Researchers at UTHealth School of Public Health have been selected to receive $1 million from a $3.4 million grant to address the opioid epidemic and identify overdose patterns.
The five-year grant titled, “Predict to Prevent: Dynamic Spatiotemporal Analyses of Opioid Overdose to Guide Pre-Emptive Public Health Responses,” is funded by the National Institute of Health (NIH).
“Opioid overdose fatalities have reached crisis levels in all socioeconomic and geographic communities in the U.S.,” said Cici Bauer, PhD, assistant professor in the Department of Biostatistics and Data Science at UTHealth School of Public Health and co-principal investigator on the grant. “Utilizing a first-of-its-kind statewide Public Health Data Warehouse in Massachusetts with multiple linked administrative data sets 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.”
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. 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,” she said.
Bauer, and Thomas Stopka, PhD, from Tufts University serve as Co principal investigators of this R01 grant. "R01 is a funding mechanism from NIH research grants and is very prestigious and competitive to get," said Bauer.
Tufts University is the contract institution on the grant.
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