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A Joint Spatio-Temporal Model of Opioid Associated Deaths and Treatment Admissions in Ohio

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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
Ji, Yixuan (author)
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
title
A Joint Spatio-Temporal Model of Opioid Associated Deaths and Treatment Admissions in Ohio
type
Thesis

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