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A mathematical model of serious and minor criminal activity

Published online by Cambridge University Press:  08 April 2016

A. A. LACEY
Affiliation:
Department of Mathematics, Heriot-Watt University, Edinburgh, EH14 4AS, UK email: a.a.Lacey@hw.ac.uk, mtsardakas@gmail.com
M. N. TSARDAKAS
Affiliation:
Department of Mathematics, Heriot-Watt University, Edinburgh, EH14 4AS, UK email: a.a.Lacey@hw.ac.uk, mtsardakas@gmail.com
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Abstract

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Using mathematical methods to understand and model crime is a recent idea that has drawn considerable attention from researchers during the last five years. From the plethora of models that have been proposed, perhaps the most successful one has been a diffusion-type differential equations model that describes how the number of criminals evolves in a specific area. We propose a more detailed form of this model that allows for two distinct criminal types associated with major and minor crime. Additionally, we examine a stochastic variant of the model that represents more realistically the ‘generation’ of new criminals. Numerical solutions from both models are presented and compared with actual crime data for the Greater Manchester area. Agreement between simulations and actual data is satisfactory. A preliminary statistical analysis of the data also supports the model's potential to describe crime.

Type
Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2016

References

[1]Andresen, M. A. & Malleson, N. (2013) Crime seasonality and its variations across space. Appl. Geography 43, 2535.Google Scholar
[2]Blumstein, A. (2002) Crime modeling. Oper. Res. 50 (1), 1624.Google Scholar
[3]Brantingham, P. J. & Brantingham, P. L. (1984) Patterns in Crime, Macmillan/McGraw-Hill School Division, New York.Google Scholar
[4]Criminal activity data (July 2014) URL: http://data.police.uk, accessed 2 February 2015.Google Scholar
[5]Epstein, J. M. (2002) Modeling civil violence: An agent-based computational approach. Proc. Natl Acad Sci. USA 99 (Suppl 3), 72437250.Google Scholar
[6]Evans, D., Fyfe, N. & Herbert, D. (2002) Crime, Policing and Place: Essays in Environmental Criminology, Taylor & Francis, London.Google Scholar
[7]Gordon, M. B., Iglesias, J. R., Semeshenko, V. & Nadal, J. P. (2009) Crime and punishment: The economic burden of impunity. Eur. Phys. J. B 68 (1), 133144.Google Scholar
[8]Gorr, W., Olligschlaeger, A. & Thompson, Y. (2003) Short-term forecasting of crime. Int. J. Forecast. 19 (4), 579594.CrossRefGoogle Scholar
[9]Johnson, S. D., Bowers, K. J. & Hirschfield, A. (1997) New insights into the spatial and temporal distribution of repeat victimization. Br. J. Criminology 37 (2), 224241.Google Scholar
[10]Johnson, S. D. & Bowers, K. J. (2004) The burglary as clue to the future the beginnings of prospective hot-spotting. Eur. J. Criminology 1 (2), 237255.CrossRefGoogle Scholar
[11]Kovandzic, T. V. & Sloan, J. J. (2002) Police levels and crime rates revisited: A county-level analysis from Florida (1980–1998). J. Criminal Justice 30 (1), 6576.Google Scholar
[12]Lahey, B. B., Moffitt, T. E. & Caspi, A. (2003) Causes of Conduct Disorder and Juvenile Delinquency, Guilford Press, New York.Google Scholar
[13]Malleson, N., Heppenstall, A. & See, L. (2012) Using an agent-based crime simulation to predict the effects of urban regeneration on individual household burglary risk. Environ. Plann. B Plan. 40 (3), 405426.Google Scholar
[14]McCalla, S. G., Short, M. B. & Brantingham, P. J. (2012) The effects of sacred value networks within an evolutionary, adversarial game. J. Stat. Phys. 151 (3), 116.Google Scholar
[15]Mohler, G. O., Short, M. B., Brantingham, P. J., Schoenberg, F. P. & Tita, G. E. (2011) Self-exciting point process modeling of crime. J. Am. Stat. Assoc. 106 (493), 100108.CrossRefGoogle Scholar
[16]Nuño, J. C., Herrero, M. A. & Primicerio, M. (2008) A triangle model of criminality. Physica A: Stat. Mech. Appl. 387 (12), 29262936.CrossRefGoogle Scholar
[17]Sampson, R. J. & Raudenbush, S. W. (1999) Systematic social observation of public spaces: A new look at disorder in Urban neighborhoods. Am. J. Soc. 105 (3), 603651.Google Scholar
[18]Short, M. B., Bertozzi, A. L. & Brantingham, P. J. (2010) Nonlinear patterns in Urban crime: Hotspots, bifurcations, and suppression. SIAM J. Appl. Dyn. Syst. 9 (2), 462483.CrossRefGoogle Scholar
[19]Short, M. B., Brantingham, P. J. & D'orsogna, M. R. (2010) Cooperation and punishment in an adversarial game: How defectors pave the way to a peaceful society. Phys. Rev. E 82 (6), 066114.Google Scholar
[20]Short, M. B., D'orsogna, M. R., Brantingham, P. J. & Tita, G. E. (2009) Measuring and modeling repeat and near-repeat burglary effects. J. Quant. Criminology 25 (3), 325339.Google Scholar
[21]Short, M. B., D'orsogna, M. R., Pasour, V. B., Tita, G. E., Brantingham, P. J., Bertozzi, A. L. & Chayes, L. B. (2008) A statistical model of criminal behavior. Math. Models Methods Appl. Sci. 18 (supp01), 12491267.Google Scholar
[22]Short, M. B., Mohler, G. O., Brantingham, P. J. & Tita, G. E. (2012) Gang rivalry dynamics via coupled point process networks. Discrete and Continuous Dynamical Systems, 19 (5), 14591477.Google Scholar
[23]Sooknanan, J., Bhatt, B. & Comissiong, D. M. G. (2013) Catching a gang - a mathematical model of the spread of gangs in a population treated as an infectious disease. Int. J. Pure Applied Math. 83 (1), 2543.CrossRefGoogle Scholar
[24]Tompson, L., Johnson, S., Ashby, M., Perkins, C. & Edwards, P. (2014) UK open source crime data: Accuracy and possibilities for research. Cartography Geogr. Inform. Sci. 42 (2), 97111.Google Scholar