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PROJECT SUMMARY/ABSTRACT The United States is in the midst of a public health crisis due to the ongoing opioid syndemic. The opioid syndemic consists of the inter-related epidemics of opioid misuse, fatal and non-fatal overdose, human immunodeficiency virus (HIV), and hepatitis C (HCV). The consequences of opioid misuse are particularly severe in Ohio as the state has experienced overdose rates that are double the national average as well as elevated risk for epidemic levels of HIV and HCV. A key need for addressing the syndemic is to improve surveillance science methodology to better measure community-levels of opioid misuse and be able to identify and target areas of emerging risk with resources. However, no single data source currently observed by the public health surveillance system fully characterizes opioid misuse at relevant spatial and temporal supports. Novel statistical methods are needed to better leverage existing data and appropriately integrate multiple imperfect surveillance outcomes across different spatial scales to comprehensively estimate levels of opioid misuse and model the syndemic over space and time. Doing so will enable estimation and inference at small areas that are relevant to local policymakers and public health officials while accounting for measurement error. There are several methodological challenges that will be overcome with achievement of the following aims: 1) develop and assess a spatio-temporal factor model that estimates a factor that can be meaningfully interpreted longitudinally, 2) develop and assess a spatial factor model that allows for outcomes to have different spatial supports, and 3) develop and assess a multivariate spatio- temporal model to estimate areal prevalence of latent opioid misuse. Successful development of a comprehensive model of the opioid syndemic will advance surveillance science and will produce estimates of opioid misuse that advance epidemiological understanding and provide valuable information to policymakers and public health officials.
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Spatio-temporal Methods for Surveillance of the Opioid Syndemic
Spatio-temporal Methods for Surveillance of the Opioid Syndemic
A Bayesian Spatio-Temporal Approach for Estimating County-Level Opioid Misuse Rates in Ohio
  • 批准号:
    9600216
  • 项目类别:
  • 资助金额:
    $23.22万
  • 财政年份:
    2018
  • 负责人:
    Staci Hepler
  • 依托单位:
海外基金