The Rapidly Changing US Illicit Drug Market and the Potential for an Improved Early Warning System: Evidence from Ohio Drug Crime Labs

Rosenblum, Daniel; Unick, Jay; Ciccarone, Daniel

doi:10.1016/j.drugalcdep.2019.107779

Cited by 59 publications

(72 citation statements)

References 21 publications

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“…Ranking the substances by average share, we can see that heroin is by far the most popular substance, mentioned on average by 1 in every 3 users. Its share of users, though, is steadily decreasing, with a loss of 10% reported in state-specific findings by Rosenblum et al [ 27 ]. Buprenorphine and oxycodone were the most mentioned prescription opioids; they showed fairly static behavior, while hydrocodone importance decreased over time [ 28 ], possibly due to more stringent prescription regulation starting in 2014 [ 69 ].…”

Section: Discussionmentioning

confidence: 99%

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Balsamo¹,

Bajardi²,

Salomone³

et al. 2021

J Med Internet Res

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Background The complex unfolding of the US opioid epidemic in the last 20 years has been the subject of a large body of medical and pharmacological research, and it has sparked a multidisciplinary discussion on how to implement interventions and policies to effectively control its impact on public health. Objective This study leverages Reddit, a social media platform, as the primary data source to investigate the opioid crisis. We aimed to find a large cohort of Reddit users interested in discussing the use of opioids, trace the temporal evolution of their interest, and extensively characterize patterns of the nonmedical consumption of opioids, with a focus on routes of administration and drug tampering. Methods We used a semiautomatic information retrieval algorithm to identify subreddits discussing nonmedical opioid consumption and developed a methodology based on word embedding to find alternative colloquial and nonmedical terms referring to opioid substances, routes of administration, and drug-tampering methods. We modeled the preferences of adoption of substances and routes of administration, estimating their prevalence and temporal unfolding. Ultimately, through the evaluation of odds ratios based on co-mentions, we measured the strength of association between opioid substances, routes of administration, and drug tampering. Results We identified 32 subreddits discussing nonmedical opioid usage from 2014 to 2018 and observed the evolution of interest among over 86,000 Reddit users potentially involved in firsthand opioid usage. We learned the language model of opioid consumption and provided alternative vocabularies for opioid substances, routes of administration, and drug tampering. A data-driven taxonomy of nonmedical routes of administration was proposed. We modeled the temporal evolution of interest in opioid consumption by ranking the popularity of the adoption of opioid substances and routes of administration, observing relevant trends, such as the surge in synthetic opioids like fentanyl and an increasing interest in rectal administration. In addition, we measured the strength of association between drug tampering, routes of administration, and substance consumption, finding evidence of understudied abusive behaviors, like chewing fentanyl patches and dissolving buprenorphine sublingually. Conclusions This work investigated some important consumption-related aspects of the opioid epidemic using Reddit data. We believe that our approach may provide a novel perspective for a more comprehensive understanding of nonmedical abuse of opioids substances and inform the prevention, treatment, and control of the public health effects.

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Section: Discussionmentioning

confidence: 99%

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Balsamo¹,

Bajardi²,

Salomone³

et al. 2021

J Med Internet Res

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“…Analyzing seized drug data can provide insight into the illicit drug markets and alert law enforcement agencies, public health departments, and other state and federal entities of state, regional, and emerging drug trends. Seized drug data have been shown as a complementary resource to other data resources, such as overdose deaths [ [29] , [30] , [31] ]. NFLIS-Drug can serve as a warning system for new drugs of abuse while other data collection systems provide complementary information.…”

Section: Discussionmentioning

confidence: 99%

Benzodiazepines reported in NFLIS-Drug, 2015 to 2018

Bollinger

Weimer

Heller

et al. 2021

Forensic Science International: Synergy

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The National Forensic Laboratory Information System (NFLIS) is a program of the U.S. Drug Enforcement Administration, Diversion Control Division. The NFLIS-Drug component collects drug identification results and associated information from drug cases submitted to and analyzed by federal, state, and local forensic laboratories. This paper presents national annual estimates and national and regional yearly trend differences for clonazepam, diazepam, flubromazolam, clonazolam, and etizolam using annual report rates per 100,000 persons aged 15 or older between 2015 and 2018. An estimated 263,538 benzodiazepine reports were identified by state and local laboratories between 2015 and 2018. Methamphetamine, cocaine, and heroin accounted for 32% of the drugs reported in the same item as alprazolam. Depressants and tranquilizers and narcotic analgesics were the drug classes most frequently identified in the same item as etizolam. A timeline of some benzodiazepines’ emergence in NFLIS-Drug is shown, as well as state- and county-level data for selected benzodiazepines.

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“…In conclusion, even when we account for the past via the inclusion of an ARIMA model, both weight and number of fentanyl seizures still have a statistically significant impact on overdose deaths. If one works at the level of counties, rather than at the state-wide level, then one must expand on Model 3.1 to account for autocorrelation among data points coming from the same county (Rosenblum et. al, 2020).…”

Section: Dependence On the Pastmentioning

confidence: 99%

“…Unfortunately, toxicology data from drug overdose deaths often lags by several months, so that authorities only see an influx of dangerous fentanyl analogues once it is too late to prevent the deaths these analogues cause. A new dataset, of law enforcement searches and seizures of drugs, has a much lower lag, and offers the opportunity for an "early warning system" to alert authorities to the presence of dangerous fentanyl analogues in the drug supply, before these analogues cause an increase in drug overdose deaths (Rosenblum et. al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…However, this simplistic analysis (easily communicated to non-statistician policymakers) is enough to confirm that fentanyl is driving the opioid epidemic, and to quantify the extent to which law enforcement drug seizures involving fentanyl (and its analogs) predict drug overdose deaths. That is, we quantify the efficacy of drug seizure data as an "early warning system" (Rosenblum et. al, 2020) and are able to make concrete policy recommendations, e.g., that all crime labs should share their data, and that the resulting information about the prevalence of fentanyl in the drug supply be shared with law enforcement, harm reduction professionals, and drug users.…”

Section: Introductionmentioning

confidence: 99%

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A Statistical Analysis of Drug Seizures and Opioid Overdose Deaths in Ohio from 2014 to 2018

White

Tran

2021

J Stud Res

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Objective. To examine the association between drug seizures and drug overdose deaths in Ohio from 2014 to 2018. Methods. We use linear regression, ARIMA models, and categorical data analysis to quantify the effect of drug seizure composition and weight on drug overdose deaths, to quantify the lag between drug seizures and overdose deaths, and to compare the weight distributions of drug seizures conducted by different types of law enforcement (national, local, and drug task forces). Results. Drug seizure composition and weight have strong predictive value for drug overdose deaths (F = 27.14, p < 1e-15, R² = .7799). A time series analysis demonstrates no statistically significant lag between drug seizures and overdose deaths or weight. Histograms and Kolmogorov-Smirnov tests demonstrate stark differences between seizure weight distributions of different types of law enforcement (p < 1e-7 for each pairwise comparison). Conclusions. Consideration of drug composition and weight can inform law enforcement seizure activity. To save lives, law enforcement should emphasize seizures of low weight drugs that contain fentanyl.

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The Rapidly Changing US Illicit Drug Market and the Potential for an Improved Early Warning System: Evidence from Ohio Drug Crime Labs

Cited by 59 publications

References 21 publications

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Benzodiazepines reported in NFLIS-Drug, 2015 to 2018

A Statistical Analysis of Drug Seizures and Opioid Overdose Deaths in Ohio from 2014 to 2018

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