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Application of Scan Statistics to Detect Suicide Clusters in Australia

BACKGROUND: Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology o...

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Autores principales: Cheung, Yee Tak Derek, Spittal, Matthew J., Williamson, Michelle Kate, Tung, Sui Jay, Pirkis, Jane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3544808/
https://www.ncbi.nlm.nih.gov/pubmed/23342098
http://dx.doi.org/10.1371/journal.pone.0054168
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author Cheung, Yee Tak Derek
Spittal, Matthew J.
Williamson, Michelle Kate
Tung, Sui Jay
Pirkis, Jane
author_facet Cheung, Yee Tak Derek
Spittal, Matthew J.
Williamson, Michelle Kate
Tung, Sui Jay
Pirkis, Jane
author_sort Cheung, Yee Tak Derek
collection PubMed
description BACKGROUND: Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. METHODS AND FINDINGS: Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. CONCLUSIONS: These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters.
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spelling pubmed-35448082013-01-22 Application of Scan Statistics to Detect Suicide Clusters in Australia Cheung, Yee Tak Derek Spittal, Matthew J. Williamson, Michelle Kate Tung, Sui Jay Pirkis, Jane PLoS One Research Article BACKGROUND: Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. METHODS AND FINDINGS: Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. CONCLUSIONS: These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. Public Library of Science 2013-01-14 /pmc/articles/PMC3544808/ /pubmed/23342098 http://dx.doi.org/10.1371/journal.pone.0054168 Text en © 2013 Cheung 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Cheung, Yee Tak Derek
Spittal, Matthew J.
Williamson, Michelle Kate
Tung, Sui Jay
Pirkis, Jane
Application of Scan Statistics to Detect Suicide Clusters in Australia
title Application of Scan Statistics to Detect Suicide Clusters in Australia
title_full Application of Scan Statistics to Detect Suicide Clusters in Australia
title_fullStr Application of Scan Statistics to Detect Suicide Clusters in Australia
title_full_unstemmed Application of Scan Statistics to Detect Suicide Clusters in Australia
title_short Application of Scan Statistics to Detect Suicide Clusters in Australia
title_sort application of scan statistics to detect suicide clusters in australia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3544808/
https://www.ncbi.nlm.nih.gov/pubmed/23342098
http://dx.doi.org/10.1371/journal.pone.0054168
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