Is Gun Violence Contagious? A Spatiotemporal Test

Original Paper

Abstract

Objectives

Existing theories of gun violence predict stable spatial concentrations and contagious diffusion of gun violence into surrounding areas. Recent empirical studies have reported confirmatory evidence of such spatiotemporal diffusion of gun violence. However, existing space/time interaction tests cannot readily distinguish spatiotemporal clustering from spatiotemporal diffusion. This leaves as an open question whether gun violence actually is contagious or merely clusters in space and time. Compounding this problem, gun violence is subject to considerable measurement error with many nonfatal shootings going unreported to police.

Methods

Using point process data from an acoustical gunshot locator system and a combination of Bayesian spatiotemporal point process modeling and classical space/time interaction tests, this paper distinguishes between clustered but non-diffusing gun violence and clustered gun violence resulting from diffusion.

Results

This paper demonstrates that contemporary urban gun violence in a metropolitan city does diffuse in space and time, but only slightly.

Conclusions

These results suggest that a disease model for the spread of gun violence in space and time may not be a good fit for most of the geographically stable and temporally stochastic process observed. And that existing space/time tests may not be adequate tests for spatiotemporal gun violence diffusion models.

Keywords

Gun violence Contagion Spatiotemporal methods 

References

  1. Bartlett MS (1964) The spectral analysis of two-dimensional point processes. Biometrika 51(3/4):299–311CrossRefGoogle Scholar
  2. Blumstein A (1995) ‘Youth violence, guns, and the illicit-drug industry’. The J Crim Law and Criminol (1973) 86(1):10–36CrossRefGoogle Scholar
  3. Braga AA (2005) Hot spots policing and crime prevention: a systematic review of randomized controlled trials. J Exp Criminol 1(3):317–342CrossRefGoogle Scholar
  4. Braga AA, Papachristos AV, Hureau DM (2010) The concentration and stability of gun violence at micro places in Boston, 1980–2008. J Quant Criminol 26(1):33–53CrossRefGoogle Scholar
  5. Branas CC, Cheney RA, MacDonald JM, Tam VW, Jackson TD, Ten Have TR (2011) A difference-in-differences analysis of health, safety, and greening vacant urban space. Am J Epidemiol 174(11):1296–1306CrossRefGoogle Scholar
  6. Branas CC, Jacoby S, Andreyeva E (2017) Firearm violence as a diseasehot people or hot spots? JAMA Intern Med 177(3):333–334CrossRefGoogle Scholar
  7. Chicago Police Department (2012) 2011 Chicago Murder Analysis. Technical report, City of Chicago, Chicago, ILGoogle Scholar
  8. Christakis NA, Fowler JH (2007) The spread of obesity in a large social network over 32 years. N Engl J Med 357(4):370–379CrossRefGoogle Scholar
  9. Christoffel KK (2007) Firearm injuries: epidemic then, endemic now. Am J Public Health 97(4):626–629CrossRefGoogle Scholar
  10. Cohen J, Tita G (1999) Diffusion in homicide: exploring a general method for detecting spatial diffusion processes. J Quant Criminol 15(4):451–493CrossRefGoogle Scholar
  11. Coleman J, Katz E, Menzel H (1957) The diffusion of an innovation among physicians. Sociometry 20(4):253–270CrossRefGoogle Scholar
  12. Cressie N, Wikle C (2011) Statistics for spatio-temporal data. Wiley, HobokenGoogle Scholar
  13. de Tarde G (1903) The laws of imitation. H. Holt and Company, New YorkGoogle Scholar
  14. Diggle PJ, Chetwynd AG, Hggkvist R, Morris SE (1995) Second-order analysis of space-time clustering. Stat Methods in Med Res 4(2):124–136CrossRefGoogle Scholar
  15. Diggle PJ, Moraga P, Rowlingson B, Taylor BM (2013) Spatial and spatio-temporal log-gaussian cox processes: extending the geostatistical paradigm. Stat Sci 28(4):542–563CrossRefGoogle Scholar
  16. Diggle P, Rowlingson B, Su T-L (2005) Point process methodology for on-line spatio-temporal disease surveillance. Environmetrics 16(5):423–434CrossRefGoogle Scholar
  17. Dodge KA (2008) Framing public policy and prevention of chronic violence in american youths. The Am Psychol 63(7):573–590CrossRefGoogle Scholar
