Jane White, K. A., Campillo-Funollet, Eduard, Nyabadza, Farai, Cusseddu, Davide, Kasumo, Christian, Imbusi, Nancy Matendechere, Juma, Victor Ogesa, Meir, A. J., Marijani, Theresia (2021) Towards understanding crime dynamics in a heterogeneous environment: A mathematical approach. Journal of Interdisciplinary Mathematics, . ISSN 0972-0502. E-ISSN 2169-012X. (doi:10.1080/09720502.2020.1860292) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:90465)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication) | |
Official URL: https://doi.org/10.1080/09720502.2020.1860292 |
Abstract
Crime data provides information on the nature and location of the crime but, in general, does not include information on the number of criminals operating in a region. By contrast, many approaches to crime reduction necessarily involve working with criminals or individuals at risk of engaging in criminal activity and so the dynamics of the criminal population is important. With this in mind, we develop a mechanistic, mathematical model which combines the number of crimes and number of criminals to create a dynamical system. Analysis of the model highlights a threshold for criminal efficiency, below which criminal numbers will settle to an equilibrium level that can be exploited to reduce crime through prevention. This efficiency measure arises from the initiation of new criminals in response to observation of criminal activity; other initiation routes - via opportunism or peer pressure - do not exhibit such thresholds although they do impact on the level of criminal activity observed. We used data from Cape Town, South Africa, to obtain parameter estimates and predicted that the number of criminals in the region is tending towards an equilibrium point but in a heterogeneous manner - a drop in the number of criminals from low crime neighbourhoods is being offset by an increase from high crime neighbourhoods.
Item Type: | Article |
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DOI/Identification number: | 10.1080/09720502.2020.1860292 |
Uncontrolled keywords: | Mathematical model; Criminal activity and number of criminals; Criminal efficiency; Cape Town; South Africa |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
Depositing User: | Amy Boaler |
Date Deposited: | 29 Sep 2021 14:06 UTC |
Last Modified: | 05 Nov 2024 12:56 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/90465 (The current URI for this page, for reference purposes) |
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