Dr. Nelís Soto-Ramírez recently conducted a “time series analysis” of monthly Adult Protective Services (APS) reports—calls to the South Carolina Department of Social Services (DSS) reporting suspected abuse, neglect, or exploitation of elderly and disabled adults. The purpose of this study was to predict future report numbers so that the agency could anticipate the rising level of reports and prepare its case managers to handle the increase in investigations accordingly.

In May, Soto-Ramírez presented findings from her study at the Modern Modeling Methods Conference (M3) at the University of Connecticut. Organized as a “poster session,” the M3 was Soto-Ramírez’s first conference as a Center employee. Her poster details the analysis she used to help inform and ultimately improve DSS’s response to future APS reports.

Experts often use time series analyses to forecast otherwise-unpredictable numbers in areas like public health and economics. Soto-Ramírez’s employment of this method in APS demonstrates her skill and expertise in applied statistics, which makes her partnership with DSS invaluable.

As a Senior Research Associate at the Center, Soto-Ramírez regularly conducts studies like these that use applied statistics and community-derived research to assist DSS in all of its program areas. She enjoys working with the agency and knows the partnership is making a positive impact in South Carolina. “It’s more indirectly impactful,” she says, comparing her role with that of DSS workers. “But I like to make a difference in the lives of vulnerable populations.”