  18. Fagan J, Wilkinson DL, Davies G (2007) Social contagion of violence. In: Flannery DJ, Vazsonyi AT, Waldman ID (eds) The cambridge handbook of violent behavior and aggression. Cambridge University Press, New York, pp 688–726CrossRefGoogle Scholar
  19. Gelman A, Jakulin A, Pittau MG, Su Y-S (2008) ‘A weakly informative default prior distribution for logistic and other regression models’. The Ann Appl Stat, 360–1383.Google Scholar
  20. Green B, Horel T, Papachristos AV (2017) Modeling contagion through social networks to explain and predict gunshot violence in chicago, 2006–2014. JAMA Intern Med 177(3):326–333CrossRefGoogle Scholar
  21. Groff ER, Ratcliffe JH, Haberman CP, Sorg ET, Joyce NM, Taylor RB (2015) Does what police do at hot spots matter? The philadelphia policing tactics experiment. Criminology 53(1):23–53CrossRefGoogle Scholar
  22. Hemingway D (2004) Private guns. Public Health, University of Michigan PressCrossRefGoogle Scholar
  23. Johnson SD (2008) Repeat burglary victimisation: a tale of two theories. J Exp Criminol 4(3):215–240CrossRefGoogle Scholar
  24. Johnson SD, Bernasco W, Bowers KJ, Elffers H, Ratcliffe J, Rengert G, Townsley M (2007) Space-time patterns of risk: a cross national assessment of residential burglary victimization. J Quant Criminol 23(3):201–219CrossRefGoogle Scholar
  25. Johnson SD, Bowers KJ (2004) The stability of space-time clusters of burglary. Br J Criminol 44(1):55–65CrossRefGoogle Scholar
  26. Knox EG (1964a) The detection of space-time interactions. J Royal Stat Soc Ser C (Appl Stat) 13(1):25–29Google Scholar
  27. Knox G (1964b) Epidemiology of childhood leukaemia in northumberland and Durham. Br J Prevent Soc Med 18(1):17–24Google Scholar
  28. Loftin C (1986) Assaultive violence as a contagious social process. Bull N Y Acad Med 62(5):550–555Google Scholar
  29. Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27(2 Part 1):209–220Google Scholar
  30. Mares D, Blackburn E (2012) Evaluating the effectiveness of an acoustic gunshot location system in St. Louis, MO’. Policing 6(1):26–42CrossRefGoogle Scholar
  31. Messner SF, Anselin L, Baller RD, Hawkins DF, Deane G, Tolnay SE (1999) The spatial patterning of county homicide rates: an application of exploratory spatial data analysis. J Quant Criminol 15(4):423–450CrossRefGoogle Scholar
  32. Metropolitan Police Department (2006) A Report on Juvenile and Adult Homicide in the Distict of Columbia. Technical report, Metropolitan Police Department, Research and Resource Development Department, Washington, D.CGoogle Scholar
  33. Meyer S, Warnke I, Rossler W, Held L (2016) Model-based testing for space-time interaction using point processes: an application to psychiatric hospital admissions in an urban area. Spat Spatio-temporal Epidemiol 17:15–25CrossRefGoogle Scholar
  34. Mohler G (2013) Modeling and estimation of multi-source clustering in crime and security data. Ann Appl Stat 7(3):1525–1539CrossRefGoogle Scholar
  35. Mohler G (2014) Marked point process hotspot maps for homicide and gun crime prediction in chicago. Int J Forecast 30(3):491–497CrossRefGoogle Scholar
  36. Mohler GO, Short MB, Brantingham PJ, Schoenberg FP, Tita GE (2011) Self-exciting point process modeling of crime. J Am Stat Assoc 106(493):100–108CrossRefGoogle Scholar
  37. Morenoff JD, Sampson RJ, Raudenbush SW (2001) Neighborhood inequality, collective efficacy, and the spatial dynamics of urban violence*. Criminology 39(3):517–558CrossRefGoogle Scholar
  38. Ornstein JT, Hammond RA (2017) The burglary boost: a note on detecting contagion using the Knox test. J Quant Criminol 33(1):65–75CrossRefGoogle Scholar
  39. Papachristos A (2009) Murder by structure: dominance relations and the social structure of gang homicide. Am J Sociol 115(1):74–128CrossRefGoogle Scholar
  40. Papachristos A, Anthony B, Piza E, Grossman L (2016) The company you keep? The spillover effects of gang membership on individual gunshot victimization in a co-offending network. Criminology 53:624–649CrossRefGoogle Scholar
