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Exploring the Influence of Drug Trafficking Gangs on Overdose Deaths in the Largest Narcotics Market in the Eastern United States

Author

Listed:
  • Nicole J. Johnson

    (Department of Criminal Justice, Temple University, Philadelphia, PA 19122, USA)

  • Caterina G. Roman

    (Department of Criminal Justice, Temple University, Philadelphia, PA 19122, USA)

  • Alyssa K. Mendlein

    (Department of Criminal Justice, Temple University, Philadelphia, PA 19122, USA)

  • Courtney Harding

    (Philadelphia Regional Office, Pennsylvania Office of the Attorney General, Philadelphia, PA 19153, USA)

  • Melissa Francis

    (Philadelphia Regional Office, Pennsylvania Office of the Attorney General, Philadelphia, PA 19153, USA)

  • Laura Hendrick

    (Philadelphia Field Division, Drug Enforcement Administration, Philadelphia, PA 19106, USA)

Abstract

Research has found that drug markets tend to cluster in space, potentially because of the profit that can be made when customers are drawn to areas with multiple suppliers. But few studies have examined how these clusters of drug markets—which have been termed “agglomeration economies”—may be related to accidental overdose deaths, and in particular, the spatial distribution of mortality from overdose. Focusing on a large neighborhood in Philadelphia, Pennsylvania, known for its open-air drug markets, this study examines whether deaths from accidental drug overdose are clustered around street corners controlled by drug trafficking gangs. This study incorporates theoretically-informed social and physical environmental characteristics of street corner units into the models predicting overdose deaths. Given a number of environmental changes relevant to drug use locations was taking place in the focal neighborhood during the analysis period, the authors first employ a novel concentration metric—the Rare Event Concentration Coefficient—to assess clustering of overdose deaths annually between 2015 and 2019. The results of these models reveal that overdose deaths became less clustered over time and that the density was considerably lower after 2017. Hence, the predictive models in this study are focused on the two-year period between 2018 and 2019. Results from spatial econometric regression models find strong support for the association between corner drug markets and accidental overdose deaths. In addition, a number of sociostructural factors, such as concentrated disadvantage, and physical environmental factors, particularly blighted housing, are associated with a higher rate of overdose deaths. Implications from this study highlight the need for efforts that strategically coordinate law enforcement, social service provision and reductions in housing blight targeted to particular geographies.

Suggested Citation

  • Nicole J. Johnson & Caterina G. Roman & Alyssa K. Mendlein & Courtney Harding & Melissa Francis & Laura Hendrick, 2020. "Exploring the Influence of Drug Trafficking Gangs on Overdose Deaths in the Largest Narcotics Market in the Eastern United States," Social Sciences, MDPI, vol. 9(11), pages 1-21, November.
    • Handle: RePEc:gam:jscscx:v:9:y:2020:i:11:p:202-:d:441509
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    References listed on IDEAS

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    1. Piza, Eric L. & Gilchrist, Andrew M., 2018. "Measuring the effect heterogeneity of police enforcement actions across spatial contexts," Journal of Criminal Justice, Elsevier, vol. 54(C), pages 76-87.
    2. Joseph Friedman & George Karandinos & Laurie Kain Hart & Fernando Montero Castrillo & Nicholas Graetz & Philippe Bourgois, 2019. "Structural vulnerability to narcotics-driven firearm violence: An ethnographic and epidemiological study of Philadelphia’s Puerto Rican inner-city," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-25, November.
    3. Cerdá, M. & Ransome, Y. & Keyes, K.M. & Koenen, K.C. & Tardiff, K. & Vlahov, D. & Galea, S., 2013. "Revisiting the role of the urban environment in substance use: The case of analgesic overdose fatalities," American Journal of Public Health, American Public Health Association, vol. 103(12), pages 2252-2260.
    4. Valasik, Matthew, 2018. "Gang violence predictability: Using risk terrain modeling to study gang homicides and gang assaults in East Los Angeles," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 10-21.
    5. Avinash Singh Bhati, 2008. "A Generalized Cross-Entropy Approach for Modeling Spatially Correlated Counts," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 574-595.
    6. Savannah Bates & Vasiliy Leonenko & James Rineer & Georgiy Bobashev, 2019. "Using synthetic populations to understand geospatial patterns in opioid related overdose and predicted opioid misuse," Computational and Mathematical Organization Theory, Springer, vol. 25(1), pages 36-47, March.
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    Cited by:

    1. Ratcliffe, Jerry H. & Taylor, Ralph B., 2023. "The disproportionate impact of post-George Floyd violence increases on minority neighborhoods in Philadelphia," Journal of Criminal Justice, Elsevier, vol. 88(C).
    2. Matthew Valasik & Shannon E. Reid, 2021. "“The More Things Change, the More They Stay the Same”: Research on Gang-Related Violence in the 21st Century—Introduction to Special Issue," Social Sciences, MDPI, vol. 10(6), pages 1-5, June.

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