Estimating the burden of the opioid epidemic for adults and adolescents in Ohio counties.
Bayesian hierarchical modeling
disease mapping
multivariate
opioids
spatial analysis
substance-related disorders
Journal
Biometrics
ISSN: 1541-0420
Titre abrégé: Biometrics
Pays: United States
ID NLM: 0370625
Informations de publication
Date de publication:
06 2021
06 2021
Historique:
revised:
19
03
2020
received:
13
06
2019
pubmed:
16
5
2020
medline:
26
10
2021
entrez:
16
5
2020
Statut:
ppublish
Résumé
Quantifying the opioid epidemic at the local level is a challenging problem that has important consequences on resource allocation. Adults and adolescents may exhibit different spatial trends and require different interventions and resources so it is important to examine the problem for each age group. In Ohio, surveillance data are collected at the county level for each age group on measurable outcomes of the opioid epidemic, overdose deaths, and treatment admissions. However, our interest lies in quantifying the unmeasurable construct, representing the burden of the opioid epidemic, which drives rates of the outcomes. We propose jointly modeling adult and adolescent surveillance outcomes through a multivariate spatial factor model. A generalized spatial factor model within each age group quantifies a latent factor related to the number of opioid-associated treatment admissions and deaths. By assuming a multivariate conditional autoregressive model for the spatial factors of adults and adolescents, we allow the adolescent model to borrow strength from the adult model (and vice versa), improving estimation. We also incorporate county-level covariates to help explain spatial heterogeneity in each of the factors. We apply this approach to the state of Ohio and discuss the findings. Our framework provides a coherent approach for synthesizing information across multiple outcomes and age groups to better understand the spatial epidemiology of the opioid epidemic.
Identifiants
pubmed: 32413155
doi: 10.1111/biom.13295
pmc: PMC7666653
mid: NIHMS1603526
doi:
Substances chimiques
Analgesics, Opioid
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
765-775Subventions
Organisme : NIDA NIH HHS
ID : R21 DA045236
Pays : United States
Informations de copyright
© 2020 The International Biometric Society.
Références
Curr HIV/AIDS Rep. 2018 Apr;15(2):96-112
pubmed: 29460225
Public Health Rep. 2015 Jul-Aug;130(4):339-42
pubmed: 26345488
J Urban Health. 2006 Nov;83(6 Suppl):i39-53
pubmed: 17096189
Biostatistics. 2003 Jan;4(1):11-25
pubmed: 12925327
J Emerg Med. 2016 Nov;51(5):485-490
pubmed: 27596964
Am J Drug Alcohol Abuse. 2017 May;43(3):299-305
pubmed: 27646841
JAMA. 2017 Dec 26;318(24):2416-2417
pubmed: 29214309
Bayesian Anal. 2017 Mar;12(1):239-259
pubmed: 29707101
MMWR Morb Mortal Wkly Rep. 2016 Jan 01;64(50-51):1378-82
pubmed: 26720857
Am J Public Health. 1984 Jul;74(7):660-6
pubmed: 6611092
Environmetrics. 2017 Dec;28(8):
pubmed: 29230091
Clin Colorectal Cancer. 2019 Jun;18(2):e261-e274
pubmed: 30713133
MMWR Morb Mortal Wkly Rep. 2017 Sep 01;66(34):904-908
pubmed: 28859050
Biostatistics. 2003 Oct;4(4):569-82
pubmed: 14557112
Am J Drug Alcohol Abuse. 2016 Sep;42(5):530-538
pubmed: 27315427
J Am Stat Assoc. 2018;113(522):755-766
pubmed: 30828120
Electron J Stat. 2014;8(1):1491-1521
pubmed: 26180577
Ann Epidemiol. 2018 Sep;28(9):641-652
pubmed: 29921551
Am J Epidemiol. 1988 May;127(5):893-904
pubmed: 3282433
NCHS Data Brief. 2017 Dec;(294):1-8
pubmed: 29319475
Epidemiology. 2019 May;30(3):365-370
pubmed: 30882402
Biom J. 2012 May;54(3):385-404
pubmed: 22685004