北卡罗来纳州丁丙诺啡优化分配的贝叶斯时空模型
北卡罗来纳州县级年度阿片类药物过量死亡与丁丙诺啡处方的表格数据，用于贝叶斯时空建模优化分配。
基本信息
资源简介
北卡罗来纳州丁丙诺啡优化分配的贝叶斯时空模型
【数据集背景】
本数据集源站标题为《A Bayesian Spatio-temporal Model to Optimize Allocation of Buprenorphine in North Carolina》。配套论文《A Bayesian Spatio-temporal Model to Optimize Allocation of Buprenorphine in North Carolina》发表于 Statistics and Public Policy（2023），DOI：10.1080/2330443X.2023.2218448。项目资助方：Research reported in this publication was supported by the National Institute On Drug Abuse of the National Institutes of Health under Award Number R01DA052214. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.。源站首次发布：2023-05-25。
【数据内容】
源站原始描述：The opioid epidemic is an ongoing public health crisis. In North Carolina, overdose deaths due to illicit opioid overdose have sharply increased over the last 5–7 years. Buprenorphine is a U.S. Food and Drug Administration approved medication for treatment of opioid use disorder and is obtained by prescription. Prior to January 2023, providers had to obtain a waiver and were limited in the number of patients that they could prescribe buprenorphine. Thus, identifying counties where increasing bup…
文件 uspp_a_2218448_sm5603.r 为文本内容，开头为：library(nloptr) library(xtable) rm(list = ls()) set.seed(12345) ################################################################################ …
文件 uspp_a_2218448_sm5601.r 为文本内容，开头为：library(spData) library(''spdep'') library(''maptools'') library(''shapefiles'') library(ggplot2) library(''ggmap'') library(''rgdal'') library(''Rmisc'')# library…
【数据结构与技术规格】
文件数 4 个，合计 1.56 MB。uspp_a_2218448_sm5603.r：text/plain，49.37 KB。uspp_a_2218448_sm5601.r：text/plain，13.95 KB。uspp_a_2218448_sm5599.pdf：application/pdf，1.48 MB。数据集 DOI：10.6084/m9.figshare.23198322.v1。
【主题与分类】
源站学科分类：Medicine、Pharmacology、Biotechnology、Cancer、Science Policy、Mental Health。主题标签：Constrained optimization、Geographic distribution、Health policy、Medication-assisted treatment、Opioid overdose、Resource allocation。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面：https://tandf.figshare.com/articles/dataset/A_Bayesian_Spatio-temporal_Model_to_Optimize_Allocation_of_Buprenorphine_in_North_Carolina/23198322
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：A Bayesian Spatio-temporal Model to Optimize Allocation of Buprenorphine in North Carolina. Taylor & Francis. Dong, Qianyu; Kline, David; Hepler, Staci A
【使用注意】
· 源站最后修改于 2023-11-27，引用时请注意版本时效。
下载信息
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使用方式
数据集获取（Figshare）
- 源站标题：A Bayesian Spatio-temporal Model to Optimize Allocation of Buprenorphine in North Carolina
- DOI：10.6084/m9.figshare.23198322.v1
- 发布日期：2023-05-25
- 文件数：4 个
- 文件总体积：1.56 MB
- 源站页面：https://tandf.figshare.com/articles/dataset/A_Bayesian_Spatio-temporal_Model_to_Optimize_Allocation_of_Buprenorphine_in_North_Carolina/23198322
命令行下载
curl -L -o "uspp_a_2218448_sm5603.r" "https://ndownloader.figshare.com/files/40894410"
curl -L -o "uspp_a_2218448_sm5601.r" "https://ndownloader.figshare.com/files/40894413"
curl -L -o "uspp_a_2218448_sm5599.pdf" "https://ndownloader.figshare.com/files/40894416"
curl -L -o "uspp_a_2218448_sm5598.csv" "https://ndownloader.figshare.com/files/40894419"
文件清单
uspp_a_2218448_sm5603.r（49.37 KB）uspp_a_2218448_sm5601.r（13.95 KB）uspp_a_2218448_sm5599.pdf（1.48 MB）uspp_a_2218448_sm5598.csv（24.09 KB）
文件总体积 1.56 MB（源站 API 实测）。
数据说明
The opioid epidemic is an ongoing public health crisis. In North Carolina, overdose deaths due to illicit opioid overdose have sharply increased over the last 5–7 years. Buprenorphine is a U.S. Food and Drug Administration approved medication for treatment of opioid use disorder and is obtained by prescription. Prior to January 2023, providers had to obtain a waiver and were limited in the number of patients that they could prescribe buprenorphine. Thus, identifying counties where increasing buprenorphine would yield the greatest overall reduction in overdose death can help policymakers target certain geographical regions to inform an effective public health response. We propose a Bayesian spatio-temporal model that relates yearly, county-level changes in illicit opioid overdose death rates to changes in buprenorphine prescriptions. We use our model to forecast the statewide count and rate of illicit opioid overdose deaths in future years, and we use nonlinear constrained optimization to identify the optimal buprenorphine increase in each county under a set of constraints on available resources. Our model estimates a negative relationship between death rate and increasing buprenorphine after accounting for other covariates, and our identified optimal single-year allocation strategy is estimated to reduce opioid overdose deaths by over 5%. Supplementary materials for this article are available online.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.23198322.v1（source: https://tandf.figshare.com/articles/dataset/A_Bayesian_Spatio-temporal_Model_to_Optimize_Allocation_of_Buprenorphine_in_North_Carolina/23198322）。
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