Small area estimation and hotspot identification of opioid use disorder among military veterans living in the Southern United States.

Small area estimation and hotspot identification of opioid use disorder among military veterans living in the Southern United States.

Albright, David L;McDaniel, Justin;Kertesz, Stefan;Seal, David;Prather, Katie;English, Thomas;Laha-Walsh, Kirsten;
substance abuse 2019 pp. 1-7
296
albright2019smallsubstance

Abstract

: The purpose of this study was to estimate opioid use disorder prevalence rates at the county level among veterans in Alabama and to determine hotspots of said rates. By combining data from the National Survey on Drug Use and Health and the American Community Survey, we developed a mixed-effects generalized linear model of opioid use disorder and modeled probabilities onto veteran-specific population counts at the county level in Alabama. : The average model-based estimate for opioid use disorder prevalence among veterans in Alabama from 2015 to 2017 was 0.79% ( = 0.16), with a minimum of 0.52% (i.e., Lowndes county, Alabama) and a maximum of 1.10% (Dale county, Alabama). Hotspot analysis revealed a significant cluster of "high-high" veteran opioid use disorder prevalence in neighboring Marion, Winston, and Cullman counties. : The application of the statistical technique presented in this study can provide feasible, cost-effective, and practical county-level prevalence estimates of veteran-specific opioid use disorder and should be widely applied by states and counties so that they can more accurately and efficiently allocate resources to caring for veterans with an opioid use disorder.

Citation

ID: 71645
Ref Key: albright2019smallsubstance
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
71645
Unique Identifier:
10.1080/08897077.2019.1703066
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet