TY - JOUR
T1 - Towards understanding crime dynamics in a heterogeneous environment
T2 - A mathematical approach
AU - Jane White, K. A.
AU - Campillo-Funollet, Eduard
AU - Nyabadza, Farai
AU - Cusseddu, Davide
AU - Kasumo, Christian
AU - Imbusi, Nancy Matendechere
AU - Juma, Victor Ogesa
AU - Meir, A. J.
AU - Marijani, Theresia
N1 - Publisher Copyright:
© 2021 Taru Publications.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - 91C99
KW - Cape Town
KW - Criminal activity and number of criminals
KW - Criminal efficiency
KW - Mathematical model
KW - South Africa
UR - http://www.scopus.com/inward/record.url?scp=85106531440&partnerID=8YFLogxK
U2 - 10.1080/09720502.2020.1860292
DO - 10.1080/09720502.2020.1860292
M3 - Article
AN - SCOPUS:85106531440
SN - 0972-0502
VL - 24
SP - 2139
EP - 2159
JO - Journal of Interdisciplinary Mathematics
JF - Journal of Interdisciplinary Mathematics
IS - 8
ER -