Researchers at UTSA leverage data science to explore impact of pandemic

JULY 20, 2022 — Wenbo Wu, chair for the Department of Management Science and Statistics in the Carlos Alvarez College of Business, is leveraging data science to identify opportunities to support local neighborhoods. Wu collaborated with Ying Huang, associate professor in demography in the College for Health, Community and Policy (HCaP), and Eric Shattuck, assistant professor of research at the UTSA Institute for Health Disparities Research in HCaP, on a research study exploring key characteristics of Jefferson Heights and Elm Creek, two vastly different San Antonio neighborhoods.

Using two years’ worth of mobile positioning data—information collected using the geographic location of a device—and survey data from the Elm Creek and Jefferson Heights neighborhoods in San Antonio, the UTSA researchers analyzed the residents’ energy hardships, economic mobility and chronic health conditions before and during the COVID-19 pandemic. Their goal was to compare the two neighborhoods and better understand the patterns of residents by tracking and characterizing their daily lives.

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“Data science is powerful. It’s a meaningful field with powerful methods.”

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“When we look at mobile positioning data, we can identify which neighborhoods may struggle more, due to their daily patterns and help provide some kind of intervention program that will improve their quality of life,” Wu said.

The researchers summarized their findings in a policy brief for the City of San Antonio. Namely, they found that residents of economically less favored neighborhoods such as Jefferson Heights experienced stalled employment recovery to a greater extent than their counterparts living in economically more favored neighborhoods like Elm Creek.

Job loss varied little between the neighborhoods but racial inequalities were present. Almost half of the Hispanic households experienced job loss compared to one-third of white households.

Additionally, many residents in Jefferson Heights faced challenges meeting their basic needs such as mortgage or rent payments and utility bills.

Based on these observations, the researchers provided suggestions to the City of San Antonio to accelerate its post-pandemic recovery.

Economic recovery efforts in San Antonio should keep the “social infrastructure” of neighborhoods in mind when planning, they noted in their policy brief. Given that racial minorities, particularly non-Hispanic Blacks in disadvantaged neighborhoods, appeared to be left behind in the employment recovery, the researchers recommended local efforts focused on financial and physical assistance, job training and employment opportunities.

For the next phase of the study, the researchers are embarking on several projects. Shattuck is comparing the results of the San Antonio survey to national data to determine if local patterns are similar to ones nationwide. Wu is looking at mobility data collected as part of the UTSA survey in order to create different profiles to possibly explain the disparities and comparison of coping behavior pre-and post-pandemic. Huang is looking more closely at neighborhood mobility patterns and how they are linked to household socioeconomic indicators.

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Wu is a core faculty member in the UTSA School of Data Science. The new school, the only one of its kind in the nation at a Tier One, Hispanic Serving Institution, will educate a new generation of data scientists while leading the nation in data-intensive research when it opens its doors to students in January.

“Data science is powerful. It’s a meaningful field with powerful methods,” Wu said.

— Ari Castañeda and Valerie Bustamante Johnson

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