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Interview

Residential Social Vulnerability Linked With Risk of COVID-19 Infection Among HCPs

Maria Asimopoulos

Headshot of Maria Zlotorzynska, PhD, MPH, Centers for Disease Control and PreventionRecently, Maria Zlotorzynska, PhD, MPH, affiliated with the Centers for Disease Control and Prevention, and colleagues examined how health care workers’ residential location and social vulnerability may impact their risk of COVID-19 infection. In this interview, Dr Zlotorzynska walks through key findings from the study and explores how health systems might use the data to anticipate labor shortages and support workers’ well-being.

What inspired your research into residential social vulnerability and COVID-19 among health care providers?

Health care workers have been one of the most impacted groups during the COVID-19 pandemic. While those who work with patients with COVID-19 experience infection risk within their workplaces, community exposures represent a substantial source of transmission among health care workers as well. We also know that Black and Hispanic health care workers have experienced a higher burden of COVID-19, much like in the general population. However, race and ethnicity are not the drivers of higher infection risk; they are just a marker. 

We wanted to find out more about the potential mechanisms for why these disparities arise. Given that racial residential segregation persists in the United States, we decided to look more deeply at the neighborhoods in which health care workers live. 

How was your study designed, and who participated?

The data for this analysis was collected by our partners in the Emerging Infections Program in 5 US states: Colorado, Minnesota, New Mexico, New York, and Oregon. Participants were health care workers who worked in selected health care facilities, which included acute care hospitals, nursing homes, outpatient clinics, and other health care facilities. 

This was a case-control study, meaning we included both health care workers who tested positive for SARS-CoV-2 (the virus that causes COVID-19) and health care workers who tested negative as a comparison. Participants completed interviews that collected information about their demographics, medical conditions, use of personal protective equipment (PPE) and workplace practices. For this analysis, we included data collected from May 2020 to December 2020.

As part of the interview, health care workers were asked to provide their residential addresses, which we used to determine the census tract in which they lived. We used a measure called the Social Vulnerability Index, or SVI, to describe the characteristics of each participant's census tract. 

The SVI was developed by our colleagues at the Agency for Toxic Substances and Disease Registry, and it is designed to identify areas most in need of resources before, during, and after hazardous events, such as infectious disease outbreaks. The SVI ranks each US census tract on 16 social factors, including poverty, crowded housing, lack of vehicle access to a personal vehicle, and groups these factors into 4 related themes. Each tract receives a separate ranking for each of the four themes as well as an overall ranking. A higher index value indicates higher social vulnerability. 

For our analysis, we grouped the 25% highest-ranked census tracts in our sample and categorized them as "high SVI", while the remaining 75% of census tracts were categorized as "low SVI." Once the data were collected and cleaned, we used statistical methods to test whether health care workers with COVID-19 were more likely, as compared to those without COVID-19, to live in high SVI areas. 

What are the major findings from your study? Did any of them surprise you?

The major finding was that health care workers with COVID-19 had a higher likelihood of living in highly vulnerable census tracts. Previous population-based studies found similar associations between higher SVI areas and COVID-19. This finding was consistent with our hypothesis that social factors in the residential area may influence infection risk for health care workers. 

Even before the COVID-19 pandemic, epidemiologists have theorized that socioeconomic factors may produce disparities in respiratory disease pandemics. For example, areas with more crowded housing, reliance on public transit, and more essential workers who cannot work from home may be more impacted. Having fewer health care resources, such as testing and treatment, may further exacerbate these disparities. Health care workers who live in these areas could then have more exposure risk beyond what they experience in their workplaces. 

Further, when we looked at each specific theme with the SVI, we found that census tract socioeconomic status and household characteristics were the primary drivers of these disparities. This means that health care workers with COVID-19 were more likely to live in areas with higher levels of poverty and unemployment, as well as areas where there were more older adults, children, and single-parent households. Because the SVI is composed of many variables, it was important for us to dive deeper into the measure and pull out what factors may be having the most impact on COVID-19 risk for this group.

Finally, we found that high proportions of certified nursing assistants and medical assistants lived in the most vulnerable areas. Almost half of health care workers in those roles lived in high SVI areas, as compared to only 1 in 10 physicians. It was important for us to identify the health care workers’ roles that could potentially encounter more viral exposure in their communities. Indeed, health care workers with COVID-19 were more likely to be either a certified nursing assistant or medical assistant than a physician.  

In your opinion, how can your findings inform efforts to address the health and wellness of providers?

There has been a lot of guidance focused on reducing viral transmission within health care settings. While this is, of course, very important to protect both workers and patients, what we hope health care systems take away from our findings is that it is important to consider the variety of social and economic contexts in which their workforce lives.  

The health care workforce is very diverse and includes people working in many different capacities. When we think of health care workers, we tend to focus on physicians and nurses, but it is important to remember the many other professionals who provide vital health care-related services, such as medical assistants, food services and environmental services staff, and others, many of whom may have lower income levels. These workers tend to live in areas where their risk for acquiring COVID-19 or other respiratory infection may be higher. 

Health care systems could apply measures like the SVI to forecast areas that are especially vulnerable to health care worker shortages during future waves of COVID-19 or other pandemics, and to consider ways to support the well-being of their workforce.  

Do you intend to expand on this research in the future?

This analysis only focused on data collected in 2020, but the project actually collected data through the end of 2021. We plan to analyze the full set of data, including examining the proportions of health care workers that reside in high socially vulnerable areas, and if these varied by health care role or health care setting where they worked. 

Is there anything else you would like to add?

We would like to thank everyone who contributed to the study, especially the staff at the Emerging Infections Program sites, and the health care workers who participated.

About Dr Zlotorzynska

Maria Zlotorzynska, PhD, MPH, is a health scientist in the Division of Healthcare Quality Promotion at the Centers for Disease Control and Prevention. Her work focuses on social epidemiology and health equity in US health care. 

© 2023 HMP Global. All Rights Reserved.
Any views and opinions expressed are those of the author(s) and/or participants and do not necessarily reflect the views, policy, or position of Integrated Healthcare Executive or HMP Global, their employees, and affiliates. 

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