  41. Patel DM, Simon MA, Taylor RM (2012) Contagion of violence–workshop summary, technical report. Institute of Medicine and National Research Council of the National Academies, WashingtonGoogle Scholar
  42. Petho A, Fallis DS, Keating D (2013) Investigations. In: Gunfire detection system captures about 39,000 shooting incidents in the District. The Washington Post. https://www.washingtonpost.com/investigations/shotspotter-detection-system-documents-39000-shooting-incidents-in-the-district/2013/11/02/055f8e9c-2ab1-11e3-8ade-a1f23cda135e_story.html
  43. Philadelphia Police Department (2014) Murder/Shooting Analysis 2013. Technical report, Philadelphia Police Department, Philadelphia, PAGoogle Scholar
  44. Ramlau-Hansen H (1983) ‘Smoothing counting process intensities by means of kernel functions’. The Ann Stat, 453–466.Google Scholar
  45. Ratcliffe JH, Rengert GF (2008) Near-repeat patterns in Philadelphia shootings. Secur J 21(1):58–76CrossRefGoogle Scholar
  46. Reiss AJ, Roth JA, Miczek KA, National Research Council (US). Panel on the understanding and control of violent behavior (1993), understanding and preventing violence. National Academy Press-1994, Washington, DCGoogle Scholar
  47. Rosenfeld R, Bray TM, Egley A (1999) Facilitating violence: a comparison of gang-motivated, gang-affiliated, and nongang youth homicides. J Quant Criminol 15(4):495–516CrossRefGoogle Scholar
  48. Sallai J, Hedgecock W, Volgyesi P, Nadas A, Balogh G, Ledeczi A (2011) Weapon classification and shooter localization using distributed multichannel acoustic sensors. J Syst Archit 57(10):869–885CrossRefGoogle Scholar
  49. Shalizi CR, Thomas AC (2011) Homophily and contagion are generically confounded in observational social network studies. Sociol Methods Res 40(2):211–329CrossRefGoogle Scholar
  50. Short MB, Brantingham PJ, Bertozzi AL, Tita GE (2010) Dissipation and displacement of hotspots in reaction-diffusion models of crime. Proc Nat Acad Sci 107(9):3961–3965CrossRefGoogle Scholar
  51. Short M, Mohler G, Brantingham PJ, Tita G (2014) Gang rivalry dynamics via couple point process networks. Disc Contin Dyn Syst 19(5):1459–1477CrossRefGoogle Scholar
  52. Skogan W, Hartnett S, Bump N, Dubois J (2009) Evaluation of ceasefire-Chicago, technical report. US, Department of Justice, WashingtonGoogle Scholar
  53. Stan Development Team (2016) ‘Stan: A c++ library for probability and sampling, version 2.9.0’Google Scholar
  54. Tita G, Cohen J (2004) Measuring spatial diffusion of shots fired activity. In: Goodchild MF, Janelle DG (eds) Spatially integrated social science. Oxford University Press, New York, pp 171–204Google Scholar
  55. Tita G, Ridgeway G (2007) The impact of gang formation on local patterns of crime. J Res Crime and Delinquency 44(2):208–237CrossRefGoogle Scholar
  56. Tita G, Riley J, Ridgeway G, Grammich C, Abrahamse A, Greenwood P (2003) Reducing gun violence: results from an intervention in east Los Angeles. RAND Corporation, Santa MonicaGoogle Scholar
  57. Townsley M, Homel R, Chaseling J (2003) Infectious Burglaries. A Test of the Near Repeat Hypothesis. British Journal of Criminology 43(3):615–633CrossRefGoogle Scholar
  58. Webster DW, Whitehill JM, Vernick JS, Curriero FC (2012) Effects of baltimores safe streets program on gun violence: a replication of Chicagos ceasefire program. J Urban Health 90(1):27–40CrossRefGoogle Scholar
  59. Weisburd D, Groff ER, Yang S-M (2012) The criminology of place: street segments and our understanding of the crime problem. Oxford University Press, OxfordCrossRefGoogle Scholar
  60. Wooditch A, Weisburd D (2015) Using space-time analysis to evaluate criminal justice programs: an application to stop-question-frisk practices. J Quant Criminol 32(2):1–23Google Scholar
  61. Zimring F (1967) Is gun control likely to reduce violent killings. Univ Chicago Law Rev 35(4):721CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.Department of CriminologyUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of StatisticsUniversity of OxfordOxfordUnited Kingdom

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