Tracking the spatial dynamics of the synthetic opioid crisis in the USA, 2013-2020 using human mobility-based graph neural network

Zhiyue Xia, Kathleen Stewart
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Abstract

Synthetic opioids are the most common drugs involved in drug-involved overdose mortalities in the U.S. The Center for Disease Control and Prevention reported that in 2018, about 70% of all drug overdose deaths involved opioids and 67% of all opioid-involved deaths were accounted for by synthetic opioids. In this study, we investigated the spread of synthetic opioids between 2013 and 2020 in the U.S., and analyzed the relationship between the spatiotemporal pattern of synthetic opioid-involved deaths and another key opioid, heroin, and compared patterns of deaths involving these two types of drugs during this time period. Spatial connections between counties were incorporated into a graph convolutional neural network model to represent and analyze the spread of synthetic opioid-involved deaths, and in the context of heroin-involved deaths.
利用基于人类流动性的图神经网络跟踪 2013-2020 年美国合成阿片类药物危机的空间动态
美国疾病控制和预防中心报告称,2018年,约70%的吸毒过量死亡事件涉及阿片类药物,67%的阿片类药物致死事件涉及合成阿片类药物、本研究调查了 2013 年至 2020 年期间合成类阿片在美国的传播情况,分析了合成类阿片致死的时空模式与另一种主要类阿片海洛因之间的关系,并比较了这一时期涉及这两类药物的死亡模式。县与县之间的空间联系被纳入图卷积神经网络模型,以表示和分析涉及合成类阿片的死亡案例的传播情况,并结合涉及海洛因的死亡案例进行分析。
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