Risks, prices, and positions: A social network analysis of illegal drug trafficking in the world-economy

Social network analysis for medical narcotics in South Korea: focusing on patients and healthcare organizations

BACKGROUND

Medical narcotics must be administered under medical supervision because of their potential for misuse and abuse, leading to more dangerous and addictive substances. The control of medical narcotics requires close monitoring to ensure that they remain safe and effective. This study proposes a methodology that can effectively identify the overprescription of medical narcotics in hospitals and patients.

METHODS

Social network analysis (SNA) was applied to prescription networks for medical narcotics. Prescription data were obtained from the Narcotics Information Management System in South Korea, which contains all data on narcotic usage nationwide. Two-mode networks comprising hospitals and patients were constructed based on prescription data from 2019 to 2021 for the three most significant narcotics: appetite suppressants, zolpidem, and propofol. Two-mode networks were then converted into one-mode networks for hospitals. Network structures and characteristics were analyzed to identify hospitals suspected of overprescribing.

RESULTS

The SNA identified hospitals that overprescribed medical narcotics. Patients suspected of experiencing narcotic addiction seek treatment in such hospitals. The structure of the network was different for the three narcotics. While appetite suppressants and propofol networks had a more centralized structure, zolpidem networks showed a less centralized but more fragmented structure. During the analysis, two types of hospitals caught our attention: one with a high degree, meaning that potential abusers have frequently visited the hospital, and the other with a high weighted degree, meaning that the hospital may overprescribe. For appetite suppressants, these two types of hospitals matched 84.6%, compared with 30.0% for propofol. In all three narcotics, clinics accounted for the largest share of the network. Patients using appetite suppressants were most likely to visit multiple locations, whereas those using zolpidem and propofol tended to form communities around their neighborhoods.

CONCLUSIONS

The significance of this study lies in its analysis of nationwide narcotic use reports and the differences observed across different types of narcotics. The social network structure between hospitals and patients varies depending on the composition of the medical narcotics. Therefore, these characteristics should be considered when controlling medication with narcotics. The results of this study provide guidelines for controlling narcotic use in other countries.

Drug Smuggling Seizures: The Effects of Reporting Consistency and Quality on the Observed Transnational Structure

If it is possible to overcome significant data challenges, social network analytics could be used to expose structural vulnerabilities in transnational drug smuggling operations, offering clear targets for crime control efforts that aim to disrupt transhipment. This study explores the extent to which data inclusion decisions might distort the emergent structure of nation-to-nation smuggling networks mapped with aggregate intelligence using United Nations Office on Drugs and Crime (UNODC) incident level seizure data (2010–2016). Bivariate exponential random graph models (ERGM) show that relaxing data inclusion standards exposes illicit backchannels (reciprocity) and a more complete picture of major transhipment activity (activity and popularity spread) than would be otherwise undetected. Relaxed data inclusion standards may help to adjust for the data limitations associated with the detection of rare events and inconsistent reporting practices, if usage rules are followed.

Uncertainty and risk: A framework for understanding pricing in online drug markets

BACKGROUND

The pricing of illicit drugs is typically approached within the risks and prices framework. Recent sociological and economic studies of prices in online drug markets have stressed the centrality of reputation for price formation. In this paper, we propose an account of price formation that is based on the risks and prices framework, but also incorporates internal social organization to explain price variation. We assess the model empirically, and extend the current empirical literature by including payment methods and informal ranking as influences on drug pricing.

METHODS

We apply our model to estimate the prices of cannabis, cocaine, and heroin in two online drug markets, cryptomarkets (n = 92.246). Using multilevel linear regression, we assess the influence of product qualities, reputation, payment methods, and informal ranking on price formation.

RESULTS

We observe extensive quantity discounts varying across substances and countries, and find premia and discounts associated with product qualities. We find evidence of payment method price adjustment, but contrary to expectation we observe conflicting evidence concerning reputation and status. We assess the robustness of our findings concerning reputation by comparing our model to previous approaches and alternative specifications.

CONCLUSION

We contribute to an emerging economic sociological approach to the study illicit markets by developing an account of price formation that incorporates cybercrime scholarship and the risks and prices framework. We find that prices in online drug markets reflect both external institutional constraint and internal social processes that reduce uncertainty.

Understanding Australian methylamphetamine drug markets through relational, temporal and spatial analyses

In the area of illicit drugs, forensic case data have proven effective at detecting links between seizures and providing greater insights into illicit drug markets. This research explored the application of mathematical and statistical techniques to several chemical profiles of Australian methylamphetamine seizures. The main aim was to create and deliver a method that would expand the use of illicit drug profiling for strategic intelligence purposes, contributing to the fight against illicit drug trafficking. The use of comparison metrics and clustering analysis to determine links between existing illicit drug specimens and subsequent new specimens was evaluated and automated. Relational, temporal and spatial analyses were subsequently used to gain an insight into illicit drug markets. Relational analysis identified clusters of seizures central to the network. Temporal analysis then provided insights into the behaviour of distribution markets, specifically the emergence and extinction of certain clusters of seizures over time. Spatial analysis aided the understanding of the inter-jurisdictional nature of illicit drug markets. These analyses allowed for the generation of strategic intelligence relating to when and where the Australian methylamphetamine illicit drug market was the most active. Additionally, the strategic level trends identified clusters of seizures that were worth investigating further. These clusters were explored through a case study, which exploited additional chemical profiling data to provide drug market knowledge at an operational level. In turn, the intelligence produced at various levels could allow relevant law enforcement agencies to take necessary measures in disrupting markets.

