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Application of Space-Time Scan Statistics to Describe Geographic and Temporal Clustering of Visible Drug Activity

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Abstract

Knowledge of the geographic and temporal clustering of drug activity can inform where health and social services are needed and can provide insight on the potential impact of local policies on drug activity. This ecologic study assessed the spatial and temporal distribution of drug activity in Baltimore, Maryland, prior to and following the implementation of a large urban redevelopment project in East Baltimore, which began in 2003. Drug activity was measured by narcotic calls for service at the neighborhood level. A space-time scan statistic approach was used to identify statistically significant clusters of narcotic calls for service across space and time, using a discrete Poisson model. After adjusting for economic deprivation and housing vacancy, clusters of narcotic calls for service were identified among neighborhoods located in Southeast, Northeast, Northwest, and West Baltimore from 2001 to 2010. Clusters of narcotic calls for service were identified among neighborhoods located in East Baltimore from 2001 to 2003, indicating a decrease in narcotic calls thereafter. A large proportion of clusters occurred among neighborhoods located in North and Northeast Baltimore after 2003, which indicated a potential spike during this time frame. These findings suggest potential displacement of drug activity coinciding with the initiation of urban redevelopment in East Baltimore. Space-time scan statistics should be used in future research to describe the potential implications of local policies on drug activity.

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References

  1. Alexander M. The new Jim Crow: mass incarceration in the age of colorblindness. New York, NY: New Press; 2012.

  2. Small W, Kerr T, Charette J, Schechter MT, Spittal PM. Impacts of intensified police activity on injection drug users: evidence from an ethnographic investigation. Int J Drug Policy. 2006; 17(2): 85–95.

    Article  Google Scholar 

  3. Werb D, Wood E, Small W, et al. Effects of police confiscation of illicit drugs and syringes among injection drug users in Vancouver. Int J Drug Policy. 2008; 19(4): 332–8.

    Article  PubMed  PubMed Central  Google Scholar 

  4. War on Drugs: Report of the Global Commission on Drug Policy. Rio de Janeiro, Brazil: Global Commission on Drug Policy; June 2011.

  5. Harocopos A, Hough M. Drug Dealing in Open-Air Markets. Washington, DC: U.S. Department of Justice; 2005.

  6. Hoffer LD, Bobashev G, Morris RJ. Researching a local heroin market as a complex adaptive system. Am J Community Psychol. 2009; 44(3–4): 273–86.

    Article  PubMed  Google Scholar 

  7. Rengert G, Chakravorty S, Bole T, Henderson K. A geographic analysis of illegal drug markets. In: Natarajan M, Hough M, eds. Illegal drug markets: from research to prevention policy. Vol 11. Monsey, NY: Criminal Justice Press; 2000:219–239.

  8. Martinez R, Rosenfeld R, Mares D. Social disorganization, drug market activity, and neighborhood violent crime. Urban Aff Rev Thousand Oaks Calif. 2008; 43(6): 846–74.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Jennings JM, Taylor RB, Salhi RA, Furr-Holden CD, Ellen JM. Neighborhood drug markets: a risk environment for bacterial sexually transmitted infections among urban youth. Soc Sci Med. 2012; 74(8): 1240–50.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Sherman SG, Hua W, Latkin CA. Individual and environmental factors related to quitting heroin injection. Subst Use Misuse. 2004; 39(8): 1199–214.

    Article  PubMed  CAS  Google Scholar 

  11. Wooditch A, Lawton B, Taxman FS. The geography of drug abuse epidemiology among probationers in Baltimore. Journal of Drug Issues. 2013; 43(2) 231–249.

  12. Taylor RB. Breaking away from broken windows. 1st ed. Boulder, Colorado: Westview Press; 2001.

    Google Scholar 

  13. Milam AJ, Furr-Holden CD, Harrell PT, Whitaker DE, Leaf PJ. Neighborhood disorder and juvenile drug arrests: a preliminary investigation using the NIfETy instrument. Am J Drug Alcohol Abuse. 2012; 38(6): 598–602.

    Article  PubMed  Google Scholar 

  14. Cohen JR. Abandoned housing: exploring lessons from Baltimore. Housing Policy Debate. 2001; 12(3): 415–48.

    Article  Google Scholar 

  15. Washington/Baltimore: High Intensity Drug Trafficking Area Drug Market Analysis. Washington, DC: U.S. Department of Justice; 2007.

  16. DHMH. Maryland Alcohol and Drug Abuse Administration (2008) Outlook and Outcomes: Fiscal Year 2007 Annual Report. Catonsville, MD: Maryland Alcohol and Drug Abuse Administration; 2008.

  17. Koper CS, Reuter P. Suppressing illegal gun markets: lessons from drug enforcement. Law and Contemporary Problems. 1996;59(1): 119-146.

