Researchers at UTSA leverage data science to explore impact of pandemic –

“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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