Research paperTransnational cocaine and heroin flow networks in western Europe: A comparison
Introduction
Cocaine and heroin users account for roughly 39 million to 55.5 million people worldwide (United Nations Office on Drugs and Crime (UNODC), 2012). Despite increased law enforcement activities, consumption of these two drugs continued unabated (Wiessing, Olszewski, Klempová, Vicente, & Griffiths, 2009). At a time when drug policy is increasingly taking an integrated turn and policy and enforcement organizations are increasingly adopting strategies that cut across drug types, the comparative study of drug-related phenomena such as trafficking is becoming increasingly important (European Union, 2012). The need for such analysis is compounded by the phenomenon of drug trafficking organizations diversifying their portfolios from a single drug into multiple drug categories, as in the case of Mexico's Sinaloa cartel, which now deals in cannabis, heroin, and methamphetamine (Keefe, 2012).
The magnitude of the illegal drug trade and its resulting problems have led governments and the drug policy research community to invest in producing large and comprehensive datasets on a variety of phenomena relating to this traffic (European Monitoring Centre for Drugs and Drug Addiction, 2008, UNODC, 2013, United States Department of Justice, 2014). These datasets contain information on prices, seizures, and flows of drugs, which lend themselves to a variety of interesting and potentially valuable analyses. Yet, with a few recent exceptions (Boivin, 2013, Boivin, 2014a, Boivin, 2014b), given the quantity and content of the available data, surprisingly little systematic research has been conducted at the country level that applies the methods of network analysis to the available data on these drugs. The main objective of this paper is, therefore, to use network analysis to compare the properties of drug flow networks for cocaine and heroin in a group of 17 western European countries, inferred using data on wholesale prices for these drugs, with a view to understanding their similarities and differences and to examining the implications of these findings for drug policy. Data permitting, the analytic methods presented in this paper can be applied to the analysis of other illegal drugs, including cannabis and amphetamine-type stimulants (ATS), in particular, and to other illegally trafficked goods and markets, including but not restricted to those for weapons, people, and wildlife.
The network approach to the analysis of drug flows is potentially rewarding on a number of levels. At the level of a single network, it can provide insights into how and why the network displays a particular set of structural properties, with implications for drug control policies including resource allocation and interdiction. Notions including but not restricted to centralization, core–periphery structure, path-redundancy, and membership can be brought to bear on these issues. At the level of an individual country, network analysis can identify the position and importance of each country in a network and the specific paths through which a drug enters, transits through, or exits a specific country. In doing so, such analysis can inform strategies for interventions by providing insights into locations in the network where the allocation of resources is most likely to be effective, both at the country level and at the level of the entire network. Comparisons of networks can likewise shed light on the degree to which an integrated approach to drug control is likely to work, and the degree to which customization for specific drugs and trafficking routes is warranted. Comparisons of the positions of specific countries in different trafficking networks can yield insights into whether the trade in one drug operates in a similar manner to the trade in another drug, which in turn can offer clues about the degree to which trafficking of one drug uses the same infrastructure as another drug.
Section snippets
Literature review
In this section, we briefly describe two literatures on which this study is based. The first is the literature on drug markets, prices, price data, and the rich variety of information that is contained in these data – the network data on which this study is based are constructed using drug price data. The second literature is the relatively small body of work that quantitatively or qualitatively analyzes the organizational structure of drug networks, using concepts from fields including network
Analytic approach
The data used in this paper represent two networks of transnational drug flows (i.e., cocaine and heroin) for 17 countries of western Europe. The most common visualization of a network is that of a collection of nodes (or vertices), representing countries, and lines or ‘edges’ that connect nodes, representing drug flows between pairs of countries. While network flows can in theory be bi-directional (i.e., country A sends to country B and vice versa), our analysis adopts the UNODC convention in
Results
The results of the triad census, shown in Table 1, reveal some interesting contrasts between the structure of the heroin and cocaine networks in Europe. The cocaine network contains many more empty triads and fewer triads with one or more connections than does the heroin network. In other words, there are many more paths for the flow of heroin through Europe than for cocaine. Interestingly, there is one type of non-empty triad, the directed line (see Fig. 1), for which the cocaine network
Discussion and conclusions
In light of the size of the cocaine and heroin problem in Europe and worldwide and the integrated nature of drug policy making and research, the comparative study of drug flow networks can provide important insights into issues of relevance to drug control efforts. Methods of network analysis originally developed in the fields of engineering and sociology can capture and characterize important features of networks that may not be visible upon casual observation. For example, in this study, it
Conflict of interest
The authors declare that there is no conflict of interest.