The Salience of Antisocial Personality Disorder for Predicting Substance Use and Violent Behavior: The Moderating Role of Deviant Peers

Deviant peer association and antisocial personality disorder are risk factors for drug use and violent offending. However, there has yet to be research that focuses on how deviant peer association may moderate the impact of antisocial personality disorder on these outcomes. Data from Wave 10 of the Pathways to Desistance dataset were used in analyses. Negative binomial regression was used to estimate the effects of covariates on violent offending. Ordered logistic regression was used to estimate the effects of covariates on substance use outcomes. Results indicated that deviant peer association moderated the impact of antisocial personality disorder on violent offending frequency and marijuana use frequency. The direction of this interaction effect was positive for marijuana use. The direction of this moderation was negative for violent offending, indicating that antisocial personality disorder–diagnosed individuals commit fewer violent offenses at similar levels of deviant peer association as nonafflicted participants.

Social network Analysis-based classifier (SNAc): A case study on time course gene expression data

BACKGROUND AND OBJECTIVES

Social Network Analysis is an attractive approach to model and analyze complex networks. In recent years, several bioinformatics related networks have been modeled and analyzed thoroughly using social network analysis. The objective of this study is to build a social network analysis based classifier for time sequential data.

METHODS

In this work, we model a genomic time sequential data as a 'social' network of interactions. We define interactions as similarity of patients' measurements. Using this 'genomic social network', we develop a classification model called Social Network Analysis-based Classifier.

RESULTS

We conducted some experiments to demonstrate how the developed Social Network Analysis-based Classifier outperforms traditional classifiers by effectively classifying a time sequential genomic dataset. Best achieved accuracy is 64.51% and best f-measure is 78.34%.

CONCLUSIONS

Our study emphasized Social Network Analysis-based Classifier Model as a powerful technique for analyzing a time sequential dataset. Eventually, the plan is to develop and evolve the Social Network Analysis-based Classifier model into a general classifier.

How Do Illicit Drugs Move Across Countries? A Network Analysis of the Heroin Supply to Europe

Illicit drugs are trafficked across manifold borders before ultimately reaching consumers. Consequently, interdiction of cross-border drug trafficking forms a critical component of the European Union’s initiative to reduce drug supplies. However, there is contradictory evidence about its effectiveness, which is due, in part, to a paucity of information about how drugs flow across borders. This study uses a network approach to analyze international drug trafficking both to and within Europe, drawing on several perspectives to delineate the factors that affect how drug shipments move across borders. The analysis explicates how drug trafficking is concentrated along specific routes; moreover, we demonstrate that its structure is not random but, rather, driven by specific factors. In particular, corruption and social and geographical proximity are key factors explaining the configuration of heroin supply to European countries. This study also provides essential insights into the disruption of traffickers’ illicit activities.

Determinants of heroin retail prices in metropolitan France: Discounts, purity and local markets

INTRODUCTION AND AIMS

Field studies have indicated a recent increase in heroin availability and use in France, and yet very little is known about the mechanisms underlying heroin retail prices. This paper offers a first attempt at identifying the determinants of heroin pricing, to measure quantity discounts and assess the influence of purity on street prices, while controlling for a geographical effect.

DESIGN AND METHODS

Data on heroin samples were collected during 2011 in seven urban areas of metropolitan France. Ordinary least squares regression was used to model the associations between price, quantity, purity and other independent variables.

RESULTS

Quantity remains the most influential variable on heroin pricing. We estimate that a 10% increase in the size of a transaction leads to a 2.3% decrease in the unit price. Assessed purity proved to be significant, although in modest proportion. Sociodemographic characteristics, such as gender, users' experience and relationships with dealers, proved to be insignificant. Heroin retail prices vary according to a geographical gradient related to the routes of entry and distribution.

DISCUSSION AND CONCLUSIONS

As a credence good, heroin retail prices in France are affected by more than simply the traditional supply and demand relationship. The results of this study also underline the limitations of a quantitative framework and should be complemented by further ethnographic research to obtain an in-depth understanding of local markets. Policies should be designed to better take local disparities into account.[Lahaie E, Janssen E, Cadet-Taïrou A. Determinants of heroin retail prices in metropolitan France:Discounts, purity and local markets. Drug Alcohol Rev 2016;35:597-604].