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Modelling underreported spatio-temporal crime events

Crime observations are one of the principal inputs used by governments for designing citizens’ security strategies. However, crime measurements are obscured by underreporting biases, resulting in the so-called “dark figure of crime”. This work studies the possibility of recovering “true” crime and u...

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Autores principales: Riascos Villegas, Álvaro J., Ñungo, Jose Sebastian, Gómez Tobón, Lucas, Dulce Rubio, Mateo, Gómez, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337961/
https://www.ncbi.nlm.nih.gov/pubmed/37437032
http://dx.doi.org/10.1371/journal.pone.0287776
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author Riascos Villegas, Álvaro J.
Ñungo, Jose Sebastian
Gómez Tobón, Lucas
Dulce Rubio, Mateo
Gómez, Francisco
author_facet Riascos Villegas, Álvaro J.
Ñungo, Jose Sebastian
Gómez Tobón, Lucas
Dulce Rubio, Mateo
Gómez, Francisco
author_sort Riascos Villegas, Álvaro J.
collection PubMed
description Crime observations are one of the principal inputs used by governments for designing citizens’ security strategies. However, crime measurements are obscured by underreporting biases, resulting in the so-called “dark figure of crime”. This work studies the possibility of recovering “true” crime and underreported incident rates over time using sequentially available daily data. For this, a novel underreporting model of spatiotemporal events based on the combinatorial multi-armed bandit framework was proposed. Through extensive simulations, the proposed methodology was validated for identifying the fundamental parameters of the proposed model: the “true” rates of incidence and underreporting of events. Once the proposed model was validated, crime data from a large city, Bogotá (Colombia), was used to estimate the “true” crime and underreporting rates. Our results suggest that this methodology could be used to rapidly estimate the underreporting rates of spatiotemporal events, which is a critical problem in public policy design.
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spelling pubmed-103379612023-07-13 Modelling underreported spatio-temporal crime events Riascos Villegas, Álvaro J. Ñungo, Jose Sebastian Gómez Tobón, Lucas Dulce Rubio, Mateo Gómez, Francisco PLoS One Research Article Crime observations are one of the principal inputs used by governments for designing citizens’ security strategies. However, crime measurements are obscured by underreporting biases, resulting in the so-called “dark figure of crime”. This work studies the possibility of recovering “true” crime and underreported incident rates over time using sequentially available daily data. For this, a novel underreporting model of spatiotemporal events based on the combinatorial multi-armed bandit framework was proposed. Through extensive simulations, the proposed methodology was validated for identifying the fundamental parameters of the proposed model: the “true” rates of incidence and underreporting of events. Once the proposed model was validated, crime data from a large city, Bogotá (Colombia), was used to estimate the “true” crime and underreporting rates. Our results suggest that this methodology could be used to rapidly estimate the underreporting rates of spatiotemporal events, which is a critical problem in public policy design. Public Library of Science 2023-07-12 /pmc/articles/PMC10337961/ /pubmed/37437032 http://dx.doi.org/10.1371/journal.pone.0287776 Text en © 2023 Riascos Villegas et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Riascos Villegas, Álvaro J.
Ñungo, Jose Sebastian
Gómez Tobón, Lucas
Dulce Rubio, Mateo
Gómez, Francisco
Modelling underreported spatio-temporal crime events
title Modelling underreported spatio-temporal crime events
title_full Modelling underreported spatio-temporal crime events
title_fullStr Modelling underreported spatio-temporal crime events
title_full_unstemmed Modelling underreported spatio-temporal crime events
title_short Modelling underreported spatio-temporal crime events
title_sort modelling underreported spatio-temporal crime events
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337961/
https://www.ncbi.nlm.nih.gov/pubmed/37437032
http://dx.doi.org/10.1371/journal.pone.0287776
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