Abstract

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 opioidepidemic.

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