Using the flow of people in cluster detection and inference.

Detalhes bibliográficos
Autor(a) principal: Ferreira, Sabino José
Data de Publicação: 2013
Outros Autores: Oliveira, Francisco S., Tavares, Ricardo, Moura, Flávio dos Reis
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
dARK ID: ark:/61566/001300000dsq4
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/5062
https://doi.org/10.5210/ojphi.v5i1.4554
Resumo: This work proposes a cluster detection method that adapts the traditional circular scan method, in the snese the proposed method uses the flow of people as a measure of proximity, interaction between regions of a map to identify a set of regions with a high risk of occurrence of some specific event. The flow of people between two regions is estimated by the gravitational method as proportional to the product of their gross domestic product and inversely proportional to the square of the distance between them. The performance of the proposed method was compared with the traditional circular scan simulating clusters from a database of real cases of homicides and also analyzing the real picture. In all simulated cases the proposed techniques overcame the circular scan with better results of detection power, sensibility and positive predictive value, except for regular shaped simulated clusters. When applied to the real situation of homicides cases the spatial flow scan algorithm presented results quite similar to original spatial scan since the detected cluster was regular. In conclusion we consider that the proposed method is a good alternative for detection of irregular and or non-connected clusters.
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spelling Using the flow of people in cluster detection and inference.Spatial scan statisticsSpatial flow scan algorithmGravity modelsThis work proposes a cluster detection method that adapts the traditional circular scan method, in the snese the proposed method uses the flow of people as a measure of proximity, interaction between regions of a map to identify a set of regions with a high risk of occurrence of some specific event. The flow of people between two regions is estimated by the gravitational method as proportional to the product of their gross domestic product and inversely proportional to the square of the distance between them. The performance of the proposed method was compared with the traditional circular scan simulating clusters from a database of real cases of homicides and also analyzing the real picture. In all simulated cases the proposed techniques overcame the circular scan with better results of detection power, sensibility and positive predictive value, except for regular shaped simulated clusters. When applied to the real situation of homicides cases the spatial flow scan algorithm presented results quite similar to original spatial scan since the detected cluster was regular. In conclusion we consider that the proposed method is a good alternative for detection of irregular and or non-connected clusters.2015-04-14T17:49:28Z2015-04-14T17:49:28Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFERREIRA, S. J. et al. Using the flow of people in cluster detection and inference. Online Journal of Public Health Informatics, v. 5, p. 1-1, 2013. Disponível em: <http://ojphi.org/ojs/index.php/ojphi/article/view/4554/3574>. Acesso em 13 abr. 2015.1947-2579http://www.repositorio.ufop.br/handle/123456789/5062https://doi.org/10.5210/ojphi.v5i1.4554ark:/61566/001300000dsq4This is an Open Access article distributed under the terms of the Creative Commons AttributionNoncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Fonte: o próprio artigo.info:eu-repo/semantics/openAccessFerreira, Sabino JoséOliveira, Francisco S.Tavares, RicardoMoura, Flávio dos Reisengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOP2024-11-11T01:53:44Zoai:repositorio.ufop.br:123456789/5062Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332024-11-11T01:53:44Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.none.fl_str_mv Using the flow of people in cluster detection and inference.
title Using the flow of people in cluster detection and inference.
spellingShingle Using the flow of people in cluster detection and inference.
Ferreira, Sabino José
Spatial scan statistics
Spatial flow scan algorithm
Gravity models
title_short Using the flow of people in cluster detection and inference.
title_full Using the flow of people in cluster detection and inference.
title_fullStr Using the flow of people in cluster detection and inference.
title_full_unstemmed Using the flow of people in cluster detection and inference.
title_sort Using the flow of people in cluster detection and inference.
author Ferreira, Sabino José
author_facet Ferreira, Sabino José
Oliveira, Francisco S.
Tavares, Ricardo
Moura, Flávio dos Reis
author_role author
author2 Oliveira, Francisco S.
Tavares, Ricardo
Moura, Flávio dos Reis
author2_role author
author
author
dc.contributor.author.fl_str_mv Ferreira, Sabino José
Oliveira, Francisco S.
Tavares, Ricardo
Moura, Flávio dos Reis
dc.subject.por.fl_str_mv Spatial scan statistics
Spatial flow scan algorithm
Gravity models
topic Spatial scan statistics
Spatial flow scan algorithm
Gravity models
description This work proposes a cluster detection method that adapts the traditional circular scan method, in the snese the proposed method uses the flow of people as a measure of proximity, interaction between regions of a map to identify a set of regions with a high risk of occurrence of some specific event. The flow of people between two regions is estimated by the gravitational method as proportional to the product of their gross domestic product and inversely proportional to the square of the distance between them. The performance of the proposed method was compared with the traditional circular scan simulating clusters from a database of real cases of homicides and also analyzing the real picture. In all simulated cases the proposed techniques overcame the circular scan with better results of detection power, sensibility and positive predictive value, except for regular shaped simulated clusters. When applied to the real situation of homicides cases the spatial flow scan algorithm presented results quite similar to original spatial scan since the detected cluster was regular. In conclusion we consider that the proposed method is a good alternative for detection of irregular and or non-connected clusters.
publishDate 2013
dc.date.none.fl_str_mv 2013
2015-04-14T17:49:28Z
2015-04-14T17:49:28Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv FERREIRA, S. J. et al. Using the flow of people in cluster detection and inference. Online Journal of Public Health Informatics, v. 5, p. 1-1, 2013. Disponível em: <http://ojphi.org/ojs/index.php/ojphi/article/view/4554/3574>. Acesso em 13 abr. 2015.
1947-2579
http://www.repositorio.ufop.br/handle/123456789/5062
https://doi.org/10.5210/ojphi.v5i1.4554
dc.identifier.dark.fl_str_mv ark:/61566/001300000dsq4
identifier_str_mv FERREIRA, S. J. et al. Using the flow of people in cluster detection and inference. Online Journal of Public Health Informatics, v. 5, p. 1-1, 2013. Disponível em: <http://ojphi.org/ojs/index.php/ojphi/article/view/4554/3574>. Acesso em 13 abr. 2015.
1947-2579
ark:/61566/001300000dsq4
url http://www.repositorio.ufop.br/handle/123456789/5062
https://doi.org/10.5210/ojphi.v5i1.4554
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFOP
instname:Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
instname_str Universidade Federal de Ouro Preto (UFOP)
instacron_str UFOP
institution UFOP
reponame_str Repositório Institucional da UFOP
collection Repositório Institucional da UFOP
repository.name.fl_str_mv Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)
repository.mail.fl_str_mv repositorio@ufop.edu.br
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