  18. Hunt D. Using GIS to identify drug markets and reduce drug-related violence. In: Thomas Y, Richardson D, Cheung I, eds. Geography and drug addiction. New York City: Springer; 2008: 395–414.

    Chapter  Google Scholar 

  19. Simon D, Burns E. The Corner: a year in the life of an Inner-City Neighborhood New York City. New York, NY: Broadway Books; 1998.

  20. Sherman SG, Latkin CA. Drug users' involvement in the drug economy: implications for harm reduction and HIV prevention programs. J Urban Health. 2002; 79(2): 266–77.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Crum RM, Lillie-Blanton M, Anthony JC. Neighborhood environment and opportunity to use cocaine and other drugs in late childhood and early adolescence. Drug Alcohol Depend. 1996; 43(3): 155–61.

    Article  PubMed  CAS  Google Scholar 

  22. Wertz JM, Sayette MA. A review of the effects of perceived drug use opportunity of self-reported urge. Exp Clin Psychopharmacol. 2001; 9(1): 3–13.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  23. Cochran SD, Grella CE, Mays VM. Do substance use norms and perceived drug availability mediate sexual orientation differences in patterns of substance use? Results from the California Quality of Life Survey II. J Stud Alcohol Drugs. 2012; 73(4): 675–85.

    PubMed  PubMed Central  Google Scholar 

  24. DeBeck K, Kerr T, Li K, Milloy MJ, Montaner J, Wood E. Incarceration and drug use patterns among a cohort of injection drug users. Addiction. 2009; 104(1): 69–76.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Latkin CA, Curry AD, Hua W, Davey MA. Direct and indirect associations of neighborhood disorder with drug use and high-risk —sexual partners. Am J Prev Med. 2007; 32(6): S234–41.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Furr-Holden CD, Lee MH, Milam AJ, Johnson RM, Lee KS, Ialongo NS. The growth of neighborhood disorder and marijuana use among urban adolescents: a case for policy and environmental interventions. J Stud Alcohol Drugs. 2011; 72(3): 371–9.

    PubMed  PubMed Central  Google Scholar 

  27. Genberg BL, Gange SJ, Go VF, et al. The effect of neighborhood deprivation and residential relocation on long-term injection cessation among injection drug users (IDUs) in Baltimore. Maryland Addict. 2011; 106(11): 1966–74.

    Article  Google Scholar 

  28. Simmons M, Jacobson J. Too big to fail? Betting a billion on East Baltimore The Daily Record. 2011; 31(2011): 1–26.

    Google Scholar 

  29. EBDI. East Baltimore Development Inc. The New East Side. Available at: http://www.ebdi.org/new_east_side.html. Accessed Jul 16 2012.

  30. The East Baltimore Revitalization Initiative. A case study for responsible development. Baltimore, MD: The Annie E. Casey Foundation; 2010.

    Google Scholar 

  31. Abt. East Baltimore Neighborhood Revitalization: Phase 1—Baseline Summary Report 2001-2005 2008.

  32. Fenton J. Baltimore has fewer than 200 killings for the first time in decades. Baltimore: The Baltimore Sun; 2012.

    Google Scholar 

  33. Fenton J. Crime spike in Northeast Baltimore alarms police, residents. Baltimore: The Baltimore Sun; 2011.

    Google Scholar 

  34. Popkin S, Rich M, Hendey L, Hayes C, Parilla J. Public Housing Transformation and Crime: Making the Case for Responsible Relocation. Washington, DC: Urban Institute; 2012.

  35. Linton SL, Kennedy CE, Latkin CA, Celentano DD, Kirk GD, Mehta SH. “Everything that looks good ain't good!”: perspectives on urban redevelopment among persons with a history of injection drug use in Baltimore, Maryland. Int J Drug Policy. 2013; 24(6): 605–13.

  36. Curtis R. Crack, cocaine and heroin: drug eras in Williamsburg, Brooklyn, 1960-2000. Addict Res Theory. 2003; 11(1): 47–63.

    Article  Google Scholar 

  37. Messer L, Laraia B, Kaufman J, et al. The development of a standardized neighborhood deprivation index. J Urban Health. 2006; 83(6): 1041–62.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Kulldorff M, Athas WF, Feurer EJ, Miller BA, Key CR. Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos. New Mexico Am J Public Health. 1998; 88(9): 1377–80.

    Article  CAS  Google Scholar 

  39. Brownstein JS, Green TC, Cassidy TA, Butler SF. Geographic information systems and pharmacoepidemiology: using spatial cluster detection to monitor local patterns of prescription opioid abuse. Pharmacoepidemiol Drug Saf. 2010; 19(6): 627–37.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Sudakin D, Power LE. Regional and temporal variation in methamphetamine-related incidents: applications of spatial and temporal scan statistics. Clin Toxicol (Phila). 2009; 47(3): 243–7.

