A Joint Spatio-Temporal Model of Opioid Associated Deaths and Treatment Admissions in Ohio
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- title
- A Joint Spatio-Temporal Model of Opioid Associated Deaths and Treatment Admissions in Ohio
- author
- Ji, Yixuan
- abstract
- Opioid misuse is a major public health issue in the United States and in 2017, Ohio had the second highest age-adjusted drug overdose rate. In this thesis, we consider a joint spatio-temporal model of county-level surveillance data on deaths and treatment admissions using a latent spatial factor model. Our main goal is to estimate a common spatial factor, which offers a summary of the underlying joint burden of opioid misuse across space and time. The result is supposed to provide a valuable tool to allocate resources across the state in a timely manner.
- subject
- conditional autoregressive
- factor model
- opioid epidemic
- resource allocation
- spatio-temporal
- contributor
- Hepler, Staci A (committee chair)
- Jiang, Miaohua (committee member)
- Erhardt, Robert (committee member)
- date
- 2019-05-24T08:35:46Z (accessioned)
- 2019-05-24T08:35:46Z (available)
- 2019 (issued)
- degree
- Mathematics and Statistics (discipline)
- identifier
- http://hdl.handle.net/10339/93963 (uri)
- language
- en (iso)
- publisher
- Wake Forest University
- type
- Thesis