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The heartbeat of the city

Human activity is organised around daily and weekly cycles, which should, in turn, dominate all types of social interactions, such as transactions, communications, gatherings and so on. Yet, despite their strategic importance for policing and security, cyclical weekly patterns in crime and road inci...

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Autores principales: Prieto Curiel, Rafael, Patino, Jorge Eduardo, Duque, Juan Carlos, O’Clery, Neave
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904221/
https://www.ncbi.nlm.nih.gov/pubmed/33626079
http://dx.doi.org/10.1371/journal.pone.0246714
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author Prieto Curiel, Rafael
Patino, Jorge Eduardo
Duque, Juan Carlos
O’Clery, Neave
author_facet Prieto Curiel, Rafael
Patino, Jorge Eduardo
Duque, Juan Carlos
O’Clery, Neave
author_sort Prieto Curiel, Rafael
collection PubMed
description Human activity is organised around daily and weekly cycles, which should, in turn, dominate all types of social interactions, such as transactions, communications, gatherings and so on. Yet, despite their strategic importance for policing and security, cyclical weekly patterns in crime and road incidents have been unexplored at the city and neighbourhood level. Here we construct a novel method to capture the weekly trace, or “heartbeat” of events and use geotagged data capturing the time and location of more than 200,000 violent crimes and nearly one million crashes in Mexico City. On aggregate, our findings show that the heartbeats of crime and crashes follow a similar pattern. We observe valleys during the night and peaks in the evening, where the intensity during a peak is 7.5 times the intensity of valleys in terms of crime and 12.3 times in terms of road accidents. Although distinct types of events, crimes and crashes reach their respective intensity peak on Friday night and valley on Tuesday morning, the result of a hyper-synchronised society. Next, heartbeats are computed for city neighbourhood ‘tiles’, a division of space within the city based on the distance to Metro and other public transport stations. We find that heartbeats are spatially heterogeneous with some diffusion, so that nearby tiles have similar heartbeats. Tiles are then clustered based on the shape of their heartbeat, e.g., tiles within groups suffer peaks and valleys of crime or crashes at similar times during the week. The clusters found are similar to those based on economic activities. This enables us to anticipate temporal traces of crime and crashes based on local amenities.
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spelling pubmed-79042212021-03-03 The heartbeat of the city Prieto Curiel, Rafael Patino, Jorge Eduardo Duque, Juan Carlos O’Clery, Neave PLoS One Research Article Human activity is organised around daily and weekly cycles, which should, in turn, dominate all types of social interactions, such as transactions, communications, gatherings and so on. Yet, despite their strategic importance for policing and security, cyclical weekly patterns in crime and road incidents have been unexplored at the city and neighbourhood level. Here we construct a novel method to capture the weekly trace, or “heartbeat” of events and use geotagged data capturing the time and location of more than 200,000 violent crimes and nearly one million crashes in Mexico City. On aggregate, our findings show that the heartbeats of crime and crashes follow a similar pattern. We observe valleys during the night and peaks in the evening, where the intensity during a peak is 7.5 times the intensity of valleys in terms of crime and 12.3 times in terms of road accidents. Although distinct types of events, crimes and crashes reach their respective intensity peak on Friday night and valley on Tuesday morning, the result of a hyper-synchronised society. Next, heartbeats are computed for city neighbourhood ‘tiles’, a division of space within the city based on the distance to Metro and other public transport stations. We find that heartbeats are spatially heterogeneous with some diffusion, so that nearby tiles have similar heartbeats. Tiles are then clustered based on the shape of their heartbeat, e.g., tiles within groups suffer peaks and valleys of crime or crashes at similar times during the week. The clusters found are similar to those based on economic activities. This enables us to anticipate temporal traces of crime and crashes based on local amenities. Public Library of Science 2021-02-24 /pmc/articles/PMC7904221/ /pubmed/33626079 http://dx.doi.org/10.1371/journal.pone.0246714 Text en © 2021 Prieto Curiel et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Prieto Curiel, Rafael
Patino, Jorge Eduardo
Duque, Juan Carlos
O’Clery, Neave
The heartbeat of the city
title The heartbeat of the city
title_full The heartbeat of the city
title_fullStr The heartbeat of the city
title_full_unstemmed The heartbeat of the city
title_short The heartbeat of the city
title_sort heartbeat of the city
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7904221/
https://www.ncbi.nlm.nih.gov/pubmed/33626079
http://dx.doi.org/10.1371/journal.pone.0246714
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