The UTHealth School of Public Health has been selected to receive a National Institute of Health (NIH) five-year grant titled, “Predict to Prevent: Dynamic Spatiotemporal Analyses of Opioid Overdose to Guide Pre-Emptive Public Health Responses.”
Cici Bauer, PhD, from UTHealth School of Public Health, and Thomas Stopka, PhD, from Tufts University serve as the multiple principal investigators of this R01 grant. "R01 is a funding mechanism from NIH research grants and is very prestigious and competitive to get," says Dr. Bauer.
The total grant amount is $3.4 million, with UTHealth awarded over $1 million. Tufts University is the contact institution of the grant.
Spearheading the School of Public Health effort is Bauer, who serves as an assistant professor in the Department of Biostatistics and Data Science. “Opioid overdose fatalities have reached crisis levels in all socioeconomic and geographic communities in the U.S.,” she says. “Utilizing a first-of-its-kind statewide Public Health Data Warehouse in Massachusetts with multiple linked administrative datasets and state-of-the-art Bayesian spatiotemporal models, we are in a unique position to fill in the gaps in the field’s ability to rapidly identify opioid overdose patterns, predict future opioid epidemics, and evaluate the effectiveness of public health and clinical interventions.”
Dr. Bauer is optimistic that the linked database will identify individual, interpersonal, community and societal factors that contribute to opioid overdose. “We need these forecasting models that rely on linked administrative data to forecast future opioid overdose spikes and assess public health intervention success,” she explains. “We plan to develop a comprehensive approach to identify the factors that contribute to opioid overdose, efficiently detect overdose hotspots, and develop forecasting models for timely prediction and prevention of future opioid overdose epidemics.”
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