outside the home. An infected person is more likely to encounter a greater number of people in the community, and a superspreader can potentially infect dozens of others. That suggests that community spread—rather than household transmission—may be a main driver of the pandemic.

Regardless, Toth points out that it is still important to take precautions at home if you know that someone you live with either has COVID-19 or has come in close contact with someone who does. Utah HERO has found that about 1% of Utahns tested positive for antibodies, meaning that about 99% were still susceptible to the disease.

“Twelve percent is still a pretty high risk if you have someone coming home with the virus,” Toth says. “It is a lot higher than before you had someone in your household who is positive.”

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Why is the COVID-19 mortality rate highest for Black Americans?

Racial disparities among essential workers could be a key reason that Black Americans are more likely than whites to contract and die of COVID-19, according to researchers at the University of Utah. They found that Blacks disproportionately worked in nine vital occupations that increase their exposure to SARs-CoV-2, the virus that causes COVID-19.

“There are a lot of theories why Blacks are dying at higher rates than other races during this pandemic,” says Fares Qeadan, a U of U Health biostatistician and senior author of the study. “However, our descriptive study strongly suggests that Blacks are not dying from COVID-19 because they are genetically more susceptible, have more comorbidities, or aren’t taking the necessary precautions. Instead, it’s likely because they are working in jobs where they have a greater risk of coming in contact with the virus day in and day out.”

The study appears in a special issue of World Medical & Health Policy.

After analyzing demographic job data, the researchers found that Blacks were nearly three times more likely than whites to work in health care support jobs such as nursing assistants or orderlies. Blacks were twice as likely to work in transportation roles such as bus drivers, movers and taxi drivers. Also, Black Americans were more likely to serve in seven other occupations deemed essential during the pandemic: food preparation, building and grounds maintenance, police and protective services, personal care (child care, hairstylists), office and administrative support, production (assemblers, painters, machinists), as well as social work and community services.

The researchers correlated these job classifications with COVID-19 deaths in 26 states and Washington, D.C. They concluded that all of these jobs placed workers at higher risk of infection and death from the novel disease. Police and protective services, health care support, transportation and food preparation were among those occupations most closely correlated with COVID-19 deaths.

This finding, Qeadan says, strongly implies that Blacks are more likely to be exposed to COVID-19 on the job than whites. It also could help explain why Blacks, who only represent 6% of the population in Wisconsin, accounted for more than 36% of the state’s COVID-19 deaths. Smaller but notably disproportionate COVID-19 death rates were found in other states such as California, New York, New Jersey and Tennessee. However, the largest disparities were detected in the Midwest, where Blacks accounted for 30-40% of COVID-19 deaths in Kansas, Missouri, Michigan and Illinois yet represented less than 15% of the populations in these states. At the time of the study in April 2020, Blacks comprise 12% of the population nationwide but 21% of COVID-19 deaths.

PHOTO CREDIT: Charlie Ehlert/University of Utah Health

Tiana and Charles Rogers.

“I find it ironic that the people we depend on as essential workers to wipe down our counters and keep things clean are the most vulnerable among us,” says Tiana N. Rogers, the corresponding author of the study and program manager for the Sorenson Impact Center’s Data, Policy, and Performance Innovation team in the David Eccles School of Business. “We need to make sure that the people doing these jobs can continue to provide for their families without having to risk their lives.”

According to study co-author, Charles R. Rogers, an assistant professor of public health, “Black essential workers could be bringing the disease home from work and inadvertently spreading it among their family members—especially considering some Blacks live in multi-generational, high-density housing.”

While this may make social distancing and other COVID-19 safety precautions more difficult, he says adhering to these guidelines is particularly important for essential workers in these situations.

Among its limitations, the study did not account for racial differences at the county or regional level within states due to a lack of access to public and desegregated data. The study’s results could also have been affected by the timing of the onset of COVID-19 in various states as well as how rapidly states adopted social distancing policies. Still, the researchers believe their findings are critical for enabling timely public health strategies for pandemics moving forward.

“This study should help health practitioners better assess what is going on among essential workers who happen to be Black,” Tiana Rogers says. “If we honestly don’t know what is happening and where it is happening, we can’t make adjustments that are equitable and give these workers the support and resources they need for survival during this crisis.”

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In addition to Tiana N. Rogers, Charles R. Rogers and Fares Qeadan, contributors to this study included Lily Y. Gu and Bin Yan of the University of Utah Medical School as well as Elizabeth VanSant-Webb of the University of Utah Sorensen Impact Center. This study was partially supported by the National Cancer Institute [grant K01CA234319] of the National Institutes of Health (NIH).

Masks save lives and livelihoods

Statewide mask requirements not only reduce the transmission of COVID-19, but they also spur more economic activity, while countywide mask requirements actually depress economic activity, according to researchers at the Marriner S. Eccles Institute for Economics and Quantitative Analysis.

The thing that really pops out,” said lead research Nathan Seegert, assistant professor of finance at the Eccles School, “is that statewide mask mandates are much more effective at both saving lives and livelihoods.”

The statewide mask requirements signal that safety measures are being taken seriously, and that boosts consumer confidence.

“If people feel safe, they’re going to go out and spend more,” Seegert said.

The study showed that the positive effects of the statewide mask requirements were seen immediately after they were enacted and up to two months afterward. The economic impact of statewide mask requirements was directly measured, showing an average of about $24 more spent per person per month, which adds up to millions of dollars per month in increased sales.

In addition to Seegert, the research was conducted by Mac Gaulin, assistant professor of Accounting, Mu-Jeung Yang, visiting assistant professor of finance, and Francisco Navarro-Sanchez, a finance doctoral candidate.

The research findings were announced at a press conference on Monday, Nov. 23 with Taylor Randall, dean of the David Eccles School of Business, and Natalie Gochnour, assistant dean at the Eccles School and director of the Kem C. Gardner Policy Institute.

Randall addressed the protests happening in Utah around the country against mask requirements.

We’re all facing a set of tradeoffs here. If you choose to not wear masks, you’re causing the confidence of your community to decrease, which means you will see reduced economic activity,” Randall said. “If we want to push the boundary, meaning we want to have better health and a better economy during this really critical time, we really should wear masks.”

Randall pointed out the connection between health and the economy.

“At the core of this relationship is mask-wearing and consumer confidence,” Randall said.

Gochnour said that Utah’s economy is performing much better than the U.S. economy, and the unemployment rate is much lower in the Beehive State compared to the U.S. But she warned that rising case counts increase safety fears, which decreases consumer confidence and leads to people shopping less.

Wearing a mask “is part of controlling our destiny” by increasing economic confidence so “we can get back on our feet faster.”

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