Deas Andrew, Spannaus Adam, Fernando Hashan, Hanson Heidi A, Kapadia Anuj J, Trafton Jodie, Maroulas Vasileios
Department of Mathematics, University of Tennessee, Circle Dr, Knoxville, 37916, TN, USA.
Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Bethel Valley Road, Oak Ridge, 37830, TN, USA.
BMC Public Health. 2025 May 13;25(1):1759. doi: 10.1186/s12889-025-23044-0.
The opioid crisis remains one of the most daunting and complex public health problems in the United States. This study investigates the national epidemic by analyzing vulnerability profiles of three key factors: opioid-related mortality rates, opioid prescription dispensing rates, and disability rank ordered rates.
This study utilizes county level data, spanning the years 2014 through 2020, on the rates of opioid-related mortality, opioid prescription dispensing, and disability. To successfully estimate and predict trends in these opioid-related factors, we augment the Kalman Filter with a novel spatial component. To define opioid vulnerability profiles, we create heat maps of our filter's predicted rates across the nation's counties and identify the hotspots. In this context, hotspots are defined on a year-by-year basis as counties with rates in the top 5% nationally.
Our spatial Kalman filter demonstrates strong predictive performance. From 2014 to 2018, these predictions highlight consistent spatiotemporal patterns across all three factors, with Appalachia distinguished as the nation's most vulnerable region. Starting in 2019 however, the dispensing rate profiles undergo a dramatic and chaotic shift.
The initial primary drivers of opioid abuse in the Appalachian region were likely prescription opioids; however, it now appears that abuse is sustained by illegal drugs. Additionally, we find that the disabled subpopulation may be more at risk of opioid-related mortality than the general population. Public health initiatives must extend beyond controlling prescription practices to address the transition to and impact of illicit drug use.
阿片类药物危机仍然是美国最严峻、最复杂的公共卫生问题之一。本研究通过分析三个关键因素的脆弱性概况来调查全国性的疫情:阿片类药物相关死亡率、阿片类药物处方配给率和残疾排名率。
本研究利用了2014年至2020年县级层面关于阿片类药物相关死亡率、阿片类药物处方配给率和残疾率的数据。为了成功估计和预测这些与阿片类药物相关因素的趋势,我们用一个新的空间成分增强了卡尔曼滤波器。为了定义阿片类药物脆弱性概况,我们绘制了滤波器预测率在全国各县的热图,并确定了热点地区。在这种情况下,热点地区逐年定义为全国比率排名前5%的县。
我们的空间卡尔曼滤波器显示出很强的预测性能。从2014年到2018年,这些预测突出了所有三个因素一致的时空模式,阿巴拉契亚地区被认为是全国最脆弱的地区。然而,从2019年开始,配给率概况发生了剧烈而混乱的变化。
阿巴拉契亚地区阿片类药物滥用最初的主要驱动因素可能是处方阿片类药物;然而,现在看来,滥用是由非法药物维持的。此外,我们发现残疾亚人群体可能比一般人群面临更高的阿片类药物相关死亡风险。公共卫生举措必须超越控制处方行为,以应对向非法药物使用的转变及其影响。