Kristin Bennett, professor in the mathematical sciences department, looks into the underlying social causes.
Kristin P. Bennett is the Associate Director of the Institute for Data Exploration and Application and a Professor in the Mathematical Sciences and Computer Science Departments and at Rensselaer Polytechnic Institute. Her research focuses on extracting information from data using novel predictive or descriptive mathematical models and data visualizations, and the applications of these methods to support decision making and to accelerate discovery in science, engineering, public health and business. She has 25 years of experience and over 100 publications in these areas. As an active member of the machine learning, data mining, and operations research communities, she has served as present or past associate or guest editor for ACM Transactions on Knowledge Discovery from Data, SIAM Journal on Optimization, Naval Research Logistics, Machine Learning Journal, IEEE Transactions on Neural Networks, and Journal on Machine Learning Research. She served as program chair of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. She has a Ph.D. in Computer Sciences from the University of Wisconsin-Madison. She founded and directs the NIH sponsored “TB-Insight” project which provided molecular epidemiology tools and methods to help track and control tuberculosis. She also founded and directs the “Data Analytics Throughout Undergraduate Mathematics” or DATUM which is pioneering highly effective new approaches for data analytics undergraduate education. She also founded the Data Interdisciplinary Challenges Intelligent Technology Exploration Laboratory (Data INCITE Lab.) In the Data INCITE Lab, undergraduate and graduate students tackle open applied data analytics problems contributed by industry, foundations, and researchers.
Some groups of Americans are clearly dying of COVID-19 at higher rates than others. In fact, regional disparities exist for all causes of death. An adult living in Ohio is 2.5 times more likely to die from suicide or overdose than one living in California.
There are underlying social causes for the regional differences in COVID-19 mortality and these so-called “deaths of despair.” More troubling, the pandemic, despair, and social risk factors are interlinked and exacerbating one another.
My lab has developed two tools – MortalityMinder and COVIDMinder — that help us understand why regional disparities in health exist. It’s clear that where you live has a huge impact on your chances of premature death.
MortalityMinder finds counties with increased rates of premature death, and finds the associated social determinants or risk factors. Nationally, deaths of despair have risen dramatically since the Great Recession, but there are a clear regional fingerprints.
In Ohio, people are more likely to die from suicide and overdose in counties with higher rates of socioeconomic distress, food insecurity, childhood poverty, and single-parent households. In California, rural counties and those with poor mental health suffer more deaths of despair.
COVIDMinder uses maps and analysis to explore regional disparities in COVID-19 deaths. Similar factors of race and socioeconomic status are social determinants of COVID-19.
Covid-19 has increased these social risk factors across the nation, with a corresponding rise of overdoses. Sadly, we predict that suicide rates will spike under COVID-19. Understanding risk factors can help us develop interventions at the national and local levels to help fight deaths of despair, COVID-19, and other health challenges in the United States.