Abstract
Opioid misuse is a significant public health issue and a national epidemic with a high prevalence of associated morbidity and mortality. The epidemic is particularly severe in Ohio which has some of the highest overdose rates in the country. It is important to understand spatial and temporal trends of the opioid epidemic to learn more about areas that are most affected and to inform potential community interventions and resource allocation. We propose a multivariate spatio-temporal model to leverage existing surveillance measures, opioid-associated deaths and treatment admissions, to learn about the underlying epidemic for counties in Ohio. We do this using a temporally varying spatial factor that synthesizes information from both counts to estimate common underlying risk which we interpret as the burden of the epidemic. We demonstrate the use of this model with county-level data from 2007 to 2018 in Ohio. Through our model estimates, we identify counties with above and below average burden and examine how those regions have shifted over time given overall statewide trends. Specifically, we highlight the sustained above average burden of the opioid epidemic on southern Ohio throughout the 12 years examined.
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Availability of data and material
The overdose death datasets analyzed during the current study are available in the Ohio Public Health Data Warehouse, http://publicapps.odh.ohio.gov/EDW/DataCatalog. The treatment admissions data that support the findings of this study are available from the Ohio Department of Mental Health and Addiction Services but restrictions apply to the availability of these data, which were used under a data use agreement, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of the Ohio Department of Mental Health and Addiction Services.
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Code has been provided as Electronic Supplementary Material.
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Acknowledgements
Research reported in this publication was supported by the National Institute On Drug Abuse of the National Institutes of Health under Award Number R21DA045236. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. These data were provided by the Ohio Department of Health. The Department specifically disclaims responsibility for any analyses, interpretations or conclusions.
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Kline, D., Ji, Y. & Hepler, S. A multivariate spatio-temporal model of the opioid epidemic in Ohio: a factor model approach. Health Serv Outcomes Res Method 21, 42–53 (2021). https://doi.org/10.1007/s10742-020-00227-3
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DOI: https://doi.org/10.1007/s10742-020-00227-3