References (62)
Risks, prices, and positions: A social network analysis of illegal drug trafficking in the world-economy?
International Journal of Drug Policy
(2014)Domestic geographic variation in illicit drug prices
Journal of Urban Economics
(1995)- et al.
The stability of centrality measures when networks are sampled
Social Networks
(2003) Centrality in networks: I. Conceptual clarification
Social Networks
(1979)Network centralization with the Gil Schmidt power centrality index
Social Networks
(2009)On the resilience of illegal drug markets
Global Crime
(2007)Drug trafficking networks in the world-economy
Crime and Networks
(2013)Macrosocial network analysis: The case of transnational drug trafficking
Lecture Notes in Social Networks
(2014)- et al.
Betweenness centrality measures for directed graphs
Social Networks
(1994) - et al.
Models of core/periphery structure
Social Networks
(1999)
UCINET for windows: Software for social network analysis
What price data tells us about drug markets
Journal of Drug Issues
How drug enforcement affects drug prices
Crime and Justice
Marijuana price gradients: Implications for exports and export-generated tax revenue for California after legalization
Journal of Drug Issues
What the price data tell us about heroin flows across Europe
International Journal of Comparative and Applied Criminal Justice
Inferring cocaine flows across Europe: Evidence from price data
Journal of Drug Policy Analysis
How powdered cocaine flows across the United States evidence from open-source price data
Journal of Drug Issues
Opium: Uncovering the politics of the poppy
The Andean cocaine industry
Pricing and packaging: The case of marijuana
Journal of Business
Telling the story of drugs in West Africa: The newest front on a losing war
The world trade network
The World Economy
Drug smugglers on drug smuggling
Research on upper-level drug trafficking: A review
Journal of Drug Issues
Monitoring the supply of heroin to Europe
EU drugs strategy 2013–20
Official Journal of the European Union
The centrality of groups and classes?
The Journal of Mathematical Sociology
Cocaine and heroin in Europe 1983–1993: A cross-national comparison of trafficking and prices
The British Journal of Criminology
Andean cocaine: The making of a global drug
Introduction to social network methods
West Africa and the transnational trade in illegal drugs: Physical properties, policing, and power
Africa Review
Cited by (22)
Review of the most common chemometric techniques in illicit drug profiling
2019, Forensic Science InternationalCitation Excerpt :Additionally, at an international level, network analysis could identify countries that are pivotal to drug markets. This could aid the suggestion of strategic targets for disrupting international drug trade [145]. It is possible to receive an indicator of how well implemented strategies are disrupting drug markets by analysing the extent of certain CCs at a given time.
Drug affordability–potential tool for comparing illicit drug markets
2018, International Journal of Drug PolicyThe importance of economic context in interpreting forensic data on drug trafficking networks
2018, Forensic Science InternationalThe determinants of heroin flows in Europe: A latent space approach
2017, Social NetworksCitation Excerpt :The results show that some characteristics of the importer (e.g. risk of arrest), when viewed in conjunction with the position of the country within the global trafficking network, can predict wholesale price mark-ups (Boivin, 2014b). Chandra and colleagues provide the second key contribution to the network analysis of drug trafficking flows (Chandra et al., 2011; Chandra and Barkell, 2012; Chandra and Joba, 2015; Chandra et al., 2016). The authors use wholesale prices reported by the UNODC between 2000 and 2008 to infer the presence and direction of transnational flows of heroin (Chandra and Barkell, 2012) and cocaine (Chandra et al., 2011) for seventeen western European countries.