Original article by Deborah Strange in University Communications. Photo credit: Jiyoung Park
Data-Driven Solutions
As an engineer, Maria Mayorga creates mathematical and computer models to study health systems. Mayorga, a professor of personalized medicine in the College of Engineering, has studied barriers to care, like ambulance response times in rural areas and racial inequity in vaccine access, as well as the impact of interventions, like masking in classrooms during the COVID-19 pandemic. These mathematical and computer models can quantify real-world issues.
“Using mathematical models, we abstract the real world and turn it into something that’s a mathematical formula or computer simulation that we can then analyze,” Mayorga said.
During the COVID-19 pandemic, Black and Hispanic Americans had a higher death rate despite being an overall younger population. Data sets showed that these populations were more likely to be essential workers and live in intergenerational residences, meaning they were more vulnerable to catching and spreading the disease at work and at home. When vaccines against the virus became available, uptake was low among those same populations. But the issue is multifaceted: Often, people needed a mobile device to schedule an appointment, or they needed to check websites frequently to find available vaccines. Essential workers couldn’t always take time off to get a vaccine. Often, initial communications about the vaccines were offered in Spanish but follow-up communications weren’t.
“A lot of these problems are hard because there’s no one reason,” Mayorga said. “There are so many reasons why people might be at a disadvantage, so there are a lot of correlations.”
When making sense of data, Mayorga turns to subject matter experts — in health, equity, diversity, community leadership — to ensure she has a holistic view of the issues.
“At the end of the day, I’m still an engineer and mathematician,” Mayorga said. “I’m not a social scientist or psychologist. It’s super important that we work in interdisciplinary teams. No problem addressing equity can be done without input either from the community you’re studying or people in the social, behavioral or medical sciences. Engineers who want to understand these problems need to find good partnerships or you can end up doing more harm.”
No problem addressing equity can be done without input either from the community you’re studying or people in the social, behavioral or medical sciences.
Maria Mayorga
Currently, Mayorga is studying diabetic retinopathy, which can lead to blindness in patients with diabetes. The disease progresses slowly and is preventable when caught early. The best way to detect it is through regular eye exams, but with several possible complications of diabetes, patients often believe their regular physicals are enough.
Mayorga’s study is working specifically with a Native American tribe, whose population shows a different progression of retinopathy than clinical trials of majority-white populations. Many clinical recommendations are based on trials that don’t have sufficient minority representation. She’s looking at different barriers to care, like access and communication, and using data to determine risk scores for patients.
“We have a sort of moral obligation to do this kind of research,” Mayorga said. “In engineering, we’re trying to address societal issues using engineering techniques. When you talk about solving societal issues, you have to take care of all of society, not just some people.”