ArticleJournal of the Royal Statistical Society. Series A, (Statistics in Society)2023
An integrated abundance model for estimating county-level prevalence of opioid misuse in Ohio.
Article in Journal of the Royal Statistical Society. Series A, (Statistics in Society), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Estimating community-level prevalence of opioid use disorder: Extrapolating from Medicaid claims data and other publicly available data sources in Ohio, USA.Addiction (Abingdon, England) · 2026Article
- Integrating data at multiple spatial scales to estimate the local burden of the opioid syndemic.Spatial and spatio-temporal epidemiology · 2025Article
- Drug Overdose Death among Residents of Urban Census Tracts: How Granular Geographical Analyses Uncover Socioenvironmental Correlates in Cuyahoga County, Ohio.Journal of urban health : bulletin of the New York Academy of Medicine · 2025Article
- Rates of Receiving Medication for Opioid Use Disorder and Opioid Overdose Deaths During the Early Synthetic Opioid Crisis: A County-level Analysis.Epidemiology (Cambridge, Mass.) · 2025Article
- Invited commentary: motivating better methods-and better data collection-for measuring the prevalence of drug misuse.American journal of epidemiology · 2025Article
- Estimation of the prevalence of opioid misuse in New York State counties, 2007-2018: a bayesian spatiotemporal abundance model approach.American journal of epidemiology · 2024Article
- Responding to the US opioid crisis: leveraging analytics to support decision making.Health care management science · 2023Article
- A spatio-temporal hierarchical model to account for temporal misalignment in American Community Survey explanatory variables.Spatial and spatio-temporal epidemiology · 2023Article
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Opioid misuse is a national epidemic and a significant drug related threat to the United States. While the scale of the problem is undeniable, estimates of the local prevalence of opioid misuse are lacking, despite their importance to policy-making and resource allocation. This is due, in part, to the challenge of directly measuring opioid misuse at a local level. In this paper, we develop a Bayesian hierarchical spatio-temporal abundance model that integrates indirect county-level data on opioid-related outcomes with state-level survey estimates on prevalence of opioid misuse to estimate the latent county-level prevalence and counts of people who misuse opioids. A simulation study shows that our integrated model accurately recovers the latent counts and prevalence. We apply our model to county-level surveillance data on opioid overdose deaths and treatment admissions from the state of Ohio. Our proposed framework can be applied to other applications of small area estimation for hard to reach populations, which is a common occurrence with many health conditions such as those related to illicit behaviors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.