ArticleThe annals of applied statistics2021
A MULTIVARIATE SPATIOTEMPORAL CHANGE-POINT MODEL OF OPIOID OVERDOSE DEATHS IN OHIO.
Article in The annals of applied statistics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A spatiotemporal analysis of opioid prescriptions in Indiana from 2015 to 2019.Substance abuse treatment, prevention, and policy · 2025Article
- Multivariate varying coefficient spatiotemporal model.Statistics in biosciences · 2024Article
- Multivariate spatiotemporal functional principal component analysis for modeling hospitalization and mortality rates in the dialysis population.Biostatistics (Oxford, England) · 2024Article
- A MULTIVARIATE SPATIOTEMPORAL CHANGE-POINT MODEL OF OPIOID OVERDOSE DEATHS IN OHIO.The annals of applied statistics · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
Ohio is one of the states most impacted by the opioid epidemic and experienced the second highest age-adjusted fatal drug overdose rate in 2017. Initially it was believed prescription opioids were driving the opioid crisis in Ohio. However, as the epidemic evolved, opioid overdose deaths due to fentanyl have drastically increased. In this work we develop a Bayesian multivariate spatiotemporal model for Ohio county overdose death rates from 2007 to 2018 due to different types of opioids. The log-odds are assumed to follow a spatially varying change point regression model. By assuming the regression coefficients are a multivariate conditional autoregressive process, we capture spatial dependence within each drug type and also dependence across drug types. The proposed model allows us to not only study spatiotemporal trends in overdose death rates but also to detect county-level shifts in these trends over time for various types of opioids.
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Registered trials
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