    Article  Google Scholar 

  41. Hanson CE, Wieczorek WF. Alcohol mortality: a comparison of spatial clustering methods. Soc Sci Med. 2002; 55(5): 791–802.

    Article  PubMed  Google Scholar 

  42. Jackson MC, Huang L, Luo J, Hachey M, Feuer E. Comparison of tests for spatial heterogeneity on data with global clustering patterns and outliers. Int J Health Geogr. 2009; 8: 55.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Kulldorff M. A spatial scan statistic. Commun Stat Theory and Methods. 1997; 26: 1481–96.

    Article  Google Scholar 

  44. Klassen AC, Kulldorff M, Curriero F. Geographical clustering of prostate cancer grade and stage at diagnosis, before and after adjustment for risk factors. Int J Health Geogr. 2005; 4(1): 1.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Kulldorff M, Huang L, Pickle L, Duczmal L. An elliptic spatial scan statistic. Stat Med. 2006; 25(22): 3929–43.

    Article  PubMed  Google Scholar 

  46. Garvin EC, Cannuscio CC, Branas CC. Greening vacant lots to reduce violent crime: a randomised controlled trial. Inj Prev. 2013; 19(3): 198–203

  47. Carter SP, Carter SL, Dannenberg AL. Zoning out crime and improving community health in Sarasota, Florida: “crime prevention through environmental design”. Am J Public Health. 2003; 93(9): 1442–5.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Roylance FD. A testy reception for new East Baltimore plans. The Baltimore Sun, July 28, 2011. http://articles.baltimoresun.com/2011-07-28/business/bs-md-ebdi-beacon-park-20110728_1_market-rate-residences-community-suspicions-redevelopment-project Accessed Nov 19 2013.

  49. DeBeck K, Wood E, Qi JZ, et al. Interest in low-threshold employment among people who inject illicit drugs: implications for street disorder. Int J Drug Policy. 2011; 22(5): 376–84.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Wallace R. A synergism of plagues: “planned shrinkage”, contagious housing destruction, and AIDS in the Bronx. Environ Res. 1988; 47(1): 1–33.

    Article  PubMed  CAS  Google Scholar 

  51. Levitt SD. Understanding Why Crime Fell in the 1990s: four factors that explain the decline and six that do not. J Econ Perspect. 2004; 18(1): 163–90.

    Article  Google Scholar 

  52. Latkin CA, German D, Hua W, Curry AD. Individual-level influences on perceptions of neighborhood disorder: a multilevel analysis. J Community Psychol. 2009; 37(1): 122–33.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Roux AVD. Neighborhoods and health: where are we and were do we go from here? Revue D Epidemiologie Et De Sante Publique. 2007; 55(1): 13–21.

    Article  Google Scholar 

  54. Cooper HL, Bossak B, Tempalski B, Des Jarlais DC, Friedman SR. Geographic approaches to quantifying the risk environment: drug-related law enforcement and access to syringe exchange programmes. Int J Drug Policy. 2009; 20(3): 217–26.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Weisburd D, Bernasco W, Bruinsma G. Putting crime in its place units of analysis in geographic criminology. New York: Springer; 2009.

  56. Jones SG, Kulldorff M. Influence of spatial resolution on space-time disease cluster detection. Plos One. 2012; 7(10): e48036.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

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Acknowledgments

This research was funded by the National Institute on Drug Abuse at the National Institutes of Health (Grant number: R01DA012568). Additional support for this research was provided by the National Institute on Drug Abuse at the National Institutes of Health (Grant numbers: T32DA007292 (Linton) and K01DA022298-01A1 (Jennings). The authors would like to thank Matthew Kachura (Baltimore Neighborhood Indicator Alliance) and Cheryl Knott (Baltimore Neighborhood Indicator Alliance), who compiled the data on narcotic calls for service and housing vacancy, and the Baltimore City Police Department for providing insight on how narcotic calls for service are measured.

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Authors and Affiliations

  1. Department of Behavioral Sciences and Health Education, Rollins School of Public Health at Emory University, 1518 Clifton Road NE, GCR 527, Atlanta, GA, 30322, USA

    Sabriya L. Linton

  2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Sabriya L. Linton, Jacky M. Jennings & Shruti H. Mehta

  3. Department of Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Jacky M. Jennings

  4. Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Carl A. Latkin

  5. Social Health Concepts and Practice, Baltimore, MD, USA

    Marisela B. Gomez

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  1. Sabriya L. Linton
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Correspondence to Sabriya L. Linton.

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Linton, S.L., Jennings, J.M., Latkin, C.A. et al. Application of Space-Time Scan Statistics to Describe Geographic and Temporal Clustering of Visible Drug Activity. J Urban Health 91, 940–956 (2014). https://doi.org/10.1007/s11524-014-9890-7

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