Understanding the opioid syndemic in North Carolina: A novel approach to modeling and identifying factors.

IF 1.8 3区 数学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Eva Murphy, David Kline, Kathleen L Egan, Kathryn E Lancaster, William C Miller, Lance A Waller, Staci A Hepler
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引用次数: 0

Abstract

The opioid epidemic is a significant public health challenge in North Carolina, but limited data restrict our understanding of its complexity. Examining trends and relationships among different outcomes believed to reflect opioid misuse provides an alternative perspective to understand the opioid epidemic. We use a Bayesian dynamic spatial factor model to capture the interrelated dynamics within six different county-level outcomes, such as illicit opioid overdose deaths, emergency department visits related to drug overdose, treatment counts for opioid use disorder, patients receiving prescriptions for buprenorphine, and newly diagnosed cases of acute and chronic hepatitis C virus and human immunodeficiency virus. We design the factor model to yield meaningful interactions among predefined subsets of these outcomes, causing a departure from the conventional lower triangular structure in the loadings matrix and leading to familiar identifiability issues. To address this challenge, we propose a novel approach that involves decomposing the loadings matrix within a Markov chain Monte Carlo algorithm, allowing us to estimate the loadings and factors uniquely. As a result, we gain a better understanding of the spatio-temporal dynamics of the opioid epidemic in North Carolina.

了解北卡罗莱纳州的阿片类药物综合征:一种建模和识别因素的新方法。
阿片类药物流行是北卡罗来纳州重大的公共卫生挑战,但有限的数据限制了我们对其复杂性的理解。研究被认为反映阿片类药物滥用的不同结果之间的趋势和关系,为了解阿片类药物流行提供了另一种视角。我们使用贝叶斯动态空间因子模型来捕捉六个不同县级结果的相关动态,例如非法阿片类药物过量死亡,与药物过量相关的急诊就诊,阿片类药物使用障碍的治疗计数,接受丁丙诺啡处方的患者,以及新诊断的急性和慢性丙型肝炎病毒和人类免疫缺陷病毒病例。我们设计了因子模型,以在这些结果的预定义子集之间产生有意义的相互作用,从而导致负载矩阵中传统的下三角形结构的偏离,并导致熟悉的可识别性问题。为了解决这一挑战,我们提出了一种新的方法,该方法涉及在马尔可夫链蒙特卡罗算法中分解负载矩阵,使我们能够唯一地估计负载和因素。因此,我们对北卡罗来纳州阿片类药物流行的时空动态有了更好的了解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biostatistics
Biostatistics 生物-数学与计算生物学
CiteScore
5.10
自引率
4.80%
发文量
45
审稿时长
6-12 weeks
期刊介绍: Among the important scientific developments of the 20th century is the explosive growth in statistical reasoning and methods for application to studies of human health. Examples include developments in likelihood methods for inference, epidemiologic statistics, clinical trials, survival analysis, and statistical genetics. Substantive problems in public health and biomedical research have fueled the development of statistical methods, which in turn have improved our ability to draw valid inferences from data. The objective of Biostatistics is to advance statistical science and its application to problems of human health and disease, with the ultimate goal of advancing the public''